{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "4f968ada-aedc-4232-b7c3-ac0aee4fa868",
   "metadata": {},
   "source": [
    "# Load in necessary packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "c720c3c6-2594-4b05-8328-cbce56bcafb0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Libraries required for moisture convergence visualization\n",
    "from datetime import datetime\n",
    "import numpy as np\n",
    "import xarray as xr\n",
    "import xwrf\n",
    "import glob\n",
    "import metpy.calc as mpcalc\n",
    "import math\n",
    "\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6bc71071-5ded-4a69-802f-9861f7e7b9e4",
   "metadata": {},
   "source": [
    "### We will first identify LASSO SGP case(s) of interest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "bfb08070-26f4-4cc3-976f-655ca28ba32f",
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 255GB\n",
       "Dimensions:                    (Time: 91, y: 250, x: 250, soil_layers_stag: 5,\n",
       "                                z: 226, x_stag: 251, y_stag: 251, z_stag: 227,\n",
       "                                force_layers: 751)\n",
       "Coordinates: (12/15)\n",
       "    CLAT                       (y, x) float32 250kB dask.array&lt;chunksize=(125, 125), meta=np.ndarray&gt;\n",
       "    XLAT                       (y, x) float32 250kB dask.array&lt;chunksize=(125, 125), meta=np.ndarray&gt;\n",
       "    XLONG                      (y, x) float32 250kB dask.array&lt;chunksize=(125, 125), meta=np.ndarray&gt;\n",
       "    XTIME                      (Time) datetime64[ns] 728B dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;\n",
       "    XLAT_U                     (y, x_stag) float32 251kB dask.array&lt;chunksize=(125, 126), meta=np.ndarray&gt;\n",
       "    XLONG_U                    (y, x_stag) float32 251kB dask.array&lt;chunksize=(125, 126), meta=np.ndarray&gt;\n",
       "    ...                         ...\n",
       "  * z_stag                     (z_stag) float32 908B 1.0 0.9959 ... 0.002178 0.0\n",
       "  * Time                       (Time) datetime64[ns] 728B 2019-04-04T12:00:00...\n",
       "  * y_stag                     (y_stag) float64 2kB -1.25e+04 ... 1.25e+04\n",
       "  * y                          (y) float64 2kB -1.245e+04 ... 1.245e+04\n",
       "  * x                          (x) float64 2kB -1.245e+04 ... 1.245e+04\n",
       "  * x_stag                     (x_stag) float64 2kB -1.25e+04 ... 1.25e+04\n",
       "Dimensions without coordinates: soil_layers_stag, force_layers\n",
       "Data variables: (12/251)\n",
       "    Times                      (Time) |S19 2kB dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
       "    LU_INDEX                   (Time, y, x) float32 23MB dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;\n",
       "    ZS                         (Time, soil_layers_stag) float32 2kB dask.array&lt;chunksize=(1, 5), meta=np.ndarray&gt;\n",
       "    DZS                        (Time, soil_layers_stag) float32 2kB dask.array&lt;chunksize=(1, 5), meta=np.ndarray&gt;\n",
       "    VAR_SSO                    (Time, y, x) float32 23MB dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;\n",
       "    U                          (Time, z, y, x_stag) float32 5GB dask.array&lt;chunksize=(1, 226, 125, 126), meta=np.ndarray&gt;\n",
       "    ...                         ...\n",
       "    geopotential               (Time, z_stag, y, x) float32 5GB dask.array&lt;chunksize=(1, 227, 125, 125), meta=np.ndarray&gt;\n",
       "    geopotential_height        (Time, z_stag, y, x) float32 5GB dask.array&lt;chunksize=(1, 227, 125, 125), meta=np.ndarray&gt;\n",
       "    wind_east                  (Time, z, y, x) float32 5GB dask.array&lt;chunksize=(1, 226, 125, 125), meta=np.ndarray&gt;\n",
       "    wind_north                 (Time, z, y, x) float32 5GB dask.array&lt;chunksize=(1, 226, 125, 125), meta=np.ndarray&gt;\n",
       "    wind_east_10               (Time, y, x) float32 23MB dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;\n",
       "    wind_north_10              (Time, y, x) float32 23MB dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;\n",
       "Attributes: (12/142)\n",
       "    TITLE:                                  OUTPUT FROM WRF V3.8.1 MODEL\n",
       "    START_DATE:                            2019-04-04_12:00:00\n",
       "    SIMULATION_START_DATE:                 2019-04-04_12:00:00\n",
       "    WEST-EAST_GRID_DIMENSION:              251\n",
       "    SOUTH-NORTH_GRID_DIMENSION:            251\n",
       "    BOTTOM-TOP_GRID_DIMENSION:             227\n",
       "    ...                                    ...\n",
       "    config_aerosol:                        NA\n",
       "    config_forecast_time:                  15.0 h\n",
       "    config_boundary_method:                Periodic\n",
       "    config_microphysics:                   Thompson (mp_physics=8)\n",
       "    config_nickname:                       runlas20190404v1addhm\n",
       "    simulation_origin_host:                cumulus-login2.ccs.ornl.gov</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-5b35e744-fe8c-42ea-890e-7fd24b65d279' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5b35e744-fe8c-42ea-890e-7fd24b65d279' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>Time</span>: 91</li><li><span class='xr-has-index'>y</span>: 250</li><li><span class='xr-has-index'>x</span>: 250</li><li><span>soil_layers_stag</span>: 5</li><li><span class='xr-has-index'>z</span>: 226</li><li><span class='xr-has-index'>x_stag</span>: 251</li><li><span class='xr-has-index'>y_stag</span>: 251</li><li><span class='xr-has-index'>z_stag</span>: 227</li><li><span>force_layers</span>: 751</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-6e23eb9c-38a7-4906-a780-2c5b06eb3416' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6e23eb9c-38a7-4906-a780-2c5b06eb3416' class='xr-section-summary' >Coordinates: <span>(15)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>CLAT</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(125, 125), meta=np.ndarray&gt;</div><input id='attrs-1919808f-cc4d-43bb-a8f4-4c84407aa476' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1919808f-cc4d-43bb-a8f4-4c84407aa476' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a8ba69bd-7182-4aa0-bccc-59220569f46b' class='xr-var-data-in' type='checkbox'><label for='data-a8ba69bd-7182-4aa0-bccc-59220569f46b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>COMPUTATIONAL GRID LATITUDE, SOUTH IS NEGATIVE</dd><dt><span>units :</span></dt><dd>degree_north</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 244.14 kiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (250, 250) </td>\n",
       "                        <td> (125, 125) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 4 chunks in 34 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
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       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>XLAT</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(125, 125), meta=np.ndarray&gt;</div><input id='attrs-e81f62a9-5cc1-4293-90e9-0d221e35b08a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e81f62a9-5cc1-4293-90e9-0d221e35b08a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-208618c4-84d7-4b29-ad4d-01ccc370a5aa' class='xr-var-data-in' type='checkbox'><label for='data-208618c4-84d7-4b29-ad4d-01ccc370a5aa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>LATITUDE, SOUTH IS NEGATIVE</dd><dt><span>units :</span></dt><dd>degree_north</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 244.14 kiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (250, 250) </td>\n",
       "                        <td> (125, 125) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 4 chunks in 34 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>XLONG</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(125, 125), meta=np.ndarray&gt;</div><input id='attrs-55f8dbf4-4342-4c0d-b179-767f8622dab8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-55f8dbf4-4342-4c0d-b179-767f8622dab8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26410bb8-e2f3-4bb4-bac2-228660570e32' class='xr-var-data-in' type='checkbox'><label for='data-26410bb8-e2f3-4bb4-bac2-228660570e32' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>LONGITUDE, WEST IS NEGATIVE</dd><dt><span>units :</span></dt><dd>degree_east</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 244.14 kiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (250, 250) </td>\n",
       "                        <td> (125, 125) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 4 chunks in 34 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
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       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>XTIME</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-16e3d42a-4f99-4fd9-b7e8-72065aacde0c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-16e3d42a-4f99-4fd9-b7e8-72065aacde0c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe5dbbc4-e990-4f4a-808d-b3c3f35b3058' class='xr-var-data-in' type='checkbox'><label for='data-fe5dbbc4-e990-4f4a-808d-b3c3f35b3058' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>minutes since 2019-04-04 12:00:00</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 728 B </td>\n",
       "                        <td> 48 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (6,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> datetime64[ns] numpy.ndarray </td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>XLAT_U</span></div><div class='xr-var-dims'>(y, x_stag)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(125, 126), meta=np.ndarray&gt;</div><input id='attrs-9c94f7da-0081-458b-8673-460c51a5a5b0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9c94f7da-0081-458b-8673-460c51a5a5b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9858bcd1-4f7b-4b33-a608-62398d1eaebf' class='xr-var-data-in' type='checkbox'><label for='data-9858bcd1-4f7b-4b33-a608-62398d1eaebf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>LATITUDE, SOUTH IS NEGATIVE</dd><dt><span>units :</span></dt><dd>degree_north</dd><dt><span>stagger :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 245.12 kiB </td>\n",
       "                        <td> 61.52 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (250, 251) </td>\n",
       "                        <td> (125, 126) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 4 chunks in 34 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>XLONG_U</span></div><div class='xr-var-dims'>(y, x_stag)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(125, 126), meta=np.ndarray&gt;</div><input id='attrs-26bb4121-5e67-4b50-a70c-3a9e50fd54f4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-26bb4121-5e67-4b50-a70c-3a9e50fd54f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1c6440c5-6e25-4805-8075-c82e0dfe63d8' class='xr-var-data-in' type='checkbox'><label for='data-1c6440c5-6e25-4805-8075-c82e0dfe63d8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>LONGITUDE, WEST IS NEGATIVE</dd><dt><span>units :</span></dt><dd>degree_east</dd><dt><span>stagger :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 245.12 kiB </td>\n",
       "                        <td> 61.52 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (250, 251) </td>\n",
       "                        <td> (125, 126) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 4 chunks in 34 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>XLAT_V</span></div><div class='xr-var-dims'>(y_stag, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(126, 125), meta=np.ndarray&gt;</div><input id='attrs-6a6a72bd-8e6d-4145-b25d-9c27e3b40246' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6a6a72bd-8e6d-4145-b25d-9c27e3b40246' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a21b62ad-91ec-4e99-a7cf-80f2d77a7cff' class='xr-var-data-in' type='checkbox'><label for='data-a21b62ad-91ec-4e99-a7cf-80f2d77a7cff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>LATITUDE, SOUTH IS NEGATIVE</dd><dt><span>units :</span></dt><dd>degree_north</dd><dt><span>stagger :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 245.12 kiB </td>\n",
       "                        <td> 61.52 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 4 chunks in 34 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>XLONG_V</span></div><div class='xr-var-dims'>(y_stag, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(126, 125), meta=np.ndarray&gt;</div><input id='attrs-480c34bb-a947-4576-a8c6-866df1c63caa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-480c34bb-a947-4576-a8c6-866df1c63caa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9d7d488d-fbf3-4a68-8c8e-c76030c6a59b' class='xr-var-data-in' type='checkbox'><label for='data-9d7d488d-fbf3-4a68-8c8e-c76030c6a59b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>LONGITUDE, WEST IS NEGATIVE</dd><dt><span>units :</span></dt><dd>degree_east</dd><dt><span>stagger :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 245.12 kiB </td>\n",
       "                        <td> 61.52 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>z</span></div><div class='xr-var-dims'>(z)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.9979 0.9938 ... 0.005743 0.001089</div><input id='attrs-48a3f7bb-d123-4719-aa4a-6bde8c442103' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-48a3f7bb-d123-4719-aa4a-6bde8c442103' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8205fa12-50ca-4214-8bc3-72c524c8ac0f' class='xr-var-data-in' type='checkbox'><label for='data-8205fa12-50ca-4214-8bc3-72c524c8ac0f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>eta values on half (mass) levels</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>standard_name :</span></dt><dd>atmosphere_sigma_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([0.997944, 0.993847, 0.989777, ..., 0.01304 , 0.005743, 0.001089],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>z_stag</span></div><div class='xr-var-dims'>(z_stag)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.0 0.9959 0.9918 ... 0.002178 0.0</div><input id='attrs-4a5c899a-a4e0-4f2e-9f07-99b83b7339fb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a5c899a-a4e0-4f2e-9f07-99b83b7339fb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7c8d30b1-d8e1-4cc0-838a-d83cc46c7eb0' class='xr-var-data-in' type='checkbox'><label for='data-7c8d30b1-d8e1-4cc0-838a-d83cc46c7eb0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>eta values on full (w) levels</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd>Z</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>c_grid_axis_shift :</span></dt><dd>0.5</dd><dt><span>standard_name :</span></dt><dd>atmosphere_sigma_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1.      , 0.995887, 0.991808, ..., 0.009308, 0.002178, 0.      ],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Time</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-04-04T12:00:00 ... 2019-04-...</div><input id='attrs-f62ea981-9fc4-4195-8219-159b32cf96ab' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f62ea981-9fc4-4195-8219-159b32cf96ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e8c3deb9-7c1d-473d-8ab6-fa81a0428937' class='xr-var-data-in' type='checkbox'><label for='data-e8c3deb9-7c1d-473d-8ab6-fa81a0428937' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>minutes since 2019-04-04 12:00:00</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-04-04T12:00:00.000000000&#x27;, &#x27;2019-04-04T12:10:00.000000000&#x27;,\n",
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       "       &#x27;2019-04-04T21:20:00.000000000&#x27;, &#x27;2019-04-04T21:30:00.000000000&#x27;,\n",
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       "       &#x27;2019-04-05T02:20:00.000000000&#x27;, &#x27;2019-04-05T02:30:00.000000000&#x27;,\n",
       "       &#x27;2019-04-05T02:40:00.000000000&#x27;, &#x27;2019-04-05T02:50:00.000000000&#x27;,\n",
       "       &#x27;2019-04-05T03:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y_stag</span></div><div class='xr-var-dims'>(y_stag)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.25e+04 -1.24e+04 ... 1.25e+04</div><input id='attrs-285fec1c-3511-4092-a07e-eae4f62a0f53' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-285fec1c-3511-4092-a07e-eae4f62a0f53' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af15ec18-3d9d-49f5-82ad-238cf8eeb84f' class='xr-var-data-in' type='checkbox'><label for='data-af15ec18-3d9d-49f5-82ad-238cf8eeb84f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>c_grid_axis_shift :</span></dt><dd>0.5</dd></dl></div><div class='xr-var-data'><pre>array([-12500., -12400., -12300., ...,  12300.,  12400.,  12500.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.245e+04 -1.235e+04 ... 1.245e+04</div><input id='attrs-4bfeab5d-7e9a-4be4-8145-3e6a288a7d37' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4bfeab5d-7e9a-4be4-8145-3e6a288a7d37' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c317e692-2c66-49cd-9c5a-417662381910' class='xr-var-data-in' type='checkbox'><label for='data-c317e692-2c66-49cd-9c5a-417662381910' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-12450., -12350., -12250., ...,  12250.,  12350.,  12450.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.245e+04 -1.235e+04 ... 1.245e+04</div><input id='attrs-065da4d8-8fe7-444b-b70c-6f567aad8717' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-065da4d8-8fe7-444b-b70c-6f567aad8717' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d7a9e5b9-d414-44f0-9224-086b94b2fb5b' class='xr-var-data-in' type='checkbox'><label for='data-d7a9e5b9-d414-44f0-9224-086b94b2fb5b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([-12450., -12350., -12250., ...,  12250.,  12350.,  12450.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x_stag</span></div><div class='xr-var-dims'>(x_stag)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.25e+04 -1.24e+04 ... 1.25e+04</div><input id='attrs-755b33db-aa2f-4255-bfb6-d5a147c44895' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-755b33db-aa2f-4255-bfb6-d5a147c44895' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d8a8dcc4-df64-4c10-8a44-c5d113c80f8f' class='xr-var-data-in' type='checkbox'><label for='data-d8a8dcc4-df64-4c10-8a44-c5d113c80f8f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>c_grid_axis_shift :</span></dt><dd>0.5</dd></dl></div><div class='xr-var-data'><pre>array([-12500., -12400., -12300., ...,  12300.,  12400.,  12500.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-23f2f944-6866-4ea4-b282-fd40c42ed6f8' class='xr-section-summary-in' type='checkbox'  ><label for='section-23f2f944-6866-4ea4-b282-fd40c42ed6f8' class='xr-section-summary' >Data variables: <span>(251)</span></label><div 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       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
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       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 1.69 kiB </td>\n",
       "                        <td> 19 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (1,) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ZS</span></div><div class='xr-var-dims'>(Time, soil_layers_stag)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 5), meta=np.ndarray&gt;</div><input id='attrs-95a5b064-024f-4f7d-acaa-e22c92bf6677' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-95a5b064-024f-4f7d-acaa-e22c92bf6677' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d23f52b7-eef1-48f4-8927-3f8cc4d1546e' class='xr-var-data-in' type='checkbox'><label for='data-d23f52b7-eef1-48f4-8927-3f8cc4d1546e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>DEPTHS OF CENTERS OF SOIL LAYERS</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>stagger :</span></dt><dd>Z</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 1.78 kiB </td>\n",
       "                        <td> 20 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 5) </td>\n",
       "                        <td> (1, 5) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DZS</span></div><div class='xr-var-dims'>(Time, soil_layers_stag)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 5), meta=np.ndarray&gt;</div><input id='attrs-22e66f48-0895-4fa3-8803-52b433fc3b9b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-22e66f48-0895-4fa3-8803-52b433fc3b9b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e42a26de-fc2e-426c-b778-079cf2e768a3' class='xr-var-data-in' type='checkbox'><label for='data-e42a26de-fc2e-426c-b778-079cf2e768a3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>THICKNESSES OF SOIL LAYERS</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>stagger :</span></dt><dd>Z</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 1.78 kiB </td>\n",
       "                        <td> 20 B </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 5) </td>\n",
       "                        <td> (1, 5) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
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       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VAR_SSO</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-1810528f-f1c3-4fb8-a25f-a1cebbe43004' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1810528f-f1c3-4fb8-a25f-a1cebbe43004' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e44a609-480c-4b07-ad34-1f26f0e25e23' class='xr-var-data-in' type='checkbox'><label for='data-6e44a609-480c-4b07-ad34-1f26f0e25e23' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>Variance of Subgrid Scale Orography MSL</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>U</span></div><div class='xr-var-dims'>(Time, z, y, x_stag)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226, 125, 126), meta=np.ndarray&gt;</div><input id='attrs-381bb22c-04dd-45dd-bb4d-01133ae22b0d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-381bb22c-04dd-45dd-bb4d-01133ae22b0d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9244349c-6fd4-4bf8-bc10-ddc9ebb36c7b' class='xr-var-data-in' type='checkbox'><label for='data-9244349c-6fd4-4bf8-bc10-ddc9ebb36c7b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>x-wind component</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>stagger :</span></dt><dd>X</dd><dt><span>standard_name :</span></dt><dd>x_wind</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 364 chunks in 33 graph layers </td>\n",
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       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>V</span></div><div class='xr-var-dims'>(Time, z, y_stag, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226, 126, 125), meta=np.ndarray&gt;</div><input id='attrs-9a697c4e-4c7f-4ac2-91f1-b7bde621c93f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9a697c4e-4c7f-4ac2-91f1-b7bde621c93f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba157987-b8f5-4565-8053-99d0fc6d5c8f' class='xr-var-data-in' type='checkbox'><label for='data-ba157987-b8f5-4565-8053-99d0fc6d5c8f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>y-wind component</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>stagger :</span></dt><dd>Y</dd><dt><span>standard_name :</span></dt><dd>y_wind</dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.81 GiB </td>\n",
       "                        <td> 13.58 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1, 226, 126, 125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 364 chunks in 33 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.81 GiB </td>\n",
       "                        <td> 13.53 MiB </td>\n",
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       "                        <td> (1, 227, 125, 125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                <tbody>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>LH_FORCE_TEND</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-a590f77a-b747-4187-898d-03d2a51f02d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a590f77a-b747-4187-898d-03d2a51f02d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5bc6ceae-2439-4e88-86d5-84ee1e306419' class='xr-var-data-in' type='checkbox'><label for='data-5bc6ceae-2439-4e88-86d5-84ee1e306419' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>SCM ideal surface latent heat flux tendency</dd><dt><span>units :</span></dt><dd>W m-2 s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "                        <td> 364 B </td>\n",
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       "                    <tr>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.70 MiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
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       "                        <th> Dask graph </th>\n",
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       "                        <td> (1, 125, 125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                        <th> Data type </th>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
       "                        <td> 13.47 MiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1, 226, 125, 125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1, 226) </td>\n",
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       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>FNP</span></div><div class='xr-var-dims'>(Time, z)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226), meta=np.ndarray&gt;</div><input id='attrs-4055db17-7d6d-410b-aa8c-20ca4c0a3b7e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4055db17-7d6d-410b-aa8c-20ca4c0a3b7e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd298732-23be-4449-8f02-394a175b7740' class='xr-var-data-in' type='checkbox'><label for='data-dd298732-23be-4449-8f02-394a175b7740' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>lower weight for vertical stretching</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 80.34 kiB </td>\n",
       "                        <td> 904 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 226) </td>\n",
       "                        <td> (1, 226) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "            </table>\n",
       "        </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>RDNW</span></div><div class='xr-var-dims'>(Time, z)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226), meta=np.ndarray&gt;</div><input id='attrs-9b35ab49-944d-47e0-8e25-29bc74fd04d7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9b35ab49-944d-47e0-8e25-29bc74fd04d7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97f4d450-1ea5-4acf-a287-e331ef004852' class='xr-var-data-in' type='checkbox'><label for='data-97f4d450-1ea5-4acf-a287-e331ef004852' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>inverse d(eta) values between full (w) levels</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 80.34 kiB </td>\n",
       "                        <td> 904 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 226) </td>\n",
       "                        <td> (1, 226) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>RDN</span></div><div class='xr-var-dims'>(Time, z)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226), meta=np.ndarray&gt;</div><input id='attrs-1d5eedcd-2d5f-48f1-9f2f-f8b9f866a16d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1d5eedcd-2d5f-48f1-9f2f-f8b9f866a16d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3810a5a3-0a96-4b32-8ae0-c2e02060788c' class='xr-var-data-in' type='checkbox'><label for='data-3810a5a3-0a96-4b32-8ae0-c2e02060788c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>inverse d(eta) values between half (mass) levels</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 80.34 kiB </td>\n",
       "                        <td> 904 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 226) </td>\n",
       "                        <td> (1, 226) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DNW</span></div><div class='xr-var-dims'>(Time, z)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226), meta=np.ndarray&gt;</div><input id='attrs-401399d3-f285-4af8-aacc-0c0dd117e487' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-401399d3-f285-4af8-aacc-0c0dd117e487' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26a4e82e-7e74-431d-9827-8da207fda4f9' class='xr-var-data-in' type='checkbox'><label for='data-26a4e82e-7e74-431d-9827-8da207fda4f9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>d(eta) values between full (w) levels</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 80.34 kiB </td>\n",
       "                        <td> 904 B </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 226) </td>\n",
       "                        <td> (1, 226) </td>\n",
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       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DN</span></div><div class='xr-var-dims'>(Time, z)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226), meta=np.ndarray&gt;</div><input id='attrs-be62ceb6-0630-453c-9567-24ae3ef049d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-be62ceb6-0630-453c-9567-24ae3ef049d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-be033e92-de8a-4860-8f15-a0a947f56eab' class='xr-var-data-in' type='checkbox'><label for='data-be033e92-de8a-4860-8f15-a0a947f56eab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>d(eta) values between half (mass) levels</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 80.34 kiB </td>\n",
       "                        <td> 904 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 226) </td>\n",
       "                        <td> (1, 226) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CFN</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-439b4dea-8d68-4ff0-9def-b31b8849ec36' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-439b4dea-8d68-4ff0-9def-b31b8849ec36' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f24c9bc-86f9-4afe-a527-7f3ef2705b0b' class='xr-var-data-in' type='checkbox'><label for='data-9f24c9bc-86f9-4afe-a527-7f3ef2705b0b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>extrapolation constant</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (6,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CFN1</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-28ac4831-0214-46e6-99bf-f72bfe9f935b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-28ac4831-0214-46e6-99bf-f72bfe9f935b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cfea9923-47d0-4a44-9b55-d3cbd29c6e95' class='xr-var-data-in' type='checkbox'><label for='data-cfea9923-47d0-4a44-9b55-d3cbd29c6e95' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>extrapolation constant</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (6,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>THIS_IS_AN_IDEAL_RUN</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-db331e45-8f81-4fb9-bcef-5277b6028161' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-db331e45-8f81-4fb9-bcef-5277b6028161' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a5082b20-ad87-4da9-a58e-a58ddf073f5d' class='xr-var-data-in' type='checkbox'><label for='data-a5082b20-ad87-4da9-a58e-a58ddf073f5d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>106</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>T/F flag: this is an ARW ideal simulation</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (6,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> int32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>P_HYD</span></div><div class='xr-var-dims'>(Time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-b50c610e-a06a-460a-8b3a-1a51956d4e4f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b50c610e-a06a-460a-8b3a-1a51956d4e4f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5812f627-59d4-4dcb-9412-0bdee973ca23' class='xr-var-data-in' type='checkbox'><label for='data-5812f627-59d4-4dcb-9412-0bdee973ca23' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>hydrostatic pressure</dd><dt><span>units :</span></dt><dd>Pa</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
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       "                        <th> Dask graph </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Q2</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-7c4876f8-3f4e-401f-8fa9-9a43c856a3ed' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7c4876f8-3f4e-401f-8fa9-9a43c856a3ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c7eb1e4b-1dd8-40a7-be2b-6dffb24bfb42' class='xr-var-data-in' type='checkbox'><label for='data-c7eb1e4b-1dd8-40a7-be2b-6dffb24bfb42' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>QV at 2 M</dd><dt><span>units :</span></dt><dd>kg kg-1</dd><dt><span>stagger :</span></dt><dd></dd><dt><span>standard_name :</span></dt><dd>humidity_mixing_ratio</dd><dt><span>long_name :</span></dt><dd>humidity_mixing_ratio_at_2m_agl</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.70 MiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 250, 250) </td>\n",
       "                        <td> (1, 125, 125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>T2</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-c2f728d1-05ad-415e-8abe-1f954d5c1ffb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c2f728d1-05ad-415e-8abe-1f954d5c1ffb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bbd71f11-3a9c-494b-a4ad-27b573fae888' class='xr-var-data-in' type='checkbox'><label for='data-bbd71f11-3a9c-494b-a4ad-27b573fae888' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>TEMP at 2 M</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>stagger :</span></dt><dd></dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>long_name :</span></dt><dd>air_temperature_at_2m_agl</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "                        <td> 21.70 MiB </td>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TH2</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-926d8485-a43b-4d1f-b71d-9de41ff9cd1a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-926d8485-a43b-4d1f-b71d-9de41ff9cd1a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ceb6b42-4f96-4270-89c8-d7281f878c63' class='xr-var-data-in' type='checkbox'><label for='data-5ceb6b42-4f96-4270-89c8-d7281f878c63' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>POT TEMP at 2 M</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>stagger :</span></dt><dd></dd><dt><span>standard_name :</span></dt><dd>air_potential_temperature</dd><dt><span>long_name :</span></dt><dd>air_potential_temperature_at_2m_agl</dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
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       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.70 MiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "                        <td> (1, 125, 125) </td>\n",
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       "                        <th> Dask graph </th>\n",
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       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PSFC</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-5b357c8b-f5b4-4422-854e-3c93cf8ab03b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5b357c8b-f5b4-4422-854e-3c93cf8ab03b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af903051-6a6f-4fb6-8591-147709e2cb9d' class='xr-var-data-in' type='checkbox'><label for='data-af903051-6a6f-4fb6-8591-147709e2cb9d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>SFC PRESSURE</dd><dt><span>units :</span></dt><dd>Pa</dd><dt><span>stagger :</span></dt><dd></dd><dt><span>standard_name :</span></dt><dd>air_pressure</dd><dt><span>long_name :</span></dt><dd>air_pressure_at_surface</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.70 MiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "                        <td> (1, 125, 125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                <tbody>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>V10</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-86cede65-f3c6-4f05-b29b-baf707fc5157' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-86cede65-f3c6-4f05-b29b-baf707fc5157' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-24fb82de-f02b-4c8a-bd5e-b9c356e41e6a' class='xr-var-data-in' type='checkbox'><label for='data-24fb82de-f02b-4c8a-bd5e-b9c356e41e6a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>V at 10 M</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>stagger :</span></dt><dd></dd><dt><span>standard_name :</span></dt><dd>y_wind</dd><dt><span>long_name :</span></dt><dd>y_wind_at_10m_agl</dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>RDY</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-445f0903-2771-4183-be72-850c092b0b51' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-445f0903-2771-4183-be72-850c092b0b51' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0719906a-0486-4ddd-8436-75b6e71db6cb' class='xr-var-data-in' type='checkbox'><label for='data-0719906a-0486-4ddd-8436-75b6e71db6cb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>INVERSE Y GRID LENGTH</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (6,) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>RESM</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-818ae424-ee97-491c-a00f-d39098384c43' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-818ae424-ee97-491c-a00f-d39098384c43' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0edda090-2c4d-4d8c-a651-f478194f0d4a' class='xr-var-data-in' type='checkbox'><label for='data-0edda090-2c4d-4d8c-a651-f478194f0d4a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>TIME WEIGHT CONSTANT FOR SMALL STEPS</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (6,) </td>\n",
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       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ZETATOP</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-d913a4df-640c-49dd-940e-aa45fef94ce7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d913a4df-640c-49dd-940e-aa45fef94ce7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3cced7a-453d-424c-a57b-f4daf0d58eb8' class='xr-var-data-in' type='checkbox'><label for='data-b3cced7a-453d-424c-a57b-f4daf0d58eb8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>ZETA AT MODEL TOP</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
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       "                    <tr>\n",
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       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (6,) </td>\n",
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       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CF1</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-e8677ed7-a056-4fcf-80ea-dc8e07213585' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e8677ed7-a056-4fcf-80ea-dc8e07213585' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fa00b313-0a6a-4471-b703-32497a50ae15' class='xr-var-data-in' type='checkbox'><label for='data-fa00b313-0a6a-4471-b703-32497a50ae15' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>2nd order extrapolation constant</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
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       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (6,) </td>\n",
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       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CF2</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-1cf2600a-4614-4360-bdab-b68de9910de5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1cf2600a-4614-4360-bdab-b68de9910de5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9eec9d95-b3a3-4bc5-8daf-e51e99c15957' class='xr-var-data-in' type='checkbox'><label for='data-9eec9d95-b3a3-4bc5-8daf-e51e99c15957' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>2nd order extrapolation constant</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
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       "                        <td> (6,) </td>\n",
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       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CF3</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-76a67ce8-cf53-4b0a-8bf4-29a4b401332b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-76a67ce8-cf53-4b0a-8bf4-29a4b401332b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2ac8cfc4-2acb-446a-bbd8-5e5b32f00363' class='xr-var-data-in' type='checkbox'><label for='data-2ac8cfc4-2acb-446a-bbd8-5e5b32f00363' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>2nd order extrapolation constant</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "                        <th> Array </th>\n",
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       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (6,) </td>\n",
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       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ITIMESTEP</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-e428218f-c7f3-4a96-9de4-3fef9af5ebf8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e428218f-c7f3-4a96-9de4-3fef9af5ebf8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ecd221be-3b38-47bf-985e-82651971e82b' class='xr-var-data-in' type='checkbox'><label for='data-ecd221be-3b38-47bf-985e-82651971e82b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>106</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd></dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
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       "            <table style=\"border-collapse: collapse;\">\n",
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       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
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       "                        <td> 24 B </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (6,) </td>\n",
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       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> int32 numpy.ndarray </td>\n",
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       "                    <tr>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "                        <td> 4.79 GiB </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>QICE</span></div><div class='xr-var-dims'>(Time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-e5ec0b12-b478-40e6-9d34-312bf46fd37c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e5ec0b12-b478-40e6-9d34-312bf46fd37c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b2681ab-1c36-43a5-a05d-c5a2268bdab1' class='xr-var-data-in' type='checkbox'><label for='data-8b2681ab-1c36-43a5-a05d-c5a2268bdab1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>Ice mixing ratio</dd><dt><span>units :</span></dt><dd>kg kg-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                </thead>\n",
       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
       "                        <td> 13.47 MiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
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       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 226, 250, 250) </td>\n",
       "                        <td> (1, 226, 125, 125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>QNICE</span></div><div class='xr-var-dims'>(Time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-c0d6c9ba-af3e-4171-a218-bbe127bbc019' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c0d6c9ba-af3e-4171-a218-bbe127bbc019' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b25dd638-1617-4456-9c4d-095b847f76b2' class='xr-var-data-in' type='checkbox'><label for='data-b25dd638-1617-4456-9c4d-095b847f76b2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>Ice Number concentration</dd><dt><span>units :</span></dt><dd>  kg-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <th> Shape </th>\n",
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       "                        <th> Dask graph </th>\n",
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       "                        <th> Array </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.70 MiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 250, 250) </td>\n",
       "                        <td> (1, 125, 125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SHDMIN</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-b4a9967e-7067-464e-b686-50cf66256a12' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b4a9967e-7067-464e-b686-50cf66256a12' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-90247c7c-193a-492d-aa34-ac92ced1069c' class='xr-var-data-in' type='checkbox'><label for='data-90247c7c-193a-492d-aa34-ac92ced1069c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>ANNUAL MIN VEG FRACTION</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.70 MiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "                        <td> 21.70 MiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 108.48 MiB </td>\n",
       "                        <td> 305.18 kiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SEAICE</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-4aaa15d2-f83b-4fb1-8e1b-d932d88f54af' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4aaa15d2-f83b-4fb1-8e1b-d932d88f54af' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-637716de-5f54-487d-8a1d-de865ced4cb2' class='xr-var-data-in' type='checkbox'><label for='data-637716de-5f54-487d-8a1d-de865ced4cb2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>SEA ICE FLAG</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "                        <td> 21.70 MiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ACSNOM</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-8d178c4e-c370-4e67-a1a4-c469d90e7405' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8d178c4e-c370-4e67-a1a4-c469d90e7405' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd076fb9-3f0d-4520-b594-8f5b33a22ebd' class='xr-var-data-in' type='checkbox'><label for='data-cd076fb9-3f0d-4520-b594-8f5b33a22ebd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>ACCUMULATED MELTED SNOW</dd><dt><span>units :</span></dt><dd>kg m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
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       "                </thead>\n",
       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.70 MiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1, 125, 125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>COSZEN</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-a19d905f-ae88-419f-b10d-1a2d414e3e4f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a19d905f-ae88-419f-b10d-1a2d414e3e4f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d875547-874a-4c4c-bad6-8719d175c5db' class='xr-var-data-in' type='checkbox'><label for='data-1d875547-874a-4c4c-bad6-8719d175c5db' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>COS of SOLAR ZENITH ANGLE</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.70 MiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1, 125, 125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>LAI</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-3a0cfc18-0fab-4435-8478-47bb0ee41be7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a0cfc18-0fab-4435-8478-47bb0ee41be7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c8a28bcc-af22-4860-94a8-2b64b7e91cad' class='xr-var-data-in' type='checkbox'><label for='data-c8a28bcc-af22-4860-94a8-2b64b7e91cad' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>LEAF AREA INDEX</dd><dt><span>units :</span></dt><dd>m-2/m-2</dd><dt><span>stagger :</span></dt><dd></dd><dt><span>standard_name :</span></dt><dd>leaf_area_index</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <th> Array </th>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.70 MiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "                        <td> (1, 125, 125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.70 MiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 250, 250) </td>\n",
       "                        <td> (1, 125, 125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "        <td>\n",
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       "                </thead>\n",
       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.70 MiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1, 125, 125) </td>\n",
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       "                        <th> Dask graph </th>\n",
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       "                        <th> Data type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MAPFAC_U</span></div><div class='xr-var-dims'>(Time, y, x_stag)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 126), meta=np.ndarray&gt;</div><input id='attrs-3667919c-25d0-4b80-ac3d-154896a01891' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3667919c-25d0-4b80-ac3d-154896a01891' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb39ef09-47a5-4d26-8cf5-044188aeb0e5' class='xr-var-data-in' type='checkbox'><label for='data-bb39ef09-47a5-4d26-8cf5-044188aeb0e5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>Map scale factor on u-grid</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1, 125, 126) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                        <th> Data type </th>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.70 MiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "                        <td> (1, 125, 125) </td>\n",
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       "                        <td> 21.70 MiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
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       "                        <th> Data type </th>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.78 MiB </td>\n",
       "                        <td> 61.52 kiB </td>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1, 125, 126) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MAPFAC_VX</span></div><div class='xr-var-dims'>(Time, y_stag, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 126, 125), meta=np.ndarray&gt;</div><input id='attrs-3d6e7949-9a9b-4c25-8402-78ba05bd83a7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3d6e7949-9a9b-4c25-8402-78ba05bd83a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d9a1c15b-f0ed-429f-9ffd-e4f1798635a9' class='xr-var-data-in' type='checkbox'><label for='data-d9a1c15b-f0ed-429f-9ffd-e4f1798635a9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>Map scale factor on v-grid, x direction</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MF_VX_INV</span></div><div class='xr-var-dims'>(Time, y_stag, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 126, 125), meta=np.ndarray&gt;</div><input id='attrs-5e842f7e-544d-4640-bfbc-893e93cd146d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5e842f7e-544d-4640-bfbc-893e93cd146d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06a73409-c11c-4e4a-b09a-fc9bdb9ceadc' class='xr-var-data-in' type='checkbox'><label for='data-06a73409-c11c-4e4a-b09a-fc9bdb9ceadc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>Inverse map scale factor on v-grid, x direction</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.78 MiB </td>\n",
       "                        <td> 61.52 kiB </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1, 126, 125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.78 MiB </td>\n",
       "                        <td> 61.52 kiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1, 126, 125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                        <th> Bytes </th>\n",
       "                        <td> 21.70 MiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "                        <th> Dask graph </th>\n",
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       "                        <th> Data type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>E</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-881affef-fcea-4512-aa60-db829f7541c1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-881affef-fcea-4512-aa60-db829f7541c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-72686e01-4711-487b-a029-37b0b7d18384' class='xr-var-data-in' type='checkbox'><label for='data-72686e01-4711-487b-a029-37b0b7d18384' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>Coriolis cosine latitude term</dd><dt><span>units :</span></dt><dd>s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                <tbody>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>COSALPHA</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-1cc70554-90cd-4b23-89ab-5297d9f04f65' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1cc70554-90cd-4b23-89ab-5297d9f04f65' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a5813ba3-ef0b-4cbd-93a3-ee887ec458f9' class='xr-var-data-in' type='checkbox'><label for='data-a5813ba3-ef0b-4cbd-93a3-ee887ec458f9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>Local cosine of map rotation</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <th> Shape </th>\n",
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       "                        <th> Shape </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>P_TOP</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-c5834865-d00b-49e6-84e3-8512c3a07756' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c5834865-d00b-49e6-84e3-8512c3a07756' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b787fd0f-9be1-47ad-9741-733c13370587' class='xr-var-data-in' type='checkbox'><label for='data-b787fd0f-9be1-47ad-9741-733c13370587' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>PRESSURE TOP OF THE MODEL</dd><dt><span>units :</span></dt><dd>Pa</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
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       "                        <th> Array </th>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (6,) </td>\n",
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       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
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       "                        <th> Shape </th>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>P00</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-f1c3c2cd-d0fc-4db9-8bc0-ebae11cb479d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f1c3c2cd-d0fc-4db9-8bc0-ebae11cb479d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a5d98913-ffd4-4b69-9497-e3f468802f7c' class='xr-var-data-in' type='checkbox'><label for='data-a5d98913-ffd4-4b69-9497-e3f468802f7c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>BASE STATE PRESURE</dd><dt><span>units :</span></dt><dd>Pa</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (6,) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLP</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-d228113a-ac47-4371-9bde-4dd74ed235d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d228113a-ac47-4371-9bde-4dd74ed235d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c4ad1b1f-bc9a-4f49-8cf5-ce3113cad675' class='xr-var-data-in' type='checkbox'><label for='data-c4ad1b1f-bc9a-4f49-8cf5-ce3113cad675' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>BASE STATE LAPSE RATE</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (6,) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TISO</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-64e19704-b85b-4bf1-9a2e-3ba82517a66d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-64e19704-b85b-4bf1-9a2e-3ba82517a66d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-76b2560a-057d-41b8-a896-271e959bd6c3' class='xr-var-data-in' type='checkbox'><label for='data-76b2560a-057d-41b8-a896-271e959bd6c3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>TEMP AT WHICH THE BASE T TURNS CONST</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (6,) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLP_STRAT</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-fe9e19bd-8295-4f0c-8381-22bd74160968' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fe9e19bd-8295-4f0c-8381-22bd74160968' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97af32cc-7297-48be-bedc-0285515ddc38' class='xr-var-data-in' type='checkbox'><label for='data-97af32cc-7297-48be-bedc-0285515ddc38' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>BASE STATE LAPSE RATE (DT/D(LN(P)) IN STRATOSPHERE</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
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       "                        <td> 24 B </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (6,) </td>\n",
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       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>P_STRAT</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-99e82ddf-db2d-4ad8-baba-4ab19781377c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-99e82ddf-db2d-4ad8-baba-4ab19781377c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4bb801a0-36b9-4972-8523-4e98e311f8e2' class='xr-var-data-in' type='checkbox'><label for='data-4bb801a0-36b9-4972-8523-4e98e311f8e2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>BASE STATE PRESSURE AT BOTTOM OF STRATOSPHERE</dd><dt><span>units :</span></dt><dd>Pa</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (6,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MAX_MSTFX</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-5ac26474-2dae-407f-be34-4a08b67580bb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ac26474-2dae-407f-be34-4a08b67580bb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c06d622-d46a-4f71-aef6-7f1da261992b' class='xr-var-data-in' type='checkbox'><label for='data-8c06d622-d46a-4f71-aef6-7f1da261992b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>Max map factor in domain</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (6,) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MAX_MSTFY</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-12458a2a-a666-4bd0-86ad-8301092c98a2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-12458a2a-a666-4bd0-86ad-8301092c98a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f592910-8b75-42ee-a8fd-fa76b55b4cc4' class='xr-var-data-in' type='checkbox'><label for='data-9f592910-8b75-42ee-a8fd-fa76b55b4cc4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>Max map factor in domain</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (6,) </td>\n",
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       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                    <tr>\n",
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       "                        <th> Shape </th>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "                        <td> 21.70 MiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>GRAUPELNC</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-b0e5a032-bd6a-4868-a72f-001f2c4b1b84' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b0e5a032-bd6a-4868-a72f-001f2c4b1b84' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a751c10-1376-4deb-96af-83d87edfd958' class='xr-var-data-in' type='checkbox'><label for='data-6a751c10-1376-4deb-96af-83d87edfd958' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>ACCUMULATED TOTAL GRID SCALE GRAUPEL</dd><dt><span>units :</span></dt><dd>mm</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1, 125, 125) </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HAILNC</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-c505b92d-0708-4e99-959b-6ac4fca67148' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c505b92d-0708-4e99-959b-6ac4fca67148' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-22a91e75-1764-4c60-8efc-d30dcc8d928c' class='xr-var-data-in' type='checkbox'><label for='data-22a91e75-1764-4c60-8efc-d30dcc8d928c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>ACCUMULATED TOTAL GRID SCALE HAIL</dd><dt><span>units :</span></dt><dd>mm</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ACSWUPTC</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-04a9b7d3-0bb2-465e-80f6-c81798ac0059' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-04a9b7d3-0bb2-465e-80f6-c81798ac0059' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ab1c4f8-136a-4416-9008-7a5e77b0b63b' class='xr-var-data-in' type='checkbox'><label for='data-5ab1c4f8-136a-4416-9008-7a5e77b0b63b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>ACCUMULATED UPWELLING CLEAR SKY SHORTWAVE FLUX AT TOP</dd><dt><span>units :</span></dt><dd>J m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ACSWDNTC</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-8dbe9de5-b0fb-4da2-b509-bd4fcc6eeed5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8dbe9de5-b0fb-4da2-b509-bd4fcc6eeed5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-27e1ec18-68b6-4e1b-87c6-78ed4e49f275' class='xr-var-data-in' type='checkbox'><label for='data-27e1ec18-68b6-4e1b-87c6-78ed4e49f275' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>ACCUMULATED DOWNWELLING CLEAR SKY SHORTWAVE FLUX AT TOP</dd><dt><span>units :</span></dt><dd>J m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "                        <td> 21.70 MiB </td>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ACSWDNB</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-af7de5f4-a277-4af3-b408-c7f018f24358' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-af7de5f4-a277-4af3-b408-c7f018f24358' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b1db5c4-0c38-4ea1-93b0-05baff8c78f6' class='xr-var-data-in' type='checkbox'><label for='data-4b1db5c4-0c38-4ea1-93b0-05baff8c78f6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>ACCUMULATED DOWNWELLING SHORTWAVE FLUX AT BOTTOM</dd><dt><span>units :</span></dt><dd>J m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "                        <td> 21.70 MiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ACLWUPBC</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-44389a1d-5732-4b7b-9a20-12ddf0591e3e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-44389a1d-5732-4b7b-9a20-12ddf0591e3e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-806a6aea-f2a8-4fac-8a55-6d63b9673ed2' class='xr-var-data-in' type='checkbox'><label for='data-806a6aea-f2a8-4fac-8a55-6d63b9673ed2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>ACCUMULATED UPWELLING CLEAR SKY LONGWAVE FLUX AT BOTTOM</dd><dt><span>units :</span></dt><dd>J m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ACLWDNBC</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-4b6c4daa-e3f5-4248-a7ae-5bf809539870' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4b6c4daa-e3f5-4248-a7ae-5bf809539870' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-16587b03-4391-4734-b9b2-ec09dcea009a' class='xr-var-data-in' type='checkbox'><label for='data-16587b03-4391-4734-b9b2-ec09dcea009a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>ACCUMULATED DOWNWELLING CLEAR SKY LONGWAVE FLUX AT BOTTOM</dd><dt><span>units :</span></dt><dd>J m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "                        <td> 21.70 MiB </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>I_ACSWDNB</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-2e43a739-6376-477a-86c6-b6b80a9d53a3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2e43a739-6376-477a-86c6-b6b80a9d53a3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3bbcf8a1-2af5-474e-830d-5fb76d08f25d' class='xr-var-data-in' type='checkbox'><label for='data-3bbcf8a1-2af5-474e-830d-5fb76d08f25d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>106</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>BUCKET FOR DOWNWELLING SHORTWAVE FLUX AT BOTTOM</dd><dt><span>units :</span></dt><dd>J m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>I_ACSWDNBC</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-18c2cac9-1029-404b-9ae9-6ae7d02e8d69' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-18c2cac9-1029-404b-9ae9-6ae7d02e8d69' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d9fa0b5e-7ac5-4a85-9e06-86e7f11ca084' class='xr-var-data-in' type='checkbox'><label for='data-d9fa0b5e-7ac5-4a85-9e06-86e7f11ca084' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>106</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>BUCKET FOR DOWNWELLING CLEAR SKY SHORTWAVE FLUX AT BOTTOM</dd><dt><span>units :</span></dt><dd>J m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <th> Shape </th>\n",
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       "                        <th> Data type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>I_ACLWUPT</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-084bef20-f3de-45e9-956c-e59ef0ada8f9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-084bef20-f3de-45e9-956c-e59ef0ada8f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-73f9434b-08cb-45ad-b3fa-055b129056af' class='xr-var-data-in' type='checkbox'><label for='data-73f9434b-08cb-45ad-b3fa-055b129056af' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>106</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>BUCKET FOR UPWELLING LONGWAVE FLUX AT TOP</dd><dt><span>units :</span></dt><dd>J m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>I_ACLWUPTC</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-7c68632c-e3a4-4bc5-b4e0-54ab50bbb625' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7c68632c-e3a4-4bc5-b4e0-54ab50bbb625' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-35f11c47-2442-48ec-a94a-41aa55f5c942' class='xr-var-data-in' type='checkbox'><label for='data-35f11c47-2442-48ec-a94a-41aa55f5c942' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>106</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>BUCKET FOR UPWELLING CLEAR SKY LONGWAVE FLUX AT TOP</dd><dt><span>units :</span></dt><dd>J m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>I_ACLWDNTC</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-abab0edc-d97a-41b6-aba3-78c443e7be88' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-abab0edc-d97a-41b6-aba3-78c443e7be88' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ff23bc6-907c-4d8d-8ded-579cf9c40738' class='xr-var-data-in' type='checkbox'><label for='data-5ff23bc6-907c-4d8d-8ded-579cf9c40738' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>106</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>BUCKET FOR DOWNWELLING CLEAR SKY LONGWAVE FLUX AT TOP</dd><dt><span>units :</span></dt><dd>J m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "                        <td> 21.70 MiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "                        <td> 21.70 MiB </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SWUPBC</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-d649ebcf-ffd0-4b2f-b440-afea7767d23a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d649ebcf-ffd0-4b2f-b440-afea7767d23a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8dba8916-84a2-4130-9c9d-500f7da57033' class='xr-var-data-in' type='checkbox'><label for='data-8dba8916-84a2-4130-9c9d-500f7da57033' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>INSTANTANEOUS UPWELLING CLEAR SKY SHORTWAVE FLUX AT BOTTOM</dd><dt><span>units :</span></dt><dd>W m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SWDNBC</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-a6369b58-b31d-4824-bdad-66f62d419854' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a6369b58-b31d-4824-bdad-66f62d419854' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d250dde3-bae7-4119-94b6-a2446ad8debc' class='xr-var-data-in' type='checkbox'><label for='data-d250dde3-bae7-4119-94b6-a2446ad8debc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>INSTANTANEOUS DOWNWELLING CLEAR SKY SHORTWAVE FLUX AT BOTTOM</dd><dt><span>units :</span></dt><dd>W m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <td> 21.70 MiB </td>\n",
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       "                <tbody>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>LWDNT</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-dbe35be0-97e0-49e5-b5bd-9d485ff636e3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dbe35be0-97e0-49e5-b5bd-9d485ff636e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ae22e7e1-7402-4ad7-b8d0-26d22bcf9fbc' class='xr-var-data-in' type='checkbox'><label for='data-ae22e7e1-7402-4ad7-b8d0-26d22bcf9fbc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>INSTANTANEOUS DOWNWELLING LONGWAVE FLUX AT TOP</dd><dt><span>units :</span></dt><dd>W m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>LWUPB</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-b5527088-3157-4013-9a66-8b52e8a97f5c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b5527088-3157-4013-9a66-8b52e8a97f5c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5f6a2e09-24c4-4ef0-9a91-3f7c6658f9b0' class='xr-var-data-in' type='checkbox'><label for='data-5f6a2e09-24c4-4ef0-9a91-3f7c6658f9b0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>INSTANTANEOUS UPWELLING LONGWAVE FLUX AT BOTTOM</dd><dt><span>units :</span></dt><dd>W m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>LWUPBC</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-1a70ba9d-3e47-4ccc-9c5e-b1e36df1e5e6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1a70ba9d-3e47-4ccc-9c5e-b1e36df1e5e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f7a49908-8c22-43dc-a450-05bc92857568' class='xr-var-data-in' type='checkbox'><label for='data-f7a49908-8c22-43dc-a450-05bc92857568' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>INSTANTANEOUS UPWELLING CLEAR SKY LONGWAVE FLUX AT BOTTOM</dd><dt><span>units :</span></dt><dd>W m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ACHFX</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-beb4271e-febf-43e1-8ee5-61e777950770' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-beb4271e-febf-43e1-8ee5-61e777950770' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0fa38d5a-e598-45db-87ab-cda5830554ef' class='xr-var-data-in' type='checkbox'><label for='data-0fa38d5a-e598-45db-87ab-cda5830554ef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>ACCUMULATED UPWARD HEAT FLUX AT THE SURFACE</dd><dt><span>units :</span></dt><dd>J m-2</dd><dt><span>stagger :</span></dt><dd></dd><dt><span>standard_name :</span></dt><dd>integral_of_surface_upward_heat_flux_in_air_wrt_time</dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SR</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-33d062b6-8515-412c-baab-0d981132b546' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-33d062b6-8515-412c-baab-0d981132b546' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fd6fe7c7-c67a-4af0-bb93-64c5725f66a3' class='xr-var-data-in' type='checkbox'><label for='data-fd6fe7c7-c67a-4af0-bb93-64c5725f66a3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>fraction of frozen precipitation</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <td> (1, 125, 125) </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SAVE_TOPO_FROM_REAL</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-0803ebb3-0112-4602-bc28-27167e93a786' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0803ebb3-0112-4602-bc28-27167e93a786' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4042dda-3b6a-4bee-81c4-fc605c5d2217' class='xr-var-data-in' type='checkbox'><label for='data-d4042dda-3b6a-4bee-81c4-fc605c5d2217' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>106</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>1=original topo from real/0=topo modified by WRF</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
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       "                        <th> Array </th>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (6,) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> int32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ISEEDARR_SPPT</span></div><div class='xr-var-dims'>(Time, z)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226), meta=np.ndarray&gt;</div><input id='attrs-9cbdcc99-99c1-4cfb-9448-6c5b2e702cfb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9cbdcc99-99c1-4cfb-9448-6c5b2e702cfb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f0cd0ea-74fe-487f-90e8-f7a5672c4241' class='xr-var-data-in' type='checkbox'><label for='data-9f0cd0ea-74fe-487f-90e8-f7a5672c4241' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>106</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>Array to hold seed for restart, SPPT</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
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       "                    <tr>\n",
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       "                        <th> Array </th>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 80.34 kiB </td>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
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       "                        <td colspan=\"2\"> int32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>m22</span></div><div class='xr-var-dims'>(Time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-b01145db-a81e-48f6-93d2-3f302f9edeb7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b01145db-a81e-48f6-93d2-3f302f9edeb7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-53984c91-c02a-48ad-ab8e-489b71e369e8' class='xr-var-data-in' type='checkbox'><label for='data-53984c91-c02a-48ad-ab8e-489b71e369e8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>22 component of NBA subgrid stress tensor</dd><dt><span>units :</span></dt><dd>m2 s-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
       "                        <td> 13.47 MiB </td>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                        <th> Data type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>m33</span></div><div class='xr-var-dims'>(Time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-a1a24ddb-5121-4072-aeae-c77da76d082d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a1a24ddb-5121-4072-aeae-c77da76d082d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-11ab76f3-d417-4b78-8326-833b4302c42c' class='xr-var-data-in' type='checkbox'><label for='data-11ab76f3-d417-4b78-8326-833b4302c42c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>33 component of NBA subgrid stress tensor</dd><dt><span>units :</span></dt><dd>m2 s-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
       "                        <td> 13.47 MiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                    <tr>\n",
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       "                        <td> 13.47 MiB </td>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>V_LS_TEND</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-95ff8dc8-8eb0-4a10-852c-c58866edcf95' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-95ff8dc8-8eb0-4a10-852c-c58866edcf95' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-43bcfdc4-fb9c-4dd7-a505-3130b144607e' class='xr-var-data-in' type='checkbox'><label for='data-43bcfdc4-fb9c-4dd7-a505-3130b144607e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>tendency large-scale meridional wind velocity</dd><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 266.96 kiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "                        <td> (1, 751) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>W_LS</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-88306110-3fe2-4a80-adc5-a7ebd996f34f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-88306110-3fe2-4a80-adc5-a7ebd996f34f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9fe35761-555d-4d86-9109-d93a9904625c' class='xr-var-data-in' type='checkbox'><label for='data-9fe35761-555d-4d86-9109-d93a9904625c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>large-scale vertical velocity</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "        <td>\n",
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       "                        <th> Array </th>\n",
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       "                <tbody>\n",
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       "                        <th> Bytes </th>\n",
       "                        <td> 266.96 kiB </td>\n",
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       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>INV_TAU_S</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-71ec9623-bded-4ce9-a738-398a9be59eaa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-71ec9623-bded-4ce9-a738-398a9be59eaa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe5eae80-8eb2-4374-a716-abc5a005cbe1' class='xr-var-data-in' type='checkbox'><label for='data-fe5eae80-8eb2-4374-a716-abc5a005cbe1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>inverse relaxation time for scalars</dd><dt><span>units :</span></dt><dd>s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>INV_TAU_M</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-d835e400-a788-4349-9a7b-5584e39d6d5d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d835e400-a788-4349-9a7b-5584e39d6d5d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b5e37b9d-b17a-4b0b-9297-5346afaf7c16' class='xr-var-data-in' type='checkbox'><label for='data-b5e37b9d-b17a-4b0b-9297-5346afaf7c16' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>inverse relaxation time for scalars</dd><dt><span>units :</span></dt><dd>s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 266.96 kiB </td>\n",
       "                        <td> 2.93 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 751) </td>\n",
       "                        <td> (1, 751) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TH_ADV</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-0605d000-5829-4669-86c3-d371a11f1cdb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0605d000-5829-4669-86c3-d371a11f1cdb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e2356874-cb40-4928-900e-4a93689e4b6f' class='xr-var-data-in' type='checkbox'><label for='data-e2356874-cb40-4928-900e-4a93689e4b6f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>tendency theta advection</dd><dt><span>units :</span></dt><dd>K s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 266.96 kiB </td>\n",
       "                        <td> 2.93 kiB </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 751) </td>\n",
       "                        <td> (1, 751) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TH_ADV_TEND</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-c1232bf2-e88e-4678-b984-91bdffff5a65' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c1232bf2-e88e-4678-b984-91bdffff5a65' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b07ee18a-b4b1-47e6-b4b3-489425718fcf' class='xr-var-data-in' type='checkbox'><label for='data-b07ee18a-b4b1-47e6-b4b3-489425718fcf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>tendency of tendency theta advection</dd><dt><span>units :</span></dt><dd>K s-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 266.96 kiB </td>\n",
       "                        <td> 2.93 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 751) </td>\n",
       "                        <td> (1, 751) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TH_RLX</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-10931ce1-4b69-4b7b-b1dd-0f680667d078' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-10931ce1-4b69-4b7b-b1dd-0f680667d078' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-267f5011-2e69-4f8e-8c8c-c3be4f236069' class='xr-var-data-in' type='checkbox'><label for='data-267f5011-2e69-4f8e-8c8c-c3be4f236069' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>theta relaxation</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 266.96 kiB </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 751) </td>\n",
       "                        <td> (1, 751) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TH_RLX_TEND</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-b7148495-9da3-407e-aade-784c67f54723' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b7148495-9da3-407e-aade-784c67f54723' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4a470acd-dbef-4f3c-beba-77ba0d2d0800' class='xr-var-data-in' type='checkbox'><label for='data-4a470acd-dbef-4f3c-beba-77ba0d2d0800' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>tendency theta relaxation</dd><dt><span>units :</span></dt><dd>K s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 266.96 kiB </td>\n",
       "                        <td> 2.93 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 751) </td>\n",
       "                        <td> (1, 751) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "        </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>QV_ADV</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-3fb24aa9-f014-4095-98a9-58fcc233b696' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3fb24aa9-f014-4095-98a9-58fcc233b696' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1e010eb-9bc4-4c7f-aa14-caeffb635284' class='xr-var-data-in' type='checkbox'><label for='data-f1e010eb-9bc4-4c7f-aa14-caeffb635284' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>tendency qv advection</dd><dt><span>units :</span></dt><dd>kg kg-1 s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
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       "                <thead>\n",
       "                    <tr>\n",
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       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 266.96 kiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "                        <td> (1, 751) </td>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>QV_ADV_TEND</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-5c630bbc-4135-44b2-9bbf-1a6e179053f3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5c630bbc-4135-44b2-9bbf-1a6e179053f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-349f1d4c-83ff-4a25-880e-07709c06f4e2' class='xr-var-data-in' type='checkbox'><label for='data-349f1d4c-83ff-4a25-880e-07709c06f4e2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>tendency of tendency qv advection</dd><dt><span>units :</span></dt><dd>kg kg-1 s-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 266.96 kiB </td>\n",
       "                        <td> 2.93 kiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1, 751) </td>\n",
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       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>QV_RLX</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-b0d8cbd5-2443-4f7f-9cb3-b1b72a7f4a47' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b0d8cbd5-2443-4f7f-9cb3-b1b72a7f4a47' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3541115d-fcac-4b9f-8e9e-171c211142c0' class='xr-var-data-in' type='checkbox'><label for='data-3541115d-fcac-4b9f-8e9e-171c211142c0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>qv relaxation</dd><dt><span>units :</span></dt><dd>kg kg-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                </thead>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
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       "                        <th> Shape </th>\n",
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       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>QV_RLX_TEND</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-0dfb3c0d-78c9-4c5e-80ef-0dd9d3b8e17e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0dfb3c0d-78c9-4c5e-80ef-0dd9d3b8e17e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-df3ca801-377d-4080-985b-63e1a40df028' class='xr-var-data-in' type='checkbox'><label for='data-df3ca801-377d-4080-985b-63e1a40df028' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>tendency qv relaxation</dd><dt><span>units :</span></dt><dd>kg kg-1 s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 266.96 kiB </td>\n",
       "                        <td> 2.93 kiB </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 751) </td>\n",
       "                        <td> (1, 751) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Z_LS</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-34c9a6e0-4189-4a5a-ab09-514bfde2b4e9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-34c9a6e0-4189-4a5a-ab09-514bfde2b4e9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8f3cd457-a670-4cb0-a9c7-34e248805f5a' class='xr-var-data-in' type='checkbox'><label for='data-8f3cd457-a670-4cb0-a9c7-34e248805f5a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>z of large-scale forcings</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <th> Array </th>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Z_LS_TEND</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-a00121a9-ee30-424a-9ae3-0d6c731b35db' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a00121a9-ee30-424a-9ae3-0d6c731b35db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5522df39-3f17-4c17-a346-fedefa61ca14' class='xr-var-data-in' type='checkbox'><label for='data-5522df39-3f17-4c17-a346-fedefa61ca14' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>tendency of z of large-scale forcings</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
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       "                    <tr>\n",
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       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 266.96 kiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PRE_SH_FLX</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-c1be21f0-2490-4815-8f16-78cdaa72fe12' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c1be21f0-2490-4815-8f16-78cdaa72fe12' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2a8c40e6-5962-4e7f-8ece-da1217e0ebd8' class='xr-var-data-in' type='checkbox'><label for='data-2a8c40e6-5962-4e7f-8ece-da1217e0ebd8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>prescribed sensible heat flux</dd><dt><span>units :</span></dt><dd>W m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PRE_SH_FLX_TEND</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-ea8fbea3-9aa2-49b9-bd0d-8c95ad745453' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ea8fbea3-9aa2-49b9-bd0d-8c95ad745453' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-83cbbf08-8188-4c7f-9365-6c6f94c44119' class='xr-var-data-in' type='checkbox'><label for='data-83cbbf08-8188-4c7f-9365-6c6f94c44119' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>tendency prescribed sensible heat flux</dd><dt><span>units :</span></dt><dd>W m-2 s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (6,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PRE_LH_FLX</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-1aa65f47-12ef-4ea0-ad47-a9bce00aeea4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1aa65f47-12ef-4ea0-ad47-a9bce00aeea4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7267dbdf-d185-4681-a2d8-402c63adc798' class='xr-var-data-in' type='checkbox'><label for='data-7267dbdf-d185-4681-a2d8-402c63adc798' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>prescribed latent heat flux</dd><dt><span>units :</span></dt><dd>W m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (6,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PRE_LH_FLX_TEND</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-55153d95-a7af-4681-af4d-9212002716bb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-55153d95-a7af-4681-af4d-9212002716bb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f9f11efb-f085-49f0-ab3b-40907c630dbc' class='xr-var-data-in' type='checkbox'><label for='data-f9f11efb-f085-49f0-ab3b-40907c630dbc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>tendency prescribed latent heat flux</dd><dt><span>units :</span></dt><dd>W m-2 s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (6,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PRE_ALBEDO</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-f91e82e5-d392-4d28-8f5c-a69e8014f767' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f91e82e5-d392-4d28-8f5c-a69e8014f767' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1c132439-65e5-4918-830e-c0574b0a4f2c' class='xr-var-data-in' type='checkbox'><label for='data-1c132439-65e5-4918-830e-c0574b0a4f2c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>prescribed albedo</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
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       "                    <tr>\n",
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       "                        <th> Array </th>\n",
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       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (6,) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PRE_ALBEDO_TEND</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-790ecbae-a96d-4d10-8d45-b084a88853e8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-790ecbae-a96d-4d10-8d45-b084a88853e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2a0db59b-5d5c-452e-99db-7e70b4355cf3' class='xr-var-data-in' type='checkbox'><label for='data-2a0db59b-5d5c-452e-99db-7e70b4355cf3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>tendency prescribed albedo</dd><dt><span>units :</span></dt><dd>s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (6,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PRE_TSK</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-a0da0760-9f6d-474e-9bdb-ce953ea25b58' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a0da0760-9f6d-474e-9bdb-ce953ea25b58' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e051d50c-f694-4e55-a577-ac375a25b674' class='xr-var-data-in' type='checkbox'><label for='data-e051d50c-f694-4e55-a577-ac375a25b674' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>prescribed skin temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (6,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PRE_TSK_TEND</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-449ac85f-b028-49f5-a2b7-1a9646081e9b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-449ac85f-b028-49f5-a2b7-1a9646081e9b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-54c760d8-5c68-4665-b4c7-241e768130df' class='xr-var-data-in' type='checkbox'><label for='data-54c760d8-5c68-4665-b4c7-241e768130df' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>tendency prescribed skin temperature</dd><dt><span>units :</span></dt><dd>K s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (6,) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NUM_MODES_AER</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-ec1fc12c-23de-4563-b270-0cffafa0b0a5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ec1fc12c-23de-4563-b270-0cffafa0b0a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3dd4944c-ad9e-4342-9aef-612ef9763115' class='xr-var-data-in' type='checkbox'><label for='data-3dd4944c-ad9e-4342-9aef-612ef9763115' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>106</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>Number of aerosol distribution modes</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (6,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> int32 numpy.ndarray </td>\n",
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       "        </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>RULSTEN</span></div><div class='xr-var-dims'>(Time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-7051a7a5-a5ce-40c1-9c5f-2efbbdd41800' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7051a7a5-a5ce-40c1-9c5f-2efbbdd41800' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3ca0862-54be-4dc4-8ec1-c5e6de74becc' class='xr-var-data-in' type='checkbox'><label for='data-a3ca0862-54be-4dc4-8ec1-c5e6de74becc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>coupled u tendency due to LS forcing</dd><dt><span>units :</span></dt><dd>Pa m s-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
       "                        <td> 13.47 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1, 226, 125, 125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 364 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
       "                        <td> 13.47 MiB </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>RTHLSTEN</span></div><div class='xr-var-dims'>(Time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-51f2f8e9-743b-4668-b78e-00bfe3603755' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-51f2f8e9-743b-4668-b78e-00bfe3603755' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb614d21-9ba7-4f9a-bbf2-2acdfe9898ef' class='xr-var-data-in' type='checkbox'><label for='data-bb614d21-9ba7-4f9a-bbf2-2acdfe9898ef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>coupled theta tendency due to LS forcing</dd><dt><span>units :</span></dt><dd>Pa K s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
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       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
       "                        <td> 13.47 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1, 226, 125, 125) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 364 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                        <td> </td>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
       "                        <td> 13.47 MiB </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
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       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>THDT_LSHOR</span></div><div class='xr-var-dims'>(Time, z)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226), meta=np.ndarray&gt;</div><input id='attrs-fdde66e0-33e2-4c7e-b126-e69ae8920fde' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fdde66e0-33e2-4c7e-b126-e69ae8920fde' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6cc3ee5e-d3a9-4f24-9f7a-7fa584397f7a' class='xr-var-data-in' type='checkbox'><label for='data-6cc3ee5e-d3a9-4f24-9f7a-7fa584397f7a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>th tendency due to LS horizontal adv</dd><dt><span>units :</span></dt><dd>K s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 80.34 kiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 226) </td>\n",
       "                        <td> (1, 226) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 80.34 kiB </td>\n",
       "                        <td> 904 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 226) </td>\n",
       "                        <td> (1, 226) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>QVDT_LSRLX</span></div><div class='xr-var-dims'>(Time, z)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226), meta=np.ndarray&gt;</div><input id='attrs-c471abd9-878c-4f16-9f1e-51e5d7d5f9e3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c471abd9-878c-4f16-9f1e-51e5d7d5f9e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c4f9c567-6bf9-469f-accd-5c2151d89569' class='xr-var-data-in' type='checkbox'><label for='data-c4f9c567-6bf9-469f-accd-5c2151d89569' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>qv tendency due to relaxation to LS</dd><dt><span>units :</span></dt><dd>kg kg-1 s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 80.34 kiB </td>\n",
       "                        <td> 904 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 226) </td>\n",
       "                        <td> (1, 226) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "        </td>\n",
       "        <td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>UDT_LSRLX</span></div><div class='xr-var-dims'>(Time, z)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226), meta=np.ndarray&gt;</div><input id='attrs-f8541080-775d-4c0e-a4fe-14f52ae29982' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f8541080-775d-4c0e-a4fe-14f52ae29982' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-73f61fdc-eb72-4530-a4c7-af237acdcb98' class='xr-var-data-in' type='checkbox'><label for='data-73f61fdc-eb72-4530-a4c7-af237acdcb98' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>u tendency due to relaxation to LS</dd><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 80.34 kiB </td>\n",
       "                        <td> 904 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 226) </td>\n",
       "                        <td> (1, 226) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "            </table>\n",
       "        </td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VDT_LSRLX</span></div><div class='xr-var-dims'>(Time, z)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226), meta=np.ndarray&gt;</div><input id='attrs-4f1ad363-1bf9-40c1-af2f-732f0bc40bef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4f1ad363-1bf9-40c1-af2f-732f0bc40bef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b93b0fc7-8abd-4d2a-810a-1205eea86b56' class='xr-var-data-in' type='checkbox'><label for='data-b93b0fc7-8abd-4d2a-810a-1205eea86b56' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>v tendency due to relaxation to LS</dd><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 80.34 kiB </td>\n",
       "                        <td> 904 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 226) </td>\n",
       "                        <td> (1, 226) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "            </table>\n",
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       "        <td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EFFCS</span></div><div class='xr-var-dims'>(Time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-4494647a-e4a1-4035-8719-4dac8244ec7a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4494647a-e4a1-4035-8719-4dac8244ec7a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-75a9e28d-f78b-4672-aef7-a46aa03bd867' class='xr-var-data-in' type='checkbox'><label for='data-75a9e28d-f78b-4672-aef7-a46aa03bd867' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>CLOUD DROPLET EFFECTIVE RADIUS</dd><dt><span>units :</span></dt><dd>micron</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
       "                        <td> 13.47 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 226, 250, 250) </td>\n",
       "                        <td> (1, 226, 125, 125) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 364 chunks in 33 graph layers </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>LWF0</span></div><div class='xr-var-dims'>(Time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-1c3bf721-4206-4425-8ca1-42c91c22d46e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1c3bf721-4206-4425-8ca1-42c91c22d46e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-947a1292-8730-4fad-ab55-39b8ca8f1d72' class='xr-var-data-in' type='checkbox'><label for='data-947a1292-8730-4fad-ab55-39b8ca8f1d72' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>Net LW radiative flux</dd><dt><span>units :</span></dt><dd>W m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <td> 4.79 GiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>LWF1</span></div><div class='xr-var-dims'>(Time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-bd2411d0-6687-471d-b49b-3ce1fcbce10f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd2411d0-6687-471d-b49b-3ce1fcbce10f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7bb57bcd-135d-41ee-933b-b8d522aa6217' class='xr-var-data-in' type='checkbox'><label for='data-7bb57bcd-135d-41ee-933b-b8d522aa6217' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>Net LW radiative flux, term1</dd><dt><span>units :</span></dt><dd>W m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
       "                        <td> 13.47 MiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SEDFQR</span></div><div class='xr-var-dims'>(Time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-1b88ec90-bbb1-466c-a846-4502ed8f21cc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1b88ec90-bbb1-466c-a846-4502ed8f21cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-104cefd2-4cdf-4f82-afdb-f2f170b00032' class='xr-var-data-in' type='checkbox'><label for='data-104cefd2-4cdf-4f82-afdb-f2f170b00032' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>sedimentation flux of rain water</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
       "                        <td> 13.47 MiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                        <th> Data type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>QVDT_COND</span></div><div class='xr-var-dims'>(Time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-347edf9a-5791-4ce6-b2f0-0b4814a46e52' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-347edf9a-5791-4ce6-b2f0-0b4814a46e52' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cdb9f944-4f25-49df-a573-65612594183c' class='xr-var-data-in' type='checkbox'><label for='data-cdb9f944-4f25-49df-a573-65612594183c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>Production rate of vapor by conversion to rain</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "                        <td> 4.79 GiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SST</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-1a0f0b76-5dcc-45b6-96ab-0f0d00a57565' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1a0f0b76-5dcc-45b6-96ab-0f0d00a57565' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fc696900-0238-404b-94e9-8fc894c854d6' class='xr-var-data-in' type='checkbox'><label for='data-fc696900-0238-404b-94e9-8fc894c854d6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>SEA SURFACE TEMPERATURE</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <th> Shape </th>\n",
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       "                        <th> Data type </th>\n",
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       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
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       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
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       "        <td>\n",
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       "                    <tr>\n",
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       "                        <th> Array </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.81 GiB </td>\n",
       "                        <td> 13.53 MiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1, 227, 125, 125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                        <th> Data type </th>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.81 GiB </td>\n",
       "                        <td> 13.53 MiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "                        <td> (1, 227, 125, 125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                <tbody>\n",
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       "                        <td> 4.79 GiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "                        <th> Bytes </th>\n",
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       "                        <td> 61.04 kiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "                        <td> (1, 125, 125) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 364 chunks in 135 graph layers </td>\n",
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       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wind_north_10</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-3cc94a5f-2e27-4361-be96-3655a0390928' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3cc94a5f-2e27-4361-be96-3655a0390928' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af96911d-6e88-4e44-a620-ecd1b0d1baf2' class='xr-var-data-in' type='checkbox'><label for='data-af96911d-6e88-4e44-a620-ecd1b0d1baf2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>earth-relative 10m y-wind component</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>grid_mapping :</span></dt><dd>wrf_projection</dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.70 MiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 250, 250) </td>\n",
       "                        <td> (1, 125, 125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 364 chunks in 135 graph layers </td>\n",
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       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "          0.9857232570648193,    0.9816849231719971,    0.9776613116264343,\n",
       "          0.9736500978469849,    0.9696520566940308,    0.9656686782836914,\n",
       "          0.9616985321044922,\n",
       "       ...\n",
       "         0.07436569780111313,   0.06433471292257309,  0.054764386266469955,\n",
       "         0.04565010964870453,   0.03694861754775047,   0.02862708829343319,\n",
       "        0.020665660500526428,  0.013039967976510525,  0.005742852110415697,\n",
       "       0.0010888208635151386],\n",
       "      dtype=&#x27;float32&#x27;, name=&#x27;z&#x27;, length=226))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>z_stag</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8474f8d1-3036-42e6-8202-ad29cb861279' class='xr-index-data-in' type='checkbox'/><label for='index-8474f8d1-3036-42e6-8202-ad29cb861279' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([                  1.0,    0.9958871603012085,    0.9918078780174255,\n",
       "            0.98774653673172,    0.9837000370025635,    0.9796698093414307,\n",
       "           0.975652813911438,    0.9716474413871765,    0.9676567316055298,\n",
       "          0.9636806845664978,\n",
       "       ...\n",
       "         0.06923836469650269,  0.059431057423353195,  0.050097715109586716,\n",
       "         0.04120250791311264,  0.032694727182388306,  0.024559449404478073,\n",
       "        0.016771873459219933,  0.009308062493801117, 0.0021776417270302773,\n",
       "                         0.0],\n",
       "      dtype=&#x27;float32&#x27;, name=&#x27;z_stag&#x27;, length=227))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>Time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bb4ee067-0b66-4b1c-88ce-d84a23245f5c' class='xr-index-data-in' type='checkbox'/><label for='index-bb4ee067-0b66-4b1c-88ce-d84a23245f5c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2019-04-04 12:00:00&#x27;, &#x27;2019-04-04 12:10:00&#x27;,\n",
       "               &#x27;2019-04-04 12:20:00&#x27;, &#x27;2019-04-04 12:30:00&#x27;,\n",
       "               &#x27;2019-04-04 12:40:00&#x27;, &#x27;2019-04-04 12:50:00&#x27;,\n",
       "               &#x27;2019-04-04 13:00:00&#x27;, &#x27;2019-04-04 13:10:00&#x27;,\n",
       "               &#x27;2019-04-04 13:20:00&#x27;, &#x27;2019-04-04 13:30:00&#x27;,\n",
       "               &#x27;2019-04-04 13:40:00&#x27;, &#x27;2019-04-04 13:50:00&#x27;,\n",
       "               &#x27;2019-04-04 14:00:00&#x27;, &#x27;2019-04-04 14:10:00&#x27;,\n",
       "               &#x27;2019-04-04 14:20:00&#x27;, &#x27;2019-04-04 14:30:00&#x27;,\n",
       "               &#x27;2019-04-04 14:40:00&#x27;, &#x27;2019-04-04 14:50:00&#x27;,\n",
       "               &#x27;2019-04-04 15:00:00&#x27;, &#x27;2019-04-04 15:10:00&#x27;,\n",
       "               &#x27;2019-04-04 15:20:00&#x27;, &#x27;2019-04-04 15:30:00&#x27;,\n",
       "               &#x27;2019-04-04 15:40:00&#x27;, &#x27;2019-04-04 15:50:00&#x27;,\n",
       "               &#x27;2019-04-04 16:00:00&#x27;, &#x27;2019-04-04 16:10:00&#x27;,\n",
       "               &#x27;2019-04-04 16:20:00&#x27;, &#x27;2019-04-04 16:30:00&#x27;,\n",
       "               &#x27;2019-04-04 16:40:00&#x27;, &#x27;2019-04-04 16:50:00&#x27;,\n",
       "               &#x27;2019-04-04 17:00:00&#x27;, &#x27;2019-04-04 17:10:00&#x27;,\n",
       "               &#x27;2019-04-04 17:20:00&#x27;, &#x27;2019-04-04 17:30:00&#x27;,\n",
       "               &#x27;2019-04-04 17:40:00&#x27;, &#x27;2019-04-04 17:50:00&#x27;,\n",
       "               &#x27;2019-04-04 18:00:00&#x27;, &#x27;2019-04-04 18:10:00&#x27;,\n",
       "               &#x27;2019-04-04 18:20:00&#x27;, &#x27;2019-04-04 18:30:00&#x27;,\n",
       "               &#x27;2019-04-04 18:40:00&#x27;, &#x27;2019-04-04 18:50:00&#x27;,\n",
       "               &#x27;2019-04-04 19:00:00&#x27;, &#x27;2019-04-04 19:10:00&#x27;,\n",
       "               &#x27;2019-04-04 19:20:00&#x27;, &#x27;2019-04-04 19:30:00&#x27;,\n",
       "               &#x27;2019-04-04 19:40:00&#x27;, &#x27;2019-04-04 19:50:00&#x27;,\n",
       "               &#x27;2019-04-04 20:00:00&#x27;, &#x27;2019-04-04 20:10:00&#x27;,\n",
       "               &#x27;2019-04-04 20:20:00&#x27;, &#x27;2019-04-04 20:30:00&#x27;,\n",
       "               &#x27;2019-04-04 20:40:00&#x27;, &#x27;2019-04-04 20:50:00&#x27;,\n",
       "               &#x27;2019-04-04 21:00:00&#x27;, &#x27;2019-04-04 21:10:00&#x27;,\n",
       "               &#x27;2019-04-04 21:20:00&#x27;, &#x27;2019-04-04 21:30:00&#x27;,\n",
       "               &#x27;2019-04-04 21:40:00&#x27;, &#x27;2019-04-04 21:50:00&#x27;,\n",
       "               &#x27;2019-04-04 22:00:00&#x27;, &#x27;2019-04-04 22:10:00&#x27;,\n",
       "               &#x27;2019-04-04 22:20:00&#x27;, &#x27;2019-04-04 22:30:00&#x27;,\n",
       "               &#x27;2019-04-04 22:40:00&#x27;, &#x27;2019-04-04 22:50:00&#x27;,\n",
       "               &#x27;2019-04-04 23:00:00&#x27;, &#x27;2019-04-04 23:10:00&#x27;,\n",
       "               &#x27;2019-04-04 23:20:00&#x27;, &#x27;2019-04-04 23:30:00&#x27;,\n",
       "               &#x27;2019-04-04 23:40:00&#x27;, &#x27;2019-04-04 23:50:00&#x27;,\n",
       "               &#x27;2019-04-05 00:00:00&#x27;, &#x27;2019-04-05 00:10:00&#x27;,\n",
       "               &#x27;2019-04-05 00:20:00&#x27;, &#x27;2019-04-05 00:30:00&#x27;,\n",
       "               &#x27;2019-04-05 00:40:00&#x27;, &#x27;2019-04-05 00:50:00&#x27;,\n",
       "               &#x27;2019-04-05 01:00:00&#x27;, &#x27;2019-04-05 01:10:00&#x27;,\n",
       "               &#x27;2019-04-05 01:20:00&#x27;, &#x27;2019-04-05 01:30:00&#x27;,\n",
       "               &#x27;2019-04-05 01:40:00&#x27;, &#x27;2019-04-05 01:50:00&#x27;,\n",
       "               &#x27;2019-04-05 02:00:00&#x27;, &#x27;2019-04-05 02:10:00&#x27;,\n",
       "               &#x27;2019-04-05 02:20:00&#x27;, &#x27;2019-04-05 02:30:00&#x27;,\n",
       "               &#x27;2019-04-05 02:40:00&#x27;, &#x27;2019-04-05 02:50:00&#x27;,\n",
       "               &#x27;2019-04-05 03:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;Time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y_stag</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-cd676b8f-dee9-4415-b8f0-1c128d1a3544' class='xr-index-data-in' type='checkbox'/><label for='index-cd676b8f-dee9-4415-b8f0-1c128d1a3544' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-12500.0, -12400.0, -12300.0, -12200.0, -12100.0, -12000.0, -11900.0,\n",
       "       -11800.0, -11700.0, -11600.0,\n",
       "       ...\n",
       "        11600.0,  11700.0,  11800.0,  11900.0,  12000.0,  12100.0,  12200.0,\n",
       "        12300.0,  12400.0,  12500.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;y_stag&#x27;, length=251))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-16c83b25-dab9-4066-a205-7e23f0edee2c' class='xr-index-data-in' type='checkbox'/><label for='index-16c83b25-dab9-4066-a205-7e23f0edee2c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-12450.0, -12350.0, -12250.0, -12150.0, -12050.0, -11950.0, -11850.0,\n",
       "       -11750.0, -11650.0, -11550.0,\n",
       "       ...\n",
       "        11550.0,  11650.0,  11750.0,  11850.0,  11950.0,  12050.0,  12150.0,\n",
       "        12250.0,  12350.0,  12450.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=250))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-62591188-d2f6-4c89-b652-0341f6a62150' class='xr-index-data-in' type='checkbox'/><label for='index-62591188-d2f6-4c89-b652-0341f6a62150' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-12450.0, -12350.0, -12250.0, -12150.0, -12050.0, -11950.0, -11850.0,\n",
       "       -11750.0, -11650.0, -11550.0,\n",
       "       ...\n",
       "        11550.0,  11650.0,  11750.0,  11850.0,  11950.0,  12050.0,  12150.0,\n",
       "        12250.0,  12350.0,  12450.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=250))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x_stag</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-6bd21250-7eb7-4938-9bf5-cbf6fbef93b0' class='xr-index-data-in' type='checkbox'/><label for='index-6bd21250-7eb7-4938-9bf5-cbf6fbef93b0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-12500.0, -12400.0, -12300.0, -12200.0, -12100.0, -12000.0, -11900.0,\n",
       "       -11800.0, -11700.0, -11600.0,\n",
       "       ...\n",
       "        11600.0,  11700.0,  11800.0,  11900.0,  12000.0,  12100.0,  12200.0,\n",
       "        12300.0,  12400.0,  12500.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;x_stag&#x27;, length=251))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-41277c88-c58a-4586-9360-3d976bc5f632' class='xr-section-summary-in' type='checkbox'  ><label for='section-41277c88-c58a-4586-9360-3d976bc5f632' class='xr-section-summary' >Attributes: <span>(142)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>TITLE :</span></dt><dd> OUTPUT FROM WRF V3.8.1 MODEL</dd><dt><span>START_DATE :</span></dt><dd>2019-04-04_12:00:00</dd><dt><span>SIMULATION_START_DATE :</span></dt><dd>2019-04-04_12:00:00</dd><dt><span>WEST-EAST_GRID_DIMENSION :</span></dt><dd>251</dd><dt><span>SOUTH-NORTH_GRID_DIMENSION :</span></dt><dd>251</dd><dt><span>BOTTOM-TOP_GRID_DIMENSION :</span></dt><dd>227</dd><dt><span>DX :</span></dt><dd>100.0</dd><dt><span>DY :</span></dt><dd>100.0</dd><dt><span>SKEBS_ON :</span></dt><dd>0</dd><dt><span>SPEC_BDY_FINAL_MU :</span></dt><dd>1</dd><dt><span>USE_Q_DIABATIC :</span></dt><dd>0</dd><dt><span>GRIDTYPE :</span></dt><dd>C</dd><dt><span>DIFF_OPT :</span></dt><dd>2</dd><dt><span>KM_OPT :</span></dt><dd>2</dd><dt><span>DAMP_OPT :</span></dt><dd>3</dd><dt><span>DAMPCOEF :</span></dt><dd>0.2</dd><dt><span>KHDIF :</span></dt><dd>1.0</dd><dt><span>KVDIF :</span></dt><dd>1.0</dd><dt><span>MP_PHYSICS :</span></dt><dd>8</dd><dt><span>RA_LW_PHYSICS :</span></dt><dd>4</dd><dt><span>RA_SW_PHYSICS :</span></dt><dd>4</dd><dt><span>SF_SFCLAY_PHYSICS :</span></dt><dd>1</dd><dt><span>SF_SURFACE_PHYSICS :</span></dt><dd>1</dd><dt><span>BL_PBL_PHYSICS :</span></dt><dd>0</dd><dt><span>CU_PHYSICS :</span></dt><dd>0</dd><dt><span>SF_LAKE_PHYSICS :</span></dt><dd>0</dd><dt><span>SURFACE_INPUT_SOURCE :</span></dt><dd>3</dd><dt><span>SST_UPDATE :</span></dt><dd>0</dd><dt><span>GRID_FDDA :</span></dt><dd>0</dd><dt><span>GFDDA_INTERVAL_M :</span></dt><dd>0</dd><dt><span>GFDDA_END_H :</span></dt><dd>0</dd><dt><span>GRID_SFDDA :</span></dt><dd>0</dd><dt><span>SGFDDA_INTERVAL_M :</span></dt><dd>0</dd><dt><span>SGFDDA_END_H :</span></dt><dd>0</dd><dt><span>HYPSOMETRIC_OPT :</span></dt><dd>1</dd><dt><span>USE_THETA_M :</span></dt><dd>1</dd><dt><span>SF_URBAN_PHYSICS :</span></dt><dd>0</dd><dt><span>SHCU_PHYSICS :</span></dt><dd>0</dd><dt><span>MFSHCONV :</span></dt><dd>0</dd><dt><span>FEEDBACK :</span></dt><dd>0</dd><dt><span>SMOOTH_OPTION :</span></dt><dd>0</dd><dt><span>SWRAD_SCAT :</span></dt><dd>1.0</dd><dt><span>W_DAMPING :</span></dt><dd>0</dd><dt><span>RADT :</span></dt><dd>1.0</dd><dt><span>BLDT :</span></dt><dd>0.0</dd><dt><span>CUDT :</span></dt><dd>0.0</dd><dt><span>AER_OPT :</span></dt><dd>0</dd><dt><span>SWINT_OPT :</span></dt><dd>0</dd><dt><span>AER_TYPE :</span></dt><dd>1</dd><dt><span>AER_AOD550_OPT :</span></dt><dd>1</dd><dt><span>AER_ANGEXP_OPT :</span></dt><dd>1</dd><dt><span>AER_SSA_OPT :</span></dt><dd>1</dd><dt><span>AER_ASY_OPT :</span></dt><dd>1</dd><dt><span>AER_AOD550_VAL :</span></dt><dd>0.12</dd><dt><span>AER_ANGEXP_VAL :</span></dt><dd>1.3</dd><dt><span>AER_SSA_VAL :</span></dt><dd>1e-45</dd><dt><span>AER_ASY_VAL :</span></dt><dd>1e-45</dd><dt><span>MOIST_ADV_OPT :</span></dt><dd>2</dd><dt><span>SCALAR_ADV_OPT :</span></dt><dd>2</dd><dt><span>TKE_ADV_OPT :</span></dt><dd>2</dd><dt><span>DIFF_6TH_OPT :</span></dt><dd>0</dd><dt><span>DIFF_6TH_FACTOR :</span></dt><dd>0.12</dd><dt><span>OBS_NUDGE_OPT :</span></dt><dd>0</dd><dt><span>BUCKET_MM :</span></dt><dd>-1.0</dd><dt><span>BUCKET_J :</span></dt><dd>-1.0</dd><dt><span>PREC_ACC_DT :</span></dt><dd>0.0</dd><dt><span>SF_OCEAN_PHYSICS :</span></dt><dd>0</dd><dt><span>ISFTCFLX :</span></dt><dd>0</dd><dt><span>ISHALLOW :</span></dt><dd>0</dd><dt><span>ISFFLX :</span></dt><dd>11</dd><dt><span>ICLOUD :</span></dt><dd>1</dd><dt><span>ICLOUD_CU :</span></dt><dd>0</dd><dt><span>TRACER_PBLMIX :</span></dt><dd>1</dd><dt><span>SCALAR_PBLMIX :</span></dt><dd>0</dd><dt><span>YSU_TOPDOWN_PBLMIX :</span></dt><dd>0</dd><dt><span>GRAV_SETTLING :</span></dt><dd>0</dd><dt><span>DFI_OPT :</span></dt><dd>0</dd><dt><span>SIMULATION_INITIALIZATION_TYPE :</span></dt><dd>IDEALIZED DATA</dd><dt><span>WEST-EAST_PATCH_START_UNSTAG :</span></dt><dd>1</dd><dt><span>WEST-EAST_PATCH_END_UNSTAG :</span></dt><dd>250</dd><dt><span>WEST-EAST_PATCH_START_STAG :</span></dt><dd>1</dd><dt><span>WEST-EAST_PATCH_END_STAG :</span></dt><dd>251</dd><dt><span>SOUTH-NORTH_PATCH_START_UNSTAG :</span></dt><dd>1</dd><dt><span>SOUTH-NORTH_PATCH_END_UNSTAG :</span></dt><dd>250</dd><dt><span>SOUTH-NORTH_PATCH_START_STAG :</span></dt><dd>1</dd><dt><span>SOUTH-NORTH_PATCH_END_STAG :</span></dt><dd>251</dd><dt><span>BOTTOM-TOP_PATCH_START_UNSTAG :</span></dt><dd>1</dd><dt><span>BOTTOM-TOP_PATCH_END_UNSTAG :</span></dt><dd>226</dd><dt><span>BOTTOM-TOP_PATCH_START_STAG :</span></dt><dd>1</dd><dt><span>BOTTOM-TOP_PATCH_END_STAG :</span></dt><dd>227</dd><dt><span>GRID_ID :</span></dt><dd>1</dd><dt><span>PARENT_ID :</span></dt><dd>0</dd><dt><span>I_PARENT_START :</span></dt><dd>0</dd><dt><span>J_PARENT_START :</span></dt><dd>0</dd><dt><span>PARENT_GRID_RATIO :</span></dt><dd>1</dd><dt><span>DT :</span></dt><dd>0.5</dd><dt><span>CEN_LAT :</span></dt><dd>0.0</dd><dt><span>CEN_LON :</span></dt><dd>0.0</dd><dt><span>TRUELAT1 :</span></dt><dd>0.0</dd><dt><span>TRUELAT2 :</span></dt><dd>0.0</dd><dt><span>MOAD_CEN_LAT :</span></dt><dd>0.0</dd><dt><span>STAND_LON :</span></dt><dd>0.0</dd><dt><span>POLE_LAT :</span></dt><dd>0.0</dd><dt><span>POLE_LON :</span></dt><dd>0.0</dd><dt><span>GMT :</span></dt><dd>0.0</dd><dt><span>JULYR :</span></dt><dd>0</dd><dt><span>JULDAY :</span></dt><dd>1</dd><dt><span>MAP_PROJ :</span></dt><dd>0</dd><dt><span>MAP_PROJ_CHAR :</span></dt><dd>Cartesian</dd><dt><span>MMINLU :</span></dt><dd></dd><dt><span>NUM_LAND_CAT :</span></dt><dd>21</dd><dt><span>ISWATER :</span></dt><dd>16</dd><dt><span>ISLAKE :</span></dt><dd>0</dd><dt><span>ISICE :</span></dt><dd>0</dd><dt><span>ISURBAN :</span></dt><dd>0</dd><dt><span>ISOILWATER :</span></dt><dd>0</dd><dt><span>doi :</span></dt><dd>10.5439/1342961</dd><dt><span>contacts :</span></dt><dd>lasso@arm.gov, LASSO PI: William Gustafson (William.Gustafson@pnnl.gov), LASSO Co-PI: Andrew Vogelmann (vogelmann@bnl.gov)</dd><dt><span>site_id :</span></dt><dd>sgp</dd><dt><span>facility_id :</span></dt><dd>C1</dd><dt><span>location_description :</span></dt><dd>Southern Great Plains (SGP), Lamont, Oklahoma</dd><dt><span>date :</span></dt><dd>20190404</dd><dt><span>simulation_id_number :</span></dt><dd>4</dd><dt><span>model_type :</span></dt><dd>WRF</dd><dt><span>model_version :</span></dt><dd>3.8.1</dd><dt><span>model_github_hash :</span></dt><dd>b6b6a5cc4229eec1ea9b005746b5ebef2205fb07</dd><dt><span>output_domain_size :</span></dt><dd>25.0 km</dd><dt><span>output_number_of_levels :</span></dt><dd>226</dd><dt><span>output_horizontal_grid_spacing :</span></dt><dd>100 m</dd><dt><span>config_large_scale_forcing :</span></dt><dd>ECMWF</dd><dt><span>config_large_scale_forcing_scale :</span></dt><dd>114 km</dd><dt><span>config_large_scale_forcing_specifics :</span></dt><dd>sgpecmwfvarX1.c1,sgpecmwftenX1.c1,sgpecmwfsfc1lX1.c1,sgpecmwfsfceX1.c1 (v20191206)</dd><dt><span>config_surface_treatment :</span></dt><dd>VARANAL</dd><dt><span>config_surface_treatment_specifics :</span></dt><dd>sgp60varanarapC1.c1 (v20191126)</dd><dt><span>config_initial_condition :</span></dt><dd>Sounding</dd><dt><span>config_initial_condition_specifics :</span></dt><dd>sgpsondewnpnC1</dd><dt><span>config_aerosol :</span></dt><dd>NA</dd><dt><span>config_forecast_time :</span></dt><dd>15.0 h</dd><dt><span>config_boundary_method :</span></dt><dd>Periodic</dd><dt><span>config_microphysics :</span></dt><dd>Thompson (mp_physics=8)</dd><dt><span>config_nickname :</span></dt><dd>runlas20190404v1addhm</dd><dt><span>simulation_origin_host :</span></dt><dd>cumulus-login2.ccs.ornl.gov</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 255GB\n",
       "Dimensions:                    (Time: 91, y: 250, x: 250, soil_layers_stag: 5,\n",
       "                                z: 226, x_stag: 251, y_stag: 251, z_stag: 227,\n",
       "                                force_layers: 751)\n",
       "Coordinates: (12/15)\n",
       "    CLAT                       (y, x) float32 250kB dask.array<chunksize=(125, 125), meta=np.ndarray>\n",
       "    XLAT                       (y, x) float32 250kB dask.array<chunksize=(125, 125), meta=np.ndarray>\n",
       "    XLONG                      (y, x) float32 250kB dask.array<chunksize=(125, 125), meta=np.ndarray>\n",
       "    XTIME                      (Time) datetime64[ns] 728B dask.array<chunksize=(6,), meta=np.ndarray>\n",
       "    XLAT_U                     (y, x_stag) float32 251kB dask.array<chunksize=(125, 126), meta=np.ndarray>\n",
       "    XLONG_U                    (y, x_stag) float32 251kB dask.array<chunksize=(125, 126), meta=np.ndarray>\n",
       "    ...                         ...\n",
       "  * z_stag                     (z_stag) float32 908B 1.0 0.9959 ... 0.002178 0.0\n",
       "  * Time                       (Time) datetime64[ns] 728B 2019-04-04T12:00:00...\n",
       "  * y_stag                     (y_stag) float64 2kB -1.25e+04 ... 1.25e+04\n",
       "  * y                          (y) float64 2kB -1.245e+04 ... 1.245e+04\n",
       "  * x                          (x) float64 2kB -1.245e+04 ... 1.245e+04\n",
       "  * x_stag                     (x_stag) float64 2kB -1.25e+04 ... 1.25e+04\n",
       "Dimensions without coordinates: soil_layers_stag, force_layers\n",
       "Data variables: (12/251)\n",
       "    Times                      (Time) |S19 2kB dask.array<chunksize=(1,), meta=np.ndarray>\n",
       "    LU_INDEX                   (Time, y, x) float32 23MB dask.array<chunksize=(1, 125, 125), meta=np.ndarray>\n",
       "    ZS                         (Time, soil_layers_stag) float32 2kB dask.array<chunksize=(1, 5), meta=np.ndarray>\n",
       "    DZS                        (Time, soil_layers_stag) float32 2kB dask.array<chunksize=(1, 5), meta=np.ndarray>\n",
       "    VAR_SSO                    (Time, y, x) float32 23MB dask.array<chunksize=(1, 125, 125), meta=np.ndarray>\n",
       "    U                          (Time, z, y, x_stag) float32 5GB dask.array<chunksize=(1, 226, 125, 126), meta=np.ndarray>\n",
       "    ...                         ...\n",
       "    geopotential               (Time, z_stag, y, x) float32 5GB dask.array<chunksize=(1, 227, 125, 125), meta=np.ndarray>\n",
       "    geopotential_height        (Time, z_stag, y, x) float32 5GB dask.array<chunksize=(1, 227, 125, 125), meta=np.ndarray>\n",
       "    wind_east                  (Time, z, y, x) float32 5GB dask.array<chunksize=(1, 226, 125, 125), meta=np.ndarray>\n",
       "    wind_north                 (Time, z, y, x) float32 5GB dask.array<chunksize=(1, 226, 125, 125), meta=np.ndarray>\n",
       "    wind_east_10               (Time, y, x) float32 23MB dask.array<chunksize=(1, 125, 125), meta=np.ndarray>\n",
       "    wind_north_10              (Time, y, x) float32 23MB dask.array<chunksize=(1, 125, 125), meta=np.ndarray>\n",
       "Attributes: (12/142)\n",
       "    TITLE:                                  OUTPUT FROM WRF V3.8.1 MODEL\n",
       "    START_DATE:                            2019-04-04_12:00:00\n",
       "    SIMULATION_START_DATE:                 2019-04-04_12:00:00\n",
       "    WEST-EAST_GRID_DIMENSION:              251\n",
       "    SOUTH-NORTH_GRID_DIMENSION:            251\n",
       "    BOTTOM-TOP_GRID_DIMENSION:             227\n",
       "    ...                                    ...\n",
       "    config_aerosol:                        NA\n",
       "    config_forecast_time:                  15.0 h\n",
       "    config_boundary_method:                Periodic\n",
       "    config_microphysics:                   Thompson (mp_physics=8)\n",
       "    config_nickname:                       runlas20190404v1addhm\n",
       "    simulation_origin_host:                cumulus-login2.ccs.ornl.gov"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Define path to the lasso simulation data\n",
    "path_shcu_root = \"/data/project/ARM_Summer_School_2024_Data/lasso_tutorial/ShCu/untar\"  # on Jupyter\n",
    "\n",
    "#Define LASSO SGP case date and simulation of interest\n",
    "case_date = datetime(2019, 4, 4) #Options[April 4, 2019; May 6, 2019]\n",
    "sim_id = 4\n",
    "\n",
    "#Load in LASSO wrfstat files. These provide 10-minute averages for various metorology variables and diagnostics\n",
    "ds_stat = xr.open_dataset(f\"{path_shcu_root}/{case_date:%Y%m%d}/sim{sim_id:04d}/raw_model/wrfstat_d01_{case_date:%Y-%m-%d_12:00:00}.nc\")\n",
    "#ds_stat\n",
    "\n",
    "#Load in LASSO-ShCu wrfout data, which is raw simulation output from the Weather Research and Forecasting (WRF) model run in an idealized LES mode.\n",
    "#Post process using xwrf package\n",
    "ds = xr.open_mfdataset(f\"{path_shcu_root}/{case_date:%Y%m%d}/sim{sim_id:04d}/raw_model/wrfout_d01_*.nc\", combine=\"nested\", concat_dim=\"Time\").xwrf.postprocess()\n",
    "\n",
    "# By default, xarray does not interpret the wrfout/wrfstat time information in a way that attaches \n",
    "# it to each variable. Here is a trick to map the time held in XTIME with the Time coordinate \n",
    "# associated with each variable.\n",
    "ds_stat[\"Time\"] = ds_stat[\"XTIME\"]\n",
    "ds[\"Time\"] = ds[\"XTIME\"]\n",
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f29b1d67-af48-4f31-bd80-f1e95275e4c8",
   "metadata": {},
   "source": [
    "### Moisture convergence requires U, V, and moisture Q. We load these in below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "276b1ab9-d405-4b9b-9fc8-e8a3245399fa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(250, 250)"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Load in u, v, and q data\n",
    "U10 = ds[\"U10\"]\n",
    "V10 = ds[\"V10\"]\n",
    "QVAPOR = ds[\"QVAPOR\"].sel(z=10, method='nearest').sel(Time=f\"{case_date:%Y-%m-%d} {hour_to_plot}:00\")\n",
    "\n",
    "#U and V have staggered x and y dimensions. The following unstaggers them to align with QVAPOR \n",
    "U = ds.U.interp(x_stag=ds.x)\n",
    "V = ds.V.interp(y_stag=ds.y)\n",
    "\n",
    "QVAPOR.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "af82c337-bb8a-464e-9948-4c65a071f524",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7fe8be7e3050>"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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5n7jgggvwkY98BK7r4uMf/zh+/OMfA1BzAWNsSaZvEtHcn3aFYYhXv/rVeNnLXoZzzjnnUdv1m5h3PvrRj+L+++8/4MzEzA69Zc7UPuwjH/kIbr75Znz5y1/GJZdcgle/+tX41a9+9YQtbBdddBH+4A/+AJdddhnm5ubwyle+8lE/7zjOAfP00jZs2LBfsP3+xisAwNatW3HmmWfCNE38z//8z5IdXr1ex69+9asl3+t2u/B9f587wsey4eFhXHfddbjwwgtxyimn0HU++tGP4qKLLqL4iS1btmDVqlWp7954440444wz9rtdt9xyCz75yU/ia1/7GjzPIzoojmOEYYhWq4V8Po9cLoezzjortZO/8MILcfXVV6NerwPY9y55z549qT6QO9ETTzwRrVYLAOia7XYbuVwOpVLpgPvs8dhnPvMZANgnxfdIVq/XH/E+AbXbf6w+0TQN1Wr1SXOtJ8L2Hvu2bT/qcTkOdu/eDQB46lOfus/zPtb7a9s2jjvuuP1q44FQ2t/97nfxwhe+EGeffTa+8IUvLHEa9vd5HYidddZZ+NznPoe3v/3tWL16NQA+z/31X/813vOe99Bc8PnPf35JnJKcC/e3XVdddRUefPBB/Md//Ae9mxIt9DwPrVYLpVIJhmEsCUH43Oc+h1e+8pWo1+vwPA+9Xg+FQmHJ9U444QQA3HF+3/veh7/5m7+Bbdt0PRmG0Wq1kMvlDvuGKzNumTO1l91111143/vehwsuuAAve9nLsHLlSpx22mn4y7/8S3z0ox99Qq552mmnYd26dfjABz6As88+GytWrHhCrgNwVGvr1q2P+blLLrnkEXWIkrZ161acccYZYIzhpptuwvLly5d85uijj8aXv/xlzMzMpOKTpJ5XUjPlQOypT30q7rrrLmzZsgXdbhdHHnkkbr31VgDAM57xDAD73oHLnfb+tuuuu+4CYwwveMELlrRh+/btqNVq+Lu/+zu85S1vwT//8z+j0+nQ34eHh1Pnuv3225fA9bfffnuqD+68807ceeeduPbaa5dcb/Xq1Tj22GP36QT+ps33ffzbv/0bTjjhhP1eeAHer1/60pcQhmFq5793v65evRr5fH6fum6333471qxZs0807HBd68lkclx95StfwcqVKw/4+/vaZDySyc3HY9l3v/tdPP/5z8fpp5+Or371q+QAJu3oo49+xGcAPP654MILL8TLX/5y3H///bAsC2vWrMGHPvQhaJqGpz/96QCA5z73uY+Ixu1vu+644w4sLCzgyCOPXPLZv/qrv8Jf/dVf4Ze//CWOO+64JdeS/S1jpW6//XacfPLJ9PeZmRnMz8/TtR588EH0+328+c1vxpvf/OYl16vVanjzm9+Mq6666lH7JrNDY5kzlbAwDHHhhRdieHgYf//3fw8AOOWUU/C2t70NH/3oR/GiF73oCaP73vve9+IrX/kKLr744ifk/NJ+kzTftm3bcMYZZyCKItx0002POKk/73nPw3vf+158/vOfx1/8xV/Q8auvvhr5fB7nnnvu/t/APkyKlTLG8Ld/+7dYtmwZZXfZtv2IKN7+tuvcc8/dJ23y//7f/8OqVavwoQ99iLLcHokSmZycxEknnYRrrrkG73jHO2i3/5Of/AT33nsv3vKWt9Bn93Wtq6++Gp///OfxjW98I5W19ETaf/3Xf2F+fv6A4+de8IIX4F/+5V/w1a9+FS972cvo+Oc//3ksW7aMFhDTNPHc5z4XX/va13DFFVcQ2rZt2zbceOONeOtb3/qkutaTyc455xyYpokHHnhgn7Fsj2W/aZrv+uuvx/Of/3z8wR/8Ab7xjW/sMyAc4M/rDW94A37605/SswnDENdccw1OPvnkAw4vSJppmkSHLiws4FOf+hSe97zn0bxUr9cJoXy87XrXu961hDmYmZnBH//xH+PP/uzP8LKXvYzmgkead84991w4joOrr7465UxdffXV0DQNz3/+8wEAxx133D7ngre85S1YWFjA5z73uX1uXjM7THZYBBmepPaBD3yAAWDf+c53Usf7/T5bt24dW7t2Lev1eku+93h1ph5LB2Rf2iqPJtopBRoPhe3evZsdccQRLJfLsWuuuWZJO7Zv3576vBTHvPLKK9lNN93E3vOe9+xTHLPb7bJrr72WXXvtteztb387A8AuvfRSdu2117Jvf/vbqc++5z3vYV/60pfYTTfdxP71X/+VnXHGGSyfz7Mbbrhhv+9jf9u1LztQnakbb7yRmabJXvCCF7Dvfe977Atf+AJbsWLFo4p2SnusMbY/7fn2t7/Nrr32WvbZz36WAWAveclLqK+73e6Sz5977rksn88/or4aY4z94R/+ITMMY8nxs88+m9VqNfapT32K3XDDDey1r30tA8Cuueaa1OfuvvtuViwW2TOe8Qz27W9/m33ta19jmzZt2qeQ5qG81umnn/6IukaPZI+m/3P66aez008/nf7/SHPAjTfeyACwa6+9NnX8c5/7HAPAfvazn9Gxyy+/nJmmyV7/+tezr3/96+ymm25i//7v/87e/va3k07eobAf/vCHLJ/Ps+npaXbDDTcsmQuSul6e57GNGzeyFStWsC984Qvse9/7HnvBC16wT3HMLVu20Pg899xzqV+uvfbaVD/s3r2bvfOd72T/+Z//yW644Qb2yU9+kk1PT7MjjjiC7dy5c7/u4UDatbc9Hl0nKdr5nve8h910003syiuvZLlc7lFFO6U9Xp2p97///cwwjNT93HTTTcwwjCXiqoZhsD/8wz/c7/vJLBPtJPvVr37FLMt6xMF88803M13X2Vvf+tYlfzvUzhSAR/yXFIR8Ik1O+o/0b29BSN/32SWXXMKmpqaYbdts7dq17B/+4R+WnFf2zb7+rVy5MvXZ/+//+//ofMPDw+xFL3oRu+222w7oPva3XfuyA3WmGGPs+uuvZ6eccgpzHIcNDQ2xCy64gO3evfsxv/ebcKZWrlz5iH370EMPpT67bds2pus6u+CCCx61XY/kdHQ6HfamN72JjY+PM9u22THHHMO+9KUv7fMcP//5z9lZZ53FCoUCK5fL7PnPfz7bvHnzYb3WCSecwMbHxx/13vfVvkPpTDHG2De+8Q125plnsnK5zHK5HFu5ciV78YtfzL7//e8fUNsPxuTYfKR/e4vuzszMsAsuuIANDQ0xx3HYKaecwr73ve8tOa+85339u/DCC+lzjUaDPetZz2IjIyPMsiw2NTXF3vjGNz7qu7Iv29927W2PVyTz7//+79natWuZbdtsamqKXXLJJanKG49kj9eZks8p+TzkeNt7vgaQGq+ZPbZpjD1OEZHMMssss99B63Q6GBoawlVXXfWE0+6ZZZbZ74ZlOlOZZZZZZgn73//9X0xOTuK1r33t4W5KZpll9ltiGTKVWWaZZZZZZplldhCWIVOZZZZZZplllllmB2GZM5VZZplllllmmWV2EJY5U5lllllmmWWW2WG1nTt34hWveAXq9ToKhQKOO+44EmH+bbBMtDOzzDLLLLPMMjts1mw2cdppp+HMM8/Ed77zHYyOjuKBBx44LCWeHq9lAeiHyeI4xsMPP4xSqXRYCqxmlllmmWX222OMMXQ6HSxbtuyAaqceqHmeB9/3D/o8tm3vd4mmd73rXfjRj36EH/7whwd93cNlmTN1mGzHjh1PaA2+zDLLLLPMfvds+/btT1gZGc/zUM8X0UN00OcaHx/Hr3/965RDlcvl9llqaMOGDTjnnHOwY8cO/OAHP8Dk5CTe8IY3/FbJk2TO1GGyhYUFVKtVbL7mCtTXHwsAYFYBECiVFgVggy4/3u8BAOJBF3FnAQAQtebgNVoAAL/dh2FzxtYq8irkpusg7PIK8wsPPYzZX+8AALR3LgIAiiMFTJ/DC2oOnXYaNFNUpb+fF/bcc/cWDPaIaugtD52HefHezo5FeFEMALB13taIMfQjPoxqroUVT+Mv+thJvE6W4djo7ebV1/tzLcRhuKQ/Yp8f8xY89Bv8fnOlHOobeB06d2KYPqvLey2VALFD00StOy1fgiaOsTiGXqrw/hgaAzSD+g4A4vYexF3Rn90Ogk6f+gsA2lvn4Y6XAQCjJxwFa5gXQ9ZMXg2eBR5YzPtCzxWg5QvieIB4YR4AEHZ4H2q6BsPl9eC0XAGa7Yj2iu/0e4g7vI9YFEGzbHGcj4Gg2wMT/W44NuKA95ff6sAs8KrxznLeV8bQmOrXzgLixRY/l++J9tswhid4Hy47AswUk1t/AeEcv/fg4YcAALO33outN/HfFxo9jK+uAQCmzjwKAFA7ei20fIn6I5jnfevN82taxQKcZRN034j4jjfu9xB7PfGcGPWRLvs2jhD2eQ1JOQ4jP4Tp8L8bORvRgJ+rNy+eoad20wtb9mDXL2f4s9E0HPEsXmR2/BQ+5q1qFRDXQhgg6nZEf/L3Iw5DGGLS120Tna38XDt+uBmLc7zdoxv5mJw46Ui4K0RNOV2nfo4GAT9XoMa7Xa2oNt7PC46zKEbt6LW8XSvWQhfjhFkFxE5R/M6fsRb50PtiTPldxGJ8xH3e7mh+F/rbd9A95IbE+C/xcRx22pj75X0AgJ0/3YZBm/fZyFF1TJzMi/e6kyPieRiIw0D0gQPdFW0RYz5sNtAX77Xf6SEQ8418PyurlqGwbiM/5lYQ93kfR615+LO7AQDtB8W7tm0W/Qb/fhzFCHr8urJ9hmVg7Gjerskzj4ez9lhx3hJi8eziRT4OWBhAs/mz03JqIQ938nHc+PW9CMVYcceHYFf4fRkOf+cM24bf5v3ZuG0zIvH8lp99KuwTz+bXKgxBdDL0QLxXXgfotfg9tnm/xN1FsIEY54EPiP6MBPITeT4iUSvVb/dpboz9EP4i/56cx7WxITz1776IVquFSkWNo9+ktdttVCoVXIBJ2AcRUu0jxr9i55Ljl1xyCS699NIlx6XD9ba3vQ0veclLcMstt1Dh+AsuuOBxt+NQWhYzdZhMUnulQh7logsAYLabdqbEXM+4D4DYZIhj8RL6DqwunzB8PyJnys7zY2Y+h1AsUnHORtfkf4+E0+GaJkpi8ii7BXKm5PeDnA3L5g0wrRCxIb6vG9AZb2PSmdKET17QDRTF98riXIZj00Rl5izE+lJaM4JG19JFWx3LRCnHv1fMq90MOVMFZ6kzVcinnSlXOJdFF9CFMxWKBSjqI2YDcQ8BgjCm/gKA2DJT92K5YkGTC76vKWfKyaedqYBPDmE4EO3TYRSEA+XklzpTOkMc8WMpZ0rjO8QgjtLOlMnvZeD5sETfOMKpMsQ9A0Ac+4hjPhkz8bZrpk2fsUoumCkWHCNE2OPHA9HWfs6CK/o20A244tnQ2Ck40MR1ma8hEG2xHDWenMR9I+TnirUYsR6L+42pj1LOlLgHT5wr0nWYcsFzbETiXTHE84oS+8LIMlEQz1vXtCVj0io4gBjzCA1ETCze5AAZMB3lTEFcwzVNMNEfRUv2RQ5FcY/QdernSIxD+awAwC6oxT0W98KiGGVx3Cq60F01H8SOcKxsMfZCH7op+msAxHJuEH0Z9RyY4h7jwIAj54OCGo9ejveFa5gwjYjuRT5TeS/cmRJ9aDvQ5XOWzpSXo+fh+yGCMBKfVX1dEONML7qIdf73yM/DF+1i9K5Z0E3hSGgxAoM/S9k+w0jPK47YNOqui1i8IzHjcyMLTfV+JZ0pcV9+zkYoxorr2Mgl5ikAMHI5+IEYD7ZF46xccGCXuOMVC4cXUQg94A9csxigC2cpEo4hIjBDjPNAp/EfGWLu1DSEYjr0/QhxIMaMpsP3+bmCIBL3wtt3KMJCbOiwtYOgEsWruH37dpTLZTr8SAWw4zjGiSeeiMsvvxwAcPzxx+POO+/EP/7jP2bOVGb7Z7f93ZcwvuI7AICh9VMYOolXGreP2EiLdthpAQDi1izYQLykQUiLOwDaFQbdfuIY/70/20J7B9+9FUf5RH3M686C+7Rz+Qd1E9Ec380aYvdZnBxOnCfNn/fF4rcQLAU17X6I3jzfUfUbfKdouQ6hBqaTg17mbdAtE5ohHB9xTstdQHGC77qGjppGYd2G1Pl7996Fxh0PAgDyozXUTngK/94U39kjjhDseID329xO6AsN+q5RGwUANdG6ZehiwYVuoD/bBAAMWryvSstrGDuJX9+sj4OJXWXc5ciA3GUCQBxHah9n2tDLvDq9Xazya+WUA6W7JXLs5LmYbtB3EEeEbjAxBgzHRtDuUftkfwVdDwOBpkhzAOiOcqi0XF5ct0z9YNTHxX2b0EJxLQBGhbdBOqfVZge5W7YDAPY83MEysQiUpjj6pVdHVVu7bfgd7qj2Zlu8rc1Fcn7tkVEgVvQBXYucU4+QuLDnETIlnWPLdaALB4bFMaELhqWca7nQ52tdlMb5OIv8GIM2P9eeezgaZDq7qB25ahG2GJPJd0oai2Pkqvy9KK8oob2DP7P5ezj6UJ6aQ36UI3a6ZRK6lXwX5ULNQh9hTyANYuyXpsZgTq7m3y9VEcv3vTEDo1TlJyjx95GZNrRIjMN+N4E28j7UCyVyptoze9AXz8EqF6ivdIt/tjCs7jXyIwyavN0SmTLqE9DF84q7bUTiXdKkk2qZKIzzZ2gWHHgNgWTv4e99877t9LxyK9fQmEcc0TOlTZajlqJB20fYD0V7+XfMvPp75PmJ98Om/ormOBISDQYwy3wO0auj0MT9SsSvNDWGzjaBjD20CwAfC0UxpitrVlK7TTeP8ih/Bvb0es4eAAATDm04ILRVY7H0IcCEM8Z6bUIP9bwLLc/HmZYXiJ+cS8DRKLmBYJEa33Lubt6xG4fKDE2DcRBOmwENYEC5XE45U49kExMT2LAhPdevX78eX/3qVx93Gw61Zc7UYbYtd86jdz+ffObv3YPxLfzFXnl+G/ba4wGohc3btRueWOidakntpCwLsSUmn8TOXTozvfkexo/jE8WRLzuLf//4M8AsAYUHA2hi8ZULXK67iN4uvliE/RCRzydVM2+iInZ1O8WEt8ePCKUayZkoDPNzyQUoPzaC4pFiErGd9OK7wO9ncaeg3oKQFur8ypU0+cRiIvdaHdr5Vjeug3Uk7yOIXVQ8tw2sxyeo/myTFpPS/B64m47j9ygcCaNSB3PE+XsdckidOp+Iq6snYdYE5WFa5AjIBTtY7NKCmasOYBf4ZK27JVpwmPyO16PFKO53aWKXn9NyDjkSLOGkEeKWCDgNuh5B/6HnI/IG4jhvi9NYQF7cg+HY5MxIB0uznQQy5qpz6wYtPJICs9w8DJu3oR8xNB/k/SmflzUyBjbg1x3sWaD+DkVbzHpFORKBWgR1t0zPQRdtiRYaiCRt5YfUz/L7umEgEouUfFYA4NT5ZG06OeoDy83RONQMDbbL7ydo8/P3Z5vkYBm2AXe8CgBwJ5RzIE03DHK2qqsnqA9mt4j39u4ZlFdxKjNXLdF753cEXV0tIlcr0flkf7vCEbGXHwF9ZIr3kWEA0plaaICJxdYQmygt76ox5XuA6CN5DKYNSyxednkB3V18zMkNAu8P4cRNFOm97jX65AjLcaLnXeUIuGVoYjNCm4pOE1FH0XxJOhPgCKvcRMnnDnDHLOloAtwxMyxd9LdGzpN8brZrUb/v/Nl3Mbzu5wCAqWcei8JyTrFKFMoqVWGMCMq7UgcEjc3E3BZ3WpgVVOfs7bsRdPn95O/lY3qitYi8GFORN1Djr1JHmBOooS6WTsMGi/L0u+bz+5JzUNzvQi9xR9scmSQkXTqAiCNovUTfSPq+00Usno3sF29hgENlugYYBwGA6QChU/tjp512Gu69997Usfvuuw8rV658/I04xJbpTGWWWWaZZZZZZofN3vrWt+InP/kJLr/8cmzevBlf/OIX8alPfeq3qtB4hkwdZhuu5zF1tEBi6i7txhcf2oaK2F3J3UzQ7aN1H6dc8qM1VFeL3ZdjI45EvIJhYG9zx1wMrecevn0ED8BlVg4Q30E4UGiR3HUGIeJYUm8W3DGBLBk6ShMccVq1gu+2DctArsb/PnzMGjgrJWXBd2SaaaWDfQVCEw3U7lSiWPInACxu3gxN55SepLIiz8foSUfzzx51AsHtcWuW/705BybuKz9aIwRjzz1bCNUobeLBq+b4FN13MLcbtqBCqut5+yVKJzoWuvg/3Ze1C0GX06OdbbthCUQil0ANJbWmF0oKDbIsilGTz1YHKNiXhQE9B3kvcRBS+yPPp519HIQwRGyPpLvCrocFgYokj8u+LXi9FEIk2wUkEA5xfcOxiQ4yNGBxwHfOvRn+DN3duxKUY5/oEUn/FEZrhDwhjula5tgUjGGOKLBA0Hm9jqI/E6iGRHIiKFQQAD0viSTqpkV9pNsmKiv5cbtUIIRPIjRe00Pg8XsJ5/voPMzHV2FY3NdoCZakoxOo4KDVIepJ7twb9zRQqN8DgFP1El2Q/WKXCshNTok+iOC3ttI9AoBj2UTnaixG7Al0bqFB/UGxeXmXxgx0QyGbkkIzDEJo7JJL1J18DyIvgCGC+GW8EwD0mx68priuTAwIfHoHdLdEY1HSaUGrRchXkEBX5POyyy5sMeY006L3vjfToPdZJp7ohk6ImemYhEgRyl1z6R4Gtwyw8xaO4OfKOUyPcfQ4t/Ek3u7qBJghYrHiUNFwAjXS8i4hhYXhDnroiT7iY6e1eQaxrxBQidBXGjNAlSfXaFYCh0jEFkmUViJPXmMB8u2KnQJR7jTfDjwaJ0mL/ZCQ016DnzMKln7uibLfCM13APbUpz4VX//61/Hud78bH/jAB7Bq1SpcddVVePnLX/6423CoLXOmDrMZlkHxAX7Ho4nab/cQNTnsTLFTno/OLj4JDdoDmgxz1SJN4HZJLAC2SUHp7ngdpdXcmaJMoSiCFikInskJ1FM0i13iE1l5ahQAd1a8pofKSu4gHHnRy/g5Nz0DENSfsThH2SsUIwEoigw8LoS3pQxrKg2OMt8jSm+wayfFNnjCUfGaXfREbNPo7DxRd7qk2EpVWrCN0EdVLlKGThQU7vg1AMDZtYUWentiOfIbRkW7dWqLpFGg68oZojgrHa5wivKdJrWxdd92WrTlglxbuwLOKh7XZVTG6VwpJ1ZfOilTZpjn02Lit7sqc8rQU+MA4AuAP8f7KExkuMl+62zfjfI0/92dmkw7vUkKCUDQ6YGJTM2KpaNaFXFfMnYpimGJcZIbV/cln2F/bg96u3aL9pWQW8WzAPXxVWDyfkWWFwt86gPDtsiZkveQyoorFciJkgs+66t+MZwciiL2J0W9CZov8iO6L8M2oMmAYJ8/b6/Vo+uyiCnHq6/aUChzJ7bXHmDHT0QWZDfAyLH8Xatv5BmE9tiE6pd2gxwMcrTLQ4CgjRiLVQxZHCEQNLhNz6VMf9ccF9pedDELffV3Q6cNkew76UjJe5QOhO1aKIyKzD+xiTOXrYImQgHAYkDMDZpot12vw5Tv5Z4F1fdibNiTI2pDohvkoPvtHjlhsl2RH8Gw+bOvrqygMDGUOpff6SLs8+87NYc2d8XJYUVNy40AiymRh+kmNBnfJIL49XKdYkK9xsISSjFXLVIoQeRHaD7AMzkrd/wcpRHuTEUlQXmatgoxsPIwKvy4uZxvyIr1ceovTTdUjKR4v+IwQCQct9DzU++rNE2EUBjWoSOSjIOk+ZZu6R/bzj//fJx//vmP/6KH2TKaL7PMMssss8wyy+wgLEOmDrM51RysooLbF2e74reHURAZQqbLd7VeY4ECRo2aQ8iRbpm0o5FQuW5aRDXFcYzOA5xakLthc2KaqIM4kXEis1AMx6Yg5l4UpyDmnT/bJX5eBQA44qz/wvLzzuTXn5gm5Im0cVgM5omMszBQWW3Fqgrk7EstIY8QLatchjvOd66SOvDbfTz8M04zNO6dx+rzeLurJ53C72t4HBCxviwIKP29AqC3e16cQ2TFJTLNDGsnDOd+fl2R0WU4NqdVwFEA2XeQCJVpwxxbQfdtNGbEc7oFvQZvl8ypY1FM9ItmO0TjRYIOYN22ova8LlEtMoMv6PYT2XyL8AWiYDkmHLn5l1lzRoGCn/12n1AX2Yf9+Q768xzxqDTaqK7l92BWhXYOVJZhPzHmKpZBFG9tLaetChuPg17g/cJCnxCp7sMcyZy5RQWVrnzWiTAn1/D7zleg9zmqEe8j8N5wbGgJKpP3gQdLvAt22aXkAGmDZovQrOLkMNyp5aLvI0Kk9mWmY8IuyoB7mdShMk0jP0QsqJjY15Ar20vOESzytnd2LaK6RqJjIvA+jhHt3sb7RQTuA0BprUAsDENlgVl5GEMiML+0HUzQYf05TjXZgwEMIaehA2A0plRWqjTN0FWmo6uoXKLLFgZY9lTeR8v/6BzYqzl9Lt9JLQ4BkTnIfI/mBqIWC2Wic/12j8ZUUsJDEwkemmUnkhocQs0Xd/HvdGe7KNT5eze0dhlcgRxJOrD/0AxlteXKOUyczMdRbdNa6FWBEgkaUotDMIEWMcsGAolSCZov5xCCn+wXmRCQqxZpPjXzFpoP8me27fu/wJoxnmhgH/sMAEDk1glVhGGSlIU+zfsSLIYu6MW4uVu94yKhIOx6lN0ZB2GK8pPvrUTOnMq+ZQWeCDvUNN/vgmXO1GE2q2Alslh0mpRn5+dhODzjRNIVfqeH2hFCNPHsk2EdwQXx4m4HUUOkegsHSbMs5Kr8xe7PtsiBkItdXKrS5Bi3G7R4UrxHHCMUWWKR58MSqctOzUEs6BEpmdCd7VA8hDW5mrJnVLyH+j32PcRiYWFxDF1IB0j6EbqhaIq8i9yQiNMQbc3VXDg14Vw2Pey5mzuJJDRoWSrlPu/CSFBn0rGJPE7JdLbtxp7N3MHac3+TYH6Z+VheNU6ZYk69AkPSHHKBMC0VA2FaQMj7w3IdVFbxCV7GteXXboRR5xMxDAtMCg3K57HQoJip2A8ps0o+t7DrIeiJ2Ak/okyf2NJJVFDGn2iGTo52HASp4wBg2CbFx8zfsR1dEf9UWT0JR4wZ2d9eo00UV65kIyeoLdk+pzGjqFCo2B5JwY0ev1rFT510FtEjiAJogaAypRMVRyp70dBT8g/yXiy3CgCwa1W6ZjC/W3yuj6ENRwAQNIvUQ5rZRu0y84ISreSIstMMjagUec0IISCb5Uf7jFeRi51uaPR7HDFy3CTtW8grR9wuJ2LZRHYcivV03I2go4zaCPTd/L32hXMeeT7sMh9nNtRYlDFXKekJx0ZhfEhcl4+HfqONzo4WAGBxtkcLdfe+e8jZlmN6n9S2OA7wTYGUUimMDxG1Lc+/8MBO5MekzMI4PVsjEasVirFluRYqK/nc5tTLSstKPPtcOY/xpyihShmz15u5md796tE8td62bGiyPyOHO4WAkjMwLRK6tUsuSUUk20UOoWVCF+/Nw7fOwHS+CwA4QmQ8mkc+BcwSDpmmq2uIa2p+H0zQ2LHvqT5OXFNS5pqu4sY0Q4dTE+NAOMq+/btN8/22W0bzZZZZZplllllmmR2EZcjUYTanlqNyGv22Rxkcg/YAjXs5aiJ3aeXpCRL1tKbWki4RQj8dRAy+25cPt350jpAhSTVFgpIChP6PuIbcVfudHu0KoyCknbftWsgLZMip8t1ZZfUkLEF36eUhDn0DSscqCqEJfRbTypEwXfjwQ/D3cAhdlu6QwZryvojyE9SbblkUNNt4eJGCiC33DgDAcNeDMzXNrzUySfer513EgrKTGkKmmyc0yh0toLyCX7u2nlNYxckR2qGGXY9oNrl7BEDBoyyO1Wc9H65ABHKjfNesuyV6NgASQoKSIgugU3ZjT2WwCboh6PUJYcqV88gPl6g/KItvL6oX4IHY8lwSddQMnYKNuzMtzN7OKbnGPQ2MisxSEm60TFSWC7FP2yCtn/aOWwAAK89oYOL0p/K/j0wSKih/5o8tQKvyc8a5IqFR2iAhOCnHpu0QsqL1uzQmpY6WbplEz0DXETaVNhkAlNatJfFWzXYQyjGu6/TMJVrLohh+W9AvUUzogxxP8rkCoPdzb5OfDfshIqGezzWSOMJBAfJjU/SdXBwhaPLgf4nmGvUWIAO9dZMy0cyRSTgCIbRH+GdZv0sIJnRdJQwQuhfTO6PbDixXZsvJLMkYukA6uru7hM5V18wiP8LHLNHRjkuUPWwnjU4BQOgTHR32PMoqlWhXe1sDdplT50ObQJpxdtml51iaSOtNAZzak2h8/ZjVdH4ZtN7esgtzd/Jnv+X+PVgQqOHxR98GANh4wdNRPOE0ft/Dy3mQOEDon2ba1BanXlaB84J6jIKQxlQcxXQ/sR/h/ut4dnHoXQsAWP3iBuw1x/BruWWFMAp6NFpo0FwbLzQQCnSZsjMtk8ak6eQoUYJFMSJfona8/QX90FV+y2i+A7fMmTrMZjoWNJmN7oVEoZl5k17i0gq+GNVPOQnmMp4hhDhSC0/eBWTciadiQzQRy6IVynRcxugk65hpuq7ibUT2WfIzfrtLMTqGbSBf59C+jLUpbTqWFrHYKYEZwqETZUqYpUMTUDgzbJgynmHgIWjdDUCJQJqOTZOLbpvkQEgnTzN0oppsXaN2SbrOb/dRnOTUyNCmVbAmpvm1wmAJlWkVHAyt5en5y04to7iK3w/RL7qhsm46TURdHr8hncw4iig2adBaTMU79EU2nbxWxXGVw2sn1NALSsxRtk8zDNgyRkd8X1IBsg/2ZXIx0C0TGsUWFcjJku3m6soDcQ+M1KerKysYPobHojgTY+KzEUpTvG+b920j51N+J1ctIWwv0GeXOPWNXWBbuWwAjzsT2Wfm0rgjLZdwpnSDFhNpdtml+MHY65Fivewbq99FOMMpZCTOr5dqkFrfUh3cch2SDZB9sbdRTKEfUh8Oophoz36T92e3H8IXDteIa6EiJUsEravpBoniYmyK+mvx/s0AAHfQhz3N61jqQxNE87F8GdayaQBAJBb/qLGLRD01w0hnzALcwdr7GBKxlIauxCBtA1WRmVuZniDHiWjsvJoLmO8pDUbZL4lnsLhzLiWkCnAnU77X7ngdzqTIss0XSJhXKrN7jTZi4Tg69TIcUQSelPzndqqNRdeHLeJMx0cKgKiV2NrK+3X3z++hTYydd6G5tSV9JMenXXaXVGEAVOxS5AUUL2fmTcr2lNIMwA1YcSaPZ8uv3aiypWVsVEKlPhoMEqKy/Blbo8uov+PFFs3DYddD5Al5BjHe2CF0pjQcHG31++dKZc5UZplllllmmWWWsAyZOnDLnKnDbP1GH05VZL0ZGmUVFep5jD1lGgBQO4r/hGmrkiNxpILNbUcFeC+2AACD2TnaxZsjk4SAyCySQbNDOz3DsWEbYnckkJCw5ylNHi+gAHTDsYi+cKe5no45OqkyWlhMtcMggjCZlUdsSj0ck4IzzeFx2KK9csc2aC6msoFkpous9dafbVHAfnWqTLpcuggg7uxaJC0uv9PF6AkCharViFIrrlI7biQoJqLhkhlRsuZZqUaBuUZeanF5in40dGpj2O0j6MoSLyqzqyR2oLy/0rSrlqjtF+sGTPF3V9CfuWqf+iiJKtpll3SeCO2Jo0Ql+i70vdCtIPDgNZR4Ze2IKgBg2R8cg9yKVUgaa84ScqPbFqGC0uIEJWLEsaLuJPJWqiHuCM2ruZ2ASGbTnQJlSib7m7II5/ZQJpcp+tipl1W5jUZ3SU1CHpzNUQLN0FP13yRFJek+ByrgOFm6hs7lq/sKPZ+C/MN+CE8gUi1ZgzKKsXojR0KOfP6JcI84QtyMSBLod0n4U9MNQkK6M3vo/DVJQeuGSsYATy6R5wDSZVlg2orGljpWfhod2tvCvk/ZmbmyrYK+J8ZgTvBnLynouNtRdSgTge2yr1i3TQkS/fkOBm0+LvVEFpqioAc0d+mlKnIyO7ejkHSJ6JWOeQp/RwBETU5Bhz0vVYJGhh1Yro3lYm6Smaa6oaOzeQsAoOy4sATqJzWzks9a03UqaE195A1S6K+kczVdR1kIFcvMw8iPsOtmHmJQbSygsnaVuMea6jc59oZGYC/nY4NKKeVdEvhkXleJ/domIVLt7eKdYIdOtDOzA7fMmTrMNugMELmiOr2uUaZa9Yi6EmFcFBRXvpGe1ASUrJmWWpDEgpqkhRBHKp0/UUU9OalICkhy9l5jgRbtXC1Rvw2qFposzKs5LlF70HSVPRMIWsmwEesiQ88uUGFdM18iGF86JUHXo4UrCkIqntoVKsRe06PsFukEAEpMcdD2Ke4sWcjVqE8Q1aJqi7UQi8m6t2079YeM5zCLRVpYWKScV7lgsShWGXKOTanZQXeASFR690XGY/PurXSPTuiTmjo5HXkXTD4j20EsnLhYPFcjjmgxMRwbeUHDGbVRlTUp29VrIxJij16jTYVnwz5vS+QF1K7y8hJRLoCiiUkEtVKHm4hbk4ujpG+6Mw1y2itFV2V/JRd5Waw5DODt5JmU/s65VG1JgDtAoaec0IIoMCtpX83QlWK2ZSI/wv+eVBxP1aCTDkxiYUz9nlDqljFSkraN9hJPTFJjIxt42v6a83g1gaGNq2AtX5PqNwCpwtjJGEVdSgQIxy5o9ygjUXNcUkBHHKmCuQn6XtJxRn1C0UricwgDRSv1ewlRTKWeL23oyCGMnshFVI2xKcrSixKFg4l6Nm31LogNWX9uj+qvIKbMPEkB19dNYFjEPBluiRzCwa6dNJblM6itXYH8Gt4WSW0CUIWv+wMS0rRLDr3vlmNCF1lucu40HJtoWX/XDqLRSNzV9xQNl4h1pHfZshJOjUHhFtWVZRSX8f6Wkgph3yc6rnn3NnLwh44SFScmV8KoiLjIQZ9LRACU2cg7TMVPyozhXLVIG1iKqT2EtfmybL4Dt8yZyiyzzDLLLLPMyLgzdTA03++fZc7UYTYWMfQEXWC7NobXcbqgsnqSgsFpd9lp0S5Ld0uKRuh1UogVwFEV+nu3DU3seOSuUqIkAN+tDjyffgf4bl0XdJ5m6JTJFscxITdypxc7JTBb6t3Y0CKRNRYKeqjboFIOMGxoohYbWCLzSCAeuqETgsJ3jREdB/ju0xF1AA0nR5leUjdJbytUqPPwIiEo9kSbEAEV5KyCdSPPR2+uxfvO4btxd7xOqAuL4lQ5k70tWe6lN99DvHcG2GwHC5t3inbbsPPpPoRugMkA+UTQqiwr47cW6ZnlVqxKBcnTc5ZJBl6XdttxEBIVI0UP4ygmvbKho1YSbcviGGGLI4BGIDIDc3lCJDQjrYMDAGE/IPTQHe8jV0+HrcZeV2WdAlRKJfQGVPNM6mdpuk4olF0uLKFfNF2nwHitUCZdL6LCfC8RpNxXAdGBGj9SOwpQlJ+8d96doj6c69DvYd9HZTVPVDDzShdItk8v1VR9Q9NKow4AR5gksmTalLHqTvBn393VIGTY7HWgJUoMEbom0ZXaKCGsmmEQ2iOporjXIVo18nwaB8manUmRYElRmb+8jzI4JVLJMx75+Q3bIjqZqPeZPVSiKfYj1MXcNXEaz26zlq+h95f12qSt1pttonk3TxSQKPLo8auQX6vqEMp7iHsdOiaNxSrDrryiRFS/5UpKvJSq8ak0+MQcuVeAfpI+lOeXz0PTddRW8SxHp14hxEoickHXo+zI2I/QvJdfS2qM1dY2UyW+chOcvtTLInPSsAitgq4Twhh6Pp1XIm557dAFoGd24JY5U4fZWMQQiwwR5sQpmsEQqcpUBy2OaQFBHKt06NBX9Iqs+ea49FnmezTpBqSM3aVrASCRRzkJsTimiTxXU3ScXqrBqKl0fwCIAZUSbNiIRRafFM7TvQVSu07SgBSPAcAs8wW9aJkqVqXr0eSVpHpk1locxQSrG2LysxwT7qhYeGyDavsVJ3fAkTUBhVAoSyiR2+UWnYsckSgdJ7I3HZCknZIxNoEXknwDCZwuBjBs3hanXoY1llb9ZkGXqKCoMYOoL7MEFW2VG+X0kuaWFV1r2mpMJOghaUm6NylSKev5WW4+lUE0EAuezCa0agZRx1bRTdX/49ahc5nlMjl5MhMs7rZJmDRs7aH70QydVK6lM9besgvtbfyzpeU1jJ7AaZ/cai7GaNQnVNxLMCDnU9JSRujDlMW5O030RU3A5Dgnp90yKbNPt0waZ/RsdZ2e56Cl4gv1hDK6jPcJ798MV7TFXLaKqD6igxOq/nqxqmLF5HPxBiq7stNMSRDoiTp5AI/7kXGRUXNuSa03uVkCVOUEQNH4VrmA0mRN9HsHCyIDrvPwInJl7uxPnsIpqsrqSRh2QlxSbgCkjEqnS/GJ7mgBI8fzjF6Z2asXyqpdhgFTjKMSlBK8rPgQB6FyQkNf1QqVzmIis1PTddglEQ+at5XMgnACc+PjKoY0kYVLfZp3U++IDCuQG0YeM8W/XxitpfqRnFMZj2eZlO2n2yrDc/ft/P4Wti5g1TncuawceZzaBMkKCHtm6F6jhQbCRVXQneZfEadoho+8mftNW0bzHbhlzlRmmWWWWWaZZUaWZfMduGXO1GG2OIrhD0SwZNfHzK94QHTuR9ux6iwevCn1nCw3D4NqO/Vp92XUJwgtIph49zYSNQRU0KvcgUeNBYLwk+gEZUu1e1SCwnBLMMQOWXdcQlPCuZ3iWEtRfvkK4pwIwjVkzSobWq/Fr7vQoEBu5ntq5xoo/kWiB7mhCnJDqoQEwKusy132oNWhnaLUmwJ4UDW/rIG+KMMxe+s9WFbkqIotyvBoCR2pQatDQasSfbHLLtVBA3qp3TH/vp7SqJG/W45JKFAsfvb7IWXnmM5DKEyokjfy/mXmUtTvLQmAttw8ZSOmEg5CX9Fc4meyL+MgpP50x/i9DNo+lfywS7tpRx9HESFOUUIA1BwSSGSpivyo0L6RNIihk8CiuWwV9Kqolydrunk9ald/tkkokabrFMQra1BaroPZX3LtpZ0/2UZ07wpRskQzbUWnxRGNQ1U/cYQQhajpwmrLzMAWYrHLLwgUw64W1fdsh9A3SccFjXnSCvPbPUIvDMuk/kxm+8n+qOoGvSuEDIcBoaHm6KRCjwU64iw0iBYKOj16R83qEGV9QYjeskEXcXuPuMdZMEnHCqpId0uKEgt9ReuXxNgsFagGnddYQK7G0buwHxLKNH83R0idegXVI7ngqFEfJ3qSPfwQ9Yuk6crLS7Cq4h6FSCnLudAHAllaaCjK3rToXZGoS360qhJEoojobWm6babqDMrnXJ4eh7tWBNEnAsyJJgzClL4aAEIvAYFQiv5OZofKY3IO5H3k03shkUTN0GFIpLLdR2+et3txkX9uzLWQq5WoXXLOlMbCgBDWYLFLlKNumSnNPwCw95oTMntyWeZMHWZjjKEzwxeYnf0Q2/t8gZjuB5iUCs1iEQ/1AUyZXWM7Kr12eDmYKLApM+X0XhvRThGX0OzQiykXAl7IVcQoRIrCUmJ1ProiNiL0fORnhaim6yioW1Imbhm6oHJ0t6zigEQdNWY6YDm5IHZoQmFelyZ7SWuFXY/oNd0wyMmTkHeyZmDQ9WgR6u4W8UJ+BHeM36s7XsegzbPHdvxkO03gk6J9eqlKNEK/0UYoJrKioJ/MckWJP/Z7VK+OeWJSdnLUVs1QzkGu4lMtN/kz7oe08Oy6dQa69SsAwHJxX7pbJidTt0xy4nJSOiHhQMXdjqJBAp8cAIqf8VUfGo6tCmYLZW672aW4skGrowQdLTPlRMnvk0NpWUqwNCF86iQyC5msyzjoUZsG83zx787soT4ujNdpkZHjyGt1qL/a2zvY+gBfEDs7+DPecOEzkdt4Ej+/6UKTzgo9gzS5kKTstEQsFMDlQohyMS3qz1A69wmaWzN0RB0Rm9dYoEVdSyyicmOSqxZRkDSebF8QQKsJGjFXoELC8j0xRyZhin71213kZZZjbVRRgkI5PlpokKOgmVbqHvg1A3JE4p5Ky5fn0QslmvTNwgzFCfYaPTzU4N+T2XiGbcIUlJ05ukKpesvamhEjiYD6xlUwx5XSOwBofl9RvI0ZsB6fu3q75zEQMY5SFsadWq6qASQqMrBEfGOydp7cABTWH0OOqlSUj1uzJIzqt7s0puX7qxm6qriQqAEpqTuz7FLYg2bo5CgHPQ+xyIpMOtLSBu0BveNFEZdWXjkEqyyqOpi2msfkOOu2qSj4oLVIfzfzNlVRkPPKQlvR1U+06QdJ8/0+1qnLnKnMMssss8wyy4wso/kO3DJn6jBb2I9g5fjuccrU8ZSn8hIU6//k6citWgcACHY+AADo7WoQRWBOTEMv8Z0L041ECRcRrDg2BUuU1vAaC+iJsg8yeNtv92g3Dagdu6S4dNvEwn0cQVrcMY+hRL26vaFu01mEVW7x7zkF6CJ7RgrX6eUhaGL3qJWqMMSOPdzVRSComLAvMv8MgzKPoiBIwenSaKfY9UiAUGpPaYZGInsAz5AEuD7V7O28XSPHbeX3utJStbKiGAVBf7jLRBC141KAb9j1qPyItCSFphk61SazXBu2oPd8AffHviY39ug3Pez+NadS7PK9AIDRE9YRUqHZjtqZp1AnGWAeU3BzMmMrVZNPBA5bieBZQ+ym7XKcQKMs2l2zbp/QHVtQLqaTI/0hNlBCrlQnsFZU5UdMi5AEiTjGnSa8ltS8WqDnVRjnAe0AqNZc0O4RPeqOFeCIxIxcJUefk+ibZkdKwFLSNqalAvMTaJRTL1PdOUnBGfVxQkIAHiANAIbPn4Ed+nSPQdej3wftAViURnB0Qyfk1y4rTTZZHoULNy7dq6c0xiQiHISKVi0PLaHBNdMicc2ksQSlSGNn4KG7g495SWE59TLcqeWijwxFky8GiBh/b0rL+BxQWrlM6WaxRMKLMMvNwRR6ZYPWIsKHt6Tuy6gvI2pQ67Qoq27QXIRd5oiUFOrUq6OqzqDvEaong/Htskv3ZU3U4azmQpzGyCQhcRL58hsNDJoqCzCOFK0H8PdWIlO6qUSIUxnOgaKzVVKQ0nmiOpz9gMRK2zvaNPfIUIPi5AhR+ZrtLEFPoRupRAc5h9jlArVHvp9RmM7YzuzJZZkzdZittKyIY194KgCgfP7LEZU4fK0vziHezmuaJQvo7r751/z37/8ElpjAx049Drljng4AiIqcomJWXtEIhd3wRZyFpMWSytUsYjRhyMWXx7SI2A3HJifLcOwlEgGhp2pORcFugsipcGpzNi3pkFAdp/gTUlv3U9SeFHSUx1gU08JmWCalQ5cm+GIVeCo2qTfXJHFKFsVY2Mon28adPOZj2NCpP5x6GZUj+CKjC+qEeV0MZnlduu5MQ6mZy9T4vJ2qeaZUrnVKa5ZOXpCI6dINjegAmVre3TkHKxGzIe9Xpu9rpk0LZuT5lBWXrAlIIpi2yjBKSjrI9uWqpVT2msxiCoJACSOKWBG7UqIFIGi3EyKNagxQRqLvQRNMTCQWtqi7SAt56IXkTA1aHfR2z4v+FPX+XAdD6zh1PbRunOjW0nq+cJoT06RCj0QFgJQjQTGFqjB1Z/ssZQxWqEiwQfRQXKgBgibXI6VabpV5H+utTkoBXablSzHFXlPRL4NWB4aI8UoJ7EqKOBhAEyKTSYV06XA61RJM4fAlpQ+wF+0FcMeK4uiEExkD0IRzoVkWLcjtLdyRad63E6WdvN9LK0bpXGbeRKUvaTCOKoS9Pkwxb/A4pBYAoLttB/+756Oyip+jfuw6mMuFQKd8f3S1vDCvSxl8ACjzzx6bWHKvSZV36YgYuoGCcICMkUmiFDXTQiTCBmSMqN9WRbI1XYexl3hr0O3T5i0OVN3FZEyk/H7Q9Yia1gw9tXkCOI0vFfH9bkBxiSMbeB/kR2rqObdmiZKm64Q+ndMuuan3Um5cKHZvMcvmezJb5kxllllmmWWWWWZkmTN14JY5U4fZVj37KSidxFElhAH0Rb670v0+mAgqlRpMwG4s7uRBlo37m1QDa9DsYIXY8ThHc5QLZo5KlhSWLyNqTiIxXqtHyJM7XkOupkTuAI66yFIQhbHhRNaZD9NNIyFxEBKN2J9tKu0niXKYFoLGPF2fKJFaleB2KYDYbyyQjo07OQJTZClSBpTvwRClN4KuR0HV8qflh+iJDL6FrQsJbSUdfo/vvBt38aB0I6EvVFw+QgH9tCttzNN9JSlRQyBvZsGhe0xm88n/8+tq9FM+r/yYi7FjBQKzfiW1L4lOyMwoicSwQT8RlBun0MqQyswsDarVkoiZzKCqFona0G2TKBEpxggoyiNZfijo9mn3LrOdNF1XWkDdNjSRXUY0XxDS9S3XhlM16fySNk0G88p7scou0a3mxDS/VmWUNMqYt5hCpPiJInXdxRahpYs75omKCcQ9jrklsGme1RkXatAGYswmxFQlXVeMYvTFOBi0B1TmQz5bfzEgvST8/D7kt81SPwMc5XPl+1OpU71HicDEzVlFw1VLiioNgn3qR1E9R9NNZXXKc0qhy6irkgukFtP8XbvR3v4gAKCycp7OabsWhvoKfQOAhQd2whTB07pbRjDL35v2Q4LGt0xCD43aiNLXkrXmfE/R5I0ZGr+5WpEoXmlxpwmIwPpU7TzRV5ppcaFW8Jqe8njUnEUosgulphyLYup7M59bkoWbDGT3OypAXaK9frtHpXHiiNF7a5cUkh756b4CeHkrKfBZE++1WchTH3iNBXrHkqWU5DlLU2MUbhG0e9TPzftF8k/+0C3XWczUgVvmTB1mM10HociOMeIopYgtC9dKOqIwWiO4vjhaoFgSwzbReYDHAUnY35yYVt+vjsKd5JO9VASP/A7ydf73yppJBbfL2I5kGjoS0HsckcyCJl78uN+lCUszDBREzTSatGJFNXkNRRVVXYfEQOWkn69X4ExytWmjPk73wBKLRVIaoTfLJyqpgmw4ViIORGXVFYbzcCIxUYmJst9YQE3ITtj1Ot2rzJYKusqB0QyD6D2iwMpuShRTKo2zOKZJNhm/JWNsxo4dx8Spm5C07kwDjhAmLRy5jqgSUjVvzgEygy8RA2JYJmIp6pqgEGRbDccm6jYvJQjGV6hxBsASzlC0exsWt8/QvQOA0V5IxHQspgqx8n7RlUK6biRS9Pk4zE1OYVgsnP5Ch84bej45EMn4lqArM69CKtZMcSaJyZ0NPCUF4Sl6SDodfrNF40xPOLlyM8GCgDYrzLBo6icHp99V0guWSc6nbCegaKHihBoDQXeA1mZRZ8/gTpU7WqLPlk0LJlalrtXbPU/Omq7rcCZF+nxtlOKMInGvhluimphxHAM9WYhYtKnbTgldJmsZAry4sRybvUafxqdhGxg/jocYlJere5XCp4a9h+YOJdiqxnw4t3NJTBXzutTuoN0j6rm3bVY5ZDK2r+CobNhaKaVODwix4ERhbJklGGy5B817tgBQzlB+tKY2C3lXZbnuVfAbAKw4Vu+taJ/X9EgmIpkdbLlLQxyKEyWipp16mTYZkroOe6pAeW9mD/0u21cYrcGRcapumSjB3q4GmptFf4v5qrx2GTJ78lrmTGWWWWaZZZZZZmQGDpLm+z2sfJM5U4fZDCevqrw350jvJlmnSe74DMcmwT2AZ5IAwMLWJrqzokyHQJYqpkWZNAh9QnhkPbBBaxH9Bt999WabyK3gu2USvgv9lPgjoVSydEnimJZARCzXQXEVR3t0KinSSUHZuWEOhZvLFHpmjovz6gZB+EACKZCV7BcaVMYjDkIMRCV1WcYhV8nBdvn3S8uKcGpCx2a8TrvC7kwr0d483Uss+l7+BNKUgNw5y12lzLoC0kKA8rkASZpPR0Vk+AwfsxrWCEcBvO3b+Xe6HiCQKRYGqiaZpM26bUIvgq6XSB6IaXcvTdd1WAI9K09PUHkPGdgM3SA0J1poIG7zXX5/bs+SRARec1CgVLaZ0l6SfUGCrqWqSi6g8kNV2m3biewxr9FGIKhTiRwZrkNlgwqj1VT/AoAW9NV4WGwhbnHkR2oKRZ5PdKzfUdmqhmMhV07rqHUe2o7a+O28X1YEpM8WzM/Q+SXCE/Y86g8robMmg9JjPyT6MOgOCEmQaGmYqPtobd2KvKkoUvl9KTobbZuFO8nHhGtadG8KyTFRnOTHFP2fMN0gGtBEmjIDuEimTIoI+yG9N5WVFYwcM536rNdYQGc772O7VKD2So2nJIqs2Y6i9ESGbhyEiIQuU1KE1qmXCTHrzfCx19o8Q8itOzFENF1evGtOqUbzQtxtI9jCk3P23HE/IVKOEPgtT0+QcCh0AzBbvI0JIVD5jnuNBWqDnEP7TQ+WmENGNgyjPC2D5HVCxWWWseXmiZrTk5pUMlnFNlXNTvH+AgoltislCscAQMK9ne27KbC9srIs+n0ch8r0g6T59IP47m+rZc7UYTYtX1Cig6EPJqgoDUgpKAMcns6PVum7XTEJ9Bp9yg7bfev9ADidJx0F3TJTKfIAp6o0Qwh8GjrB5pLiAhRVo5eqKmbJslThWrlwhoFSUPcTNbYkzeiWUFjD61Npw5NgomafFgygCTHCZGwI1TTrd5U0QHdpXI9umVQEVNJ5LGKpSTl535JWWhQCnyVdI3FLFgYq3kZSI4ZBCz2zTFrorWGRcVmqUVp2tNBQqdtuokBvU/VxeSV3IvMjQ4pOFcafh8g2mn0YLNqR+nvQ7VNGmtdYIMrEsJUit3zexckRFNbxenbmslVUzw5MKc/LenbhzDa07n5A9F2MoQ1H8PPW1cTtyAw5r4ugqZSlAcDIF5TTsXu7cv4k9RYGapzkXVhl8fx2IqUqLtsvx7c7tRzmGHfK5feZ11WUTb+LgRCSlY5GFIQkRxD2fXp2+XoFebFeyXdm5ueb6RnUnIKSpZBCtv0u/Cbvo8gPlANdrtAmQ4qR9mablDYfeiFRZ7qjiftyiP7xWh3E93FHQMYOsjimDUCyb+NOixZv6ayFcypuzal3qb4giT0W8qk4N+lQSodDt0zYMoM26lMK/8ixR6C4go9r6VwMWospajs/wh0Aqr+YqP8Zez1yUGQf92eb5OgXJ4dJ9T/yfCzumBNtEI6pHyPsy3elRe2X7y8b9EmUM2rOYmHzVvrM+CmcMpeSEXreVXIeYQA95I69dCuTG5PuroYqki42PhNPXYmqkGwwHJs2E4PWIqdWExYFIXQpoZHIspVj20xsxlgc0xwinUS9VKVMZ9ZrU+be4q4F5Mr8u/VN0/yzyyeR2ZPXMmcqs8wyyyyzzDIjO+hsvt8/YOq3y5n63//9X1x55ZW49dZbsWvXLnz961/H85//fPo7Ywzvf//78alPfQrNZhMnn3wyPvGJT2Djxo30mcFggHe84x340pe+hH6/j7POOguf/OQnsXz5cvpMs9nEm970JvzXf/0XAOCP/uiP8LGPfQxVkWEFANu2bcPFF1+MG264Afl8Hn/yJ3+Cj3zkI7BttRPZH9PzJcDjsH3YnIMhUBktUQNP1m6KPJ8CGw3HTlUVL45K0UCOTgRdjwIYvaZHu5zKSr67LIzXMXYSRy/sqbVEy0QNEYA8+zCCVgsAYFXbMOoTor0utJIICpdtNS3agXVmm6RDU1zLRUdZHGNwz895u2vbiG5iACKJYAhUKFWvr98lUU1JEwTdPmWBRZ5PlEVpQmZO5WkHrRk67bIXdy0QlRL7qtQL0SC6QRmLurg+F5kUZVNcB3adI0t6IkkAUtNH1+HUy/RZCsz1eF8M2j06Fix2IXEIScflhoc4JSb6wJ/jcL/cwfdmGgi6QhsnihNIXIzyFG/P0Ea+M8+tPR56jaMMiEOwvqAMJQrn9eg5dx7YSrvh+sYj4Bz/DP41oVem95oIdnDkKu62CTVRgeQD5AU6oSeoGDKZbQYAoZ8o7aECeSU6wUULRXal7aggeSFEyzylw8V8j2iThS08SDryo0QpFAOFUU4TlldNqJJMAkGK/AVqA/O9xDhQiKFdEdpTtVFV+9L3SJxS0s1+p0d1BOX1ZRuovYkyTT1KoOD3k6xvqFumKlOz0FGUtq9EJCNfBCb3PBXwLGvJlZTYYxyEhGbKfjfzNrWlUHfhiuuWVi6jkjQS6SxODqN45Br+vbEVJKApkyLihQZpO4Vdj8aEvKbf6VFYQmFijNBOo92ALSnYOdVfsdDtCrwQwTaeadgWP+utRVTXqpJT8r5rx26CdYRI5pA6bM05eo6a7QAy3EEgZ/25PZT55zU6hCSXV/E5rjw9QeN8cecc3U8cBDTnSsQtXy9T3/d27SGqUGaP2q5FlGF+uKRKxJRUzT+irrsdLAoNMBbFqG/gFGp1I59Hu4UaDpUddDZfRvM9ua3b7eLYY4/Fq171KrzoRS9a8vcrrrgCH/3oR3H11Vdj7dq1+OAHP4izzz4b9957L0olPjG+5S1vwTe/+U18+ctfRr1ex9vf/nacf/75uPXWW2EIiP9P/uRPsGPHDlx33XUAgNe97nX40z/9U3zzm98EAERRhPPOOw8jIyP4v//7PzQaDVx44YVgjOFjH/vYAd2TXqzAEGn9aM5RjIQuqTTw4qcAX2zkghwFYUp1WdIbahEPYdiyzpOZKgQMALWjplWds2IdWpSmFI1OC2GX0xh+Yw9ylqwt5kDfq1ArTJtokMWd82jdx2M+5KSem5ikxaq7+X7kBcWUpJIoRmjQB0Qb4oSas1QkDj1f0UOOuq6MsUjGMESJjDG/G1B8lRRbDBZ9csyKuk5OEqNU5jYC4czlqitI0Z1ixXQDsegDvVSDI9oadj1aXGXmVOCFqYVPOk6GPFfehV5Qitwyg1OKCy488DAa9+8RfRASvTm8bgRD66f5vS/nC59eGyNFfC1Uqs2SworjiOjc3myL6qQt7pxD7p5bebvEs4kGKtUeUEr50ilhUZyKy2HJQtzympKmi6JUDUgZWyYdw7AfqoLB61eDWUKgUzpofp/o3mBuNznK/qIYs7auqL3RGsX2WEWXMgOHj+F9ZNWHKa7GqI+DGSJ2T8Z/FcpqQbZsVUNybif6u9NZbYZlUp1BM28rx0q817lqiRyUQWuRqDf598J4nZTADccmx8fvdOlc0jRDp4W+t2sPxeTJDNPYD4kKD/s+OWOShrcKqqi5XSqoLMVE0e9UxlpCJFSapDnjboeyI/12T9GT4u92qUD3ZS6bVuM7jmC5stanmCPKXXovnWqBhDTbO/jzbt63k5wWd7xOTh4VlU62q9OkcWLURlTsqLBBaxFeQ9CetkFOlKxhGXR6FOtllwpEdfqdHrVLChM79Qo5WL1de4jidUf53+ubplOOMsmAiGfkt7bS3DZoLhJdPHHyWlSOOw4AYC2bBgB4iRCHzJ589lvlTD372c/Gs5/97H3+jTGGq666Cn/5l3+JF77whQCAz3/+8xgbG8MXv/hFvP71r8fCwgI+85nP4N/+7d/wzGc+EwBwzTXXYMWKFfj+97+Pc845B3fffTeuu+46/OQnP8HJJ58MAPiXf/kXnHrqqbj33nuxbt06XH/99bjrrruwfft2LFvGdw9/+7d/i1e+8pW47LLLUC6X99nGfZlRGYIpdrB6pQ5Dpnv32hQfYjgqpZe0jBK+UeQNaEfUmxcBxI6KJzJsA/k6dzYmTuOxS/ZRJ4BVhTOjm9DkiyoLi+Zd2FWBBnV6CFt8IdccF1oiYBIQKsNC9dkdH8Kee3g8w+zPeWzI6IlK6diOYixu5anf+X6P4o+SiAYhRAA0ESdBZUyCkLRt3OUTXFEdKkA97PUVCuAHNLFHfkS7RWnuqKuKAE+solgTiTxEQQhdIIFOvULohHSqEPoAIWt9pSTe7cPbI5TmxQIxumEYE38g+j6BBKZM9n3OIWcrP8avWZiYpXTtXqNPCEiuWkJOIDCyfbGdB0RcGvQyYItyFsJhxkIjVdBYqrXHfkixVFQiRteV1o/tUBydK/o9aDZV8WN/tyqQLAvJ5l1yPuOe0j3SDD1VhgPgcTN2MTEOhKYUJKrU2EWllRZ3zlFgsERYI88nJy9XLcGsCgV+04K5TJU24tdPoEZeF9AFGiqfgWURkhd32xztAEePZd8l0SDpUPrtHqwCdxAkUmmXXVqc/U4PXos7mrZYWOsbj6AEEBYGCLZtAcAX12CvBdQuFZRmXKtH84DlKg2ypMnxKx2CwsSQQm4T5U1YFKVUvwGJhvLfa7qhklOEHEPQbickUXRokSpRJE2iVVZzTqHPYUB9ZwkJhPxwiZwSy82ngrWT9w5wR1iiUOHOBxIlgvh4MCdWIdh+H+/D7Q/BFM9DPtvI88kJdcfr5OxI8xMbWTOfU3Fpho5YVCxIJmpIjbw4jlFbx9swctyR/O/L19DGIpzbSbFa8vuh56ekQSSS59QratOWFyV94r1Q3yfQMprvwO13prjzQw89hJmZGTzrWc+iY7lcDqeffjp+/OMfAwBuvfVWBEGQ+syyZcuwadMm+szNN9+MSqVCjhQAnHLKKahUKqnPbNq0iRwpADjnnHMwGAxw66237rN9g8EA7XY79S+zzDLLLLPMnmwmab6D+ff7Zr9VyNSj2cwMjwEZGxtLHR8bG8PWrVvpM7Zto1arLfmM/P7MzAxGR0ext42OjqY+s/d1arUabNumz+xtH/rQh/D+979/yXEWx9AEcmDYDu1GIvAsOUDFMNhll3b2g+ZiKvND7vILw3z3Vpqspa4h6Q1bZtVVRql2lhb5hOyQevGgTzEShqPiLGTWH6DQpKRYn1Ov0E6vtZkrJu+6+Q4MHcV3X4WJOtF//dkmwd5SNFMrlJWkQr9Lf5ffKa1fT6n+mu0o8T6pDr7Ypd1w0PWo3fmag9oRvE+mznkab+sJf4g4J1Awr4NwZgvvW5GlxaKIpCTMiVUpQVUAiAd9un5v5y4VW+GHRM9UpqoAgNHj18KUCuuBT9RVUg2bapPFsarn5SsqSaJRxVGX0qUl+iH7CwD0YoBY1JpjVp7OpfcX6LOS6slVi0Q/JtPfpWl5F4ZEqXIOUSkyhdvodymDKQ5CQhwKYyKD0ExkM/W7RAsNmh1K/e7uFpIUjFHtPv75Tuq+wh0P0Pcrqydhy1gZ0ebgwTsJwdQtU0k2FEqKwpK15hJp8qm4rr1ivACeqSYzyQZNha45Ap1LZnzFUZyigAD+PH2qPTkg6re7W7b1HsjZxHQd9GWVgj0LNI5kgXLDyVFavTs5Qm0hwctqKRWfJSksa5Rv/FLFnQNfvbteF6yrYhEBwGt26fzVbhuxRBgFeh776nlbbl5Rv7GKgVt4gKPQfqdHKLCm60Q/SrMK+ZQgLN2vJeQjIkaUveUq5XbdNmHUhbCuyFrVrJyiqTstdB/mY1WFQPhEAZemxpSquaTwyi6MvBATzruJd/FhardE7PRErGRhpEqhFzSPLzQobMBvqTqVMuMx6PpUicKwTMzfwUMk5u/Yjqln8v4sS7FSI52RndmTy35nnClp2l4eMWNsybG9be/P7Ovzj+czSXv3u9+Nt73tbfT/druNFStWpGMS9prIZQkW6TQlq58n4xpy5RzcUT6xJ5WaO6KsheXmqHwDUVSGQbSP1m9TYVpSOg8DWvDNnKPkGwylUSR12ZJyBrpt0kQlJ/X5O7Zj2w13AACG1o2htpbHqthlV5UyEbFB+bEgVRpDag3lZUmRoQkVgxNHihIUpSw0fTfFQSUpkuJEBfWNPO1fOmMIB0BHxCH1OkrLKqGvRYWGLUuVc5GK4XM70ReOemfbLFGKumXRpCoDTgFg7v9+KvpQXyJBwMJAXb/fU85rQrVZJg/U1iiZBhbHaN7BKQ32a06r5mpFCv63ptdTEV963qZNjl3FKSBKLKJS90suBrqjSpbE/S7poCWL0cq29httom0KY8PqPDIweDBAn4KTVVLE0JEi5d42UFouxmccq0Vb0i6mpSgq00YoCtxKB1DGRQE8JsUQDh+gxod01KOFBgXhR52W0s+S959zFPWcUP1fstBCSHiIsWGXXRqz8pxhc47i/IKuhygQdJNwHDs7FlAY5QHRldWT9P6443VFm4pr6m6JHFTme4oalnGMXhfeLqnArisnai9qHgB02yHqK44jomtJJT5mKAjaKaWF1JdxmwFtcsyCAzMQbUjExSXV+klyxDaXjO8oCFPlmKSDI0uoLD68iLC/GQAwfmKM2gZe6ko+A3ES8eV04D8lfoj5IFctkpNp1kbo8/SthNYdCwPEYhx5rQ78ttioCS2xoqEnZDPK6ULc4PFbvozb7HRVGah+egMKcMpTvtelqTHkV/E5gjYC4aGLmdI17aC0on4fdaZ+Z2i+8XG+OOyNDM3OzhKKND4+Dt/30Ww2H/Uzu3fvXnL+ubm51Gf2vk6z2UQQBEsQK2m5XA7lcjn1L7PMMssss8yebKYZ2kH/+32z3xlkatWqVRgfH8f3vvc9HH/88QAA3/fxgx/8AB/+8IcBACeccAIsy8L3vvc9vPSlLwUA7Nq1C3fccQeuuOIKAMCpp56KhYUF3HLLLTjpJJ7t9tOf/hQLCwt42tOeRp+57LLLsGvXLkxM8B3O9ddfj1wuhxNOOOGA2q2ZFmAkgm4tRYtQTScR9BgHAan8OvUyZbB5jTZRLVRwuNFF80H+vdoRVVUcVUDhLIqg+UoAUdb2IqXzxO5s73R3qk0mMsL8ZiulCEzp7YLuC7p9zN3BhRX33LubUJvaUStVWrGAvRc2b1Wqx8tXKCE+ETiMOAQbCGSs36U07SRSIiks1lE74ygIsevmO/l57+O1EGtrp+BMCOfXtFM1zQBefFlPiDiSsKlEphoz1N9ht58KSJbZVXK33bjzQbQe5N+vrKzBn+TPy5YoW0I2IIk6yh16de0K2o1D10llunXfdrQFAikz2aIgQv/bvwQAFOp5jB7PKd7iSk57aZalhDQNg4LFWRRTDcR4scWvFfoKkfO6qo9k1l4KeQigCYpLZlDpeRdxx6fPSgqstnaS+ouKJhs6oTks9BHu4gVspVBo677tlDoOAE6d7+LlOLPLLmVb7bn5DgAcDa2snkR1vUjxnxSIhu1QH3iNBaJtzARtJfteM3R6jma5QgV3CVW2LNgjPDRAL6p3TSJrmq6yDA3LJGV0u6jedYkGlabGKFkDukE0HCGFSSQm7xJ6LJ9LMPswzRu5WilVTJn3a6DQLMdVgpFhQIW2pU2cuh7V0/6QX7dSJ4kMRS3mYYlNoZZ3aWfuSGQqjlPSIjITVDN0mHvVDGTdPj07LQiVKKxIjnDHCsjXeVvNvK36PvSJcpaCsVrOQSRQy95Mg5B9WQi8ODkCW6DTeqFEfUw0e6JYdLLiQ7LGY66sziWrGWi6TufwGxzxHrQ61AcAEjShQLFtgwqBF0ZrNB/pxap672RmrJUuRv9Emm5o0PUMmToQ+61yphYXF7F582b6/0MPPYRf/epXGBoawtTUFN7ylrfg8ssvx5FHHokjjzwSl19+OQqFAv7kT/4EAFCpVHDRRRfh7W9/O+r1OoaGhvCOd7wDRx99NGX3rV+/Hueeey5e+9rX4p//+Z8BcGmE888/H+vWcerkWc96FjZs2IA//dM/xZVXXok9e/bgHe94B1772tceMOIU97tgIttE03WaJFisUs5VqrFL8LSRL1BsT3dmD01E0gZtH715/hKWl5dTsSsAoIVeonhxvKQ0jAZQAVsA6dIy8qeAtENvQIucVXAozkg6NU69gvJyDnW3d3TQfoijevmRKvIjUhVcaUPJDD+ZnQOoxZ35nqKaAl9NquKnWSyiMMr7TTd0dHdFoj/6FKMjncz5u2dQX8cXwcrqSaIspLPn1Cs8c4ifjJxHGT/TfXiWHKDi1Bgqa1aKdo9T33Y330/3UFymqFjSOxJp9nGC5jCdHOnQyBiXVNFpT9FKoTdAd1YoT++WKfcqvqrX6GP+tgcBgOJX4iimmJTCeJ2c1ziKVAybpJJsRXcx3YC/wBeZ7i7eB5qh07nyozXKsJOZhbLvAMCeWI6a6E9v58NYEEW7u1KfqNmlRaY4USaKSW4U5u+eoTFtOSYKQvVfZka543Vy0GQ7AF5kd+6nt/HPTPI4vvzEGCl2++0eUVxywbQrJZUlVqkrOkk3FA1NivmKbktSTFpC60jSN7nqInKCKpKK25EfofmQlL24A+Vp3re5WpHoUklTsihaUkaHHxfZhJ2ukkwZm1DPQUqMLDSU+v3snNK0andpLMus08LJz0JUFPpayXg7WSrIKdAcoDsFmmNs6RDHMdH4QGKTEGBJfBUAkgWI/JA01aRVVo1iaD1/v6xymajG/vYZmvvk5jJXK9Hz9Ns96vv68ev539efCM3hn2XeImJB99Ic023TZkFPvHdxFKMwweer0go+bzgrVqj3w+sqytxPlpQSMX3tHjnt0hkrrxpHVRRbt8ZWqALnvQ6CbfeJfhGZi0OHrpxMZgduv1XO1M9//nOceeaZ9H8Zg3ThhRfi6quvxjvf+U70+3284Q1vINHO66+/njSmAODv/u7vYJomXvrSl5Jo59VXX00aUwDwhS98AW9605so6++P/uiP8PGPf5z+bhgG/vu//xtveMMbcNppp6VEOzPLLLPMMsvst9oSKPHjMu33r9Lxb5UzdcYZZ4CxR35Imqbh0ksvxaWXXvqIn3EcBx/72MceVVxzaGgI11xzzaO2ZWpqCt/61rces82PZeHsTsQCytZMm2gW5ntEN5VEzazSmmmiGKLGLsr6ibwBweXSNEMjzZ6kdg8LxI4vFfiuU0aUpBE4DaJTWwiZCtMIGMB3xZKm8BoLhEjJ7J3CaI12V93dXczexVGswLsDo8fzIEtJ1Rj5QopG1JLtEX2kCXqEhb5C1wQioAOwEpOADD5lcYvEIWUg/8LWBczdyduSrz2IkY0cBRg+hlOLSXQjas4SkiH1pDRDp12lPTZBSJpmO7TLlcib3+kpNeogpCB5ea+6ZdLO2nQdCoQmpDJU6sssimjH7zU68BeFArkYR07NIUV8p14iHRw5XnqzSkkcUJlimq6TmCBlkFbqCh3Lu7AEOje4ewu/F88n5XV3zZEqW0zSiKYFc1QVWKYswMa8QlMEUtOd7VGsRX60RrSmRCF028LCQ/z7sR/RZyUi5zX7FMBeSBQE1ww9VWAZ4AHqkn7xOz3SYZIIqbl8tSoMbVgU3Ly3jhMZUTJe6pkBHMGVaur50T5RPVEgaEBDI7HH3nwfkS8qCCwfpmdn6xw9CRcXSRR3YctuygyUSEdl9TIUNghkt1KncSQDzY1EIHnQ3o6WQCsHzQ4hlIbQOEMcwegJNLbxMCWeSDRqSeanDCUQP+1EX/ntbkorzk9osslj0iIvSGQny3qTw5TxC9OGJt77oOulagkCgOv5KK7gKM7Ei54BjPNxJIVsWdAHOvPivmYQNThC6jeUpp0c/7lE4rdTLdGcJmldzbRoTC9u301zi6Szc9VSSgB0+ERejcMcV4WY9651yj9g0ZzZFM87ru7BoTJNP7i4Jw0ZzZfZIbbBzq2IconCwNKZ6rYpxkUKOGq2Q1x+2FNp/4aTo5dfwsiWY8KpitiNiCHcIxSHxWKYir1ISBvQtRzFz7PeglK2Dn1yKihmqt2D1xQFiyOGwohwNmQmkGWqFOqiDaut1MHl4iZjVXSrC8sVKdAjYzBF9mGK7pKClCxOlGIQsgS6AU3Gf+ltJRKpa0qNXFBJhmWgvFwVSt72f3wRm7+HT6qrnnUURp9yFP9+zqHFg+6lXKCFJ1lyBGaOKFLZLqe6kMpykkYlgapFcrxgWrQ4k5OYiMWB2aL08DiK6X6k2a6F0hSf7O1yIeFQCsdtrzInMv3ectU9kthirw0m79FxiYYwHR4/097WQBw9QOeXtBSVJnHLlLGo511a3K1aDeXpvjgXP+Z3fVpEYz9UDr4shFxwYAn6st8P4QuaTz7XfM1RWWJ+SPerGTo5qpS231ykDLvIGyCm90fEGw08JRsQxxS3wjPo0qVnNN0A0xOSDnJMykUyDIg2SsZfyXazKKastcgLSZzVsA0URqqpPhi0OqTKH0cMnqQ6xRgor4pVlmEUgcnC5XKh1g1y9kJvgDDhzMhNkKSt4m4HTJSuiRYaKtYqGUOZdPbFIcqsTXyORTuJruUZjVItPaG2LkxmOwJK2T0/WqONJPMUJcnimM61uJknDi08NIvqXAsAMBwGMITQa9KSjmAyhAHgNLuM79JNixzR3FCFshpT1RsEbTpoLtKGRYY6VFZPwlm+QnxHiQyTIGx7Tyo+SwqisjimDGf5jLqCzs7syWmZM5VZZplllllmmZHphkYxfY/r+xkyldmhtqg/oGKhhltSWTu1hHAoFfCcTWWtydpegNJQMQIF+0uYtlB3KWOLaDzHJdSEhYEqb+JyJCi2C4Ao56FDabBEYQAmArBJgLHVoV12HDMKLpW7fBbHFCTsVPMoTnA6IT9SI9hcBlzz4qyi3lenC4mfWbJ9hSqYyEiEpkOzBC0ld8hej3bLkecTUhcFMXQ7TUsEXki7YMu1ieaTQelDR62k56CZViKIvykub1A2lO64KiuTxanCzdKSWWuUrSSO5cdG1K7V91JCqPw7hgqGzbu0c7bcHOIoTX07tTzyo1V+fssi6oH0bFwV3Gs4OVVDrlZagkwNZueQkx+uTxDaIM8/+PkW7LyF0ySzt+/G5Ckrxd/FOPJDEjV01xxJO3u9XEd+QiVbAID50Aw6D4uSOXNNCuaVxuIYhiOuX1MaRBKNMh2TMrbMvA27xJ+NVVZipJISCnp9OmaXXEJ7JFVUhEJnmW6qpSFBXRFSmKBq4jgmOoyCvgcDVbfOD5cglIGnkg9YxChRomMbcOp7Un0kxzPAEUiAvxdSZ66yelIFq/ueaos03aCxaTo5ojWdeky0thzTsddNodYpGgqCxpS0v2nTZ2WJGi2BStqDPtFdYd+ne1f3HVMg+WBhQMdl+zhlKWi6OFKaVZZJlFrQ5d/vPLyI9g6e+DF/+w7SZzOpAHSQ0ryS5X+MxPtpiTnMLrs0TsxiUY1fgZhHzVmq1dhvLBBVOrSJl5Mxl01TnU09rzTbKInHMCgLMZrbSRphoTdQGaayfuHBxDAdoGn6wcVMaY8SjvO7apkzdZjNrha5cJwwufgGu3ellKUBpGvzISFsB+VY2WJCdCbG1EJfqsIcnwYARK5S8dal+ne/DZiivpTNJyam6dCYmPQNi5wsPQigiRgD2S4Wx4mFjSVqe/GFwHQdEq8srRhVMVGJlGHpRBo2wITcwPxtD1AG2sTTuOOX23gSUFsm2mUDoo0UGxJFtFgE3T5B5MGiTw6fpLlytkG7L01XcSs0eRby5OAgoUouU629Rhu5Ko+XKK7uwpJp925ZFYGW4n2Roi6CrkfP0ZVxKrURJcYYx0CU/j4b9BEnaBP57JPp2rKwteU65Ehohg4rSMsYsIJDz04z9AQFq1Lt5d/7DUVPOqZNmVwyJmnsKVOUOThoD9De1hB9LGg+Xcfcr+4X/dZC/anH8b4dmSRnRFYpzA/vxMJWqSKv+kvWfcxVi4n6bQ71oaSKF3fO0TuTqxZhC2rPqNQV5ZYwUtWfGiOJi7bIMLTcX6Iqi1EPjVMsI4BEHJ8UaAyRWjrkginr4sU59SfbpGfj1ESbmkrIU8a/AdxZko6CfN6h56M3y++33/R4pi6A0RM4HZ1bdRTRjwCgiYU8ZeIZ5t0SnBWcgtJ0fUnGL79HEQc16FMWa5zYIKiMxUhRoeL909yyir8an0JBOFmGbdF8JSlov9OlUIFeo4/SBH92JDFiWuQYRt1OWlhXONCFUREKoGupOpwDEZNHG5eRGm1sQs+nzVtPvNfSKZPnlPGcBUOHJjL/pKp5vNgiB9ywTViiveGiyOp74C4av9bUWhgyI0/OrYkYuzghT9GbaVABcrkp1hJxgJk9+SxzpjLLLLPMMsssM7KM5jtwy5ypw2zW+EowQafFnSahHv3ZFlEtEjY3HTtB7zip0jFSVyU3yqkqe80xQIn/ziwHkUCemNx96iYi8buum9DkzluUHNFZDE1k/jHdBBO7cL0yTLC1Zuyg69uivlQUREuCSgujNRL3Y6FP9xh0PUXxyIBP26FAWAB4+JbtqZ8jG3+qausdexqvPQclbIfQVxmRcUwUl2EbVLdQGotixLHCFGRws0RVgKXBqUkbtDpUBZ5FMcoSXYsjlckl0MFcrZTS3JE0mCXK5Bi10ZQQYZykT6TJJIAgnVFp7EVf+u0e7bYtN09IIaFRuk79Lf/Pr2WRaKxEQgzLTD0PKr0h6M/6xpBKyCzunIPf4deS92qXXSqdMX/HNgoEr9RGoIuA4mR2mE7oWo529DIDrTDuEZpkODbdj9Q4a+/oEEpWW2tSGzXbAfpyl6+oPdkHhmNTu6TtuXsr3GV3Ym/TdENlVYpECC2O9lkWSj57zXag5dN1NpNtsdwmWg8J8VcvRHUlf69Hjz+CApllJlzY7RMVurB1gUrSlFZweki3TaKDtZyj2pDQfkLi/ZDH426HdOtku3LLJqnvWRggEEKxUmMsDkKVtVZT8jNyzBq6oYL0TZsCyK1Sl0IBNDk2/TCFJpWWVwGoskQsDAgNijxfoceJuqEyEN1yc2DivY4jBsvlc5/UmyqM1ujZsyimPpZIeegNCG0KE6ECvZkGDIEcGTLBJIpUpvJsBzt+wucpnUIs8igt589z/OQWCptO5DcoSw3t3o5gjj87v9MlxKy+8QjYNd4HMimoE2kArsahsINVMc+y+TI75KYXKxQHojsFCOIAkeerjBcRaxB0VVp12PcRefy45eZgCaG+gnDAEMcwl00D4FkkmqD0mPxp5RVFFofQBnzySL4CKrW7QHFKsjgyb49KT5Y0RRyxRGFmPtFa1aoqXtztECzvG0rEricm6OTir1smimP8ezLDafO3H8Ce+/mkv+HlLRSOTivOszAgys+pVzAkFcTXqOLDMm5mz+YGpdXnyjmMbOLZkzKDzxiZVMKlcUyxKHKCHzQXsbiTx0u0t+wip8M9IlAOp8xqsx3YZeHYjY3QBElxKHGkUsvzLuDtlbmTWJgQqwlct02ieqRTpVtmajEIKW5MxNNVi4o+MoxErIihnCVxzJ0cIcmHpBCnFE41hwJU5OJbK5JjIyUMFnd1EIo6ZoP2ALnbeGaVu2wUxhhPD5f0UdD14IgUf3dyZInMAqCoysjzidJrbxM1LJsexo8TMiKrVlAf86w0QT3JOKlygaQR+rNN5UCIBXfQ6qCzlQt8lt2yylDLOeo57atAsmmlM2UhMrdk7co4QmHMSF1Lt0ws7uL3Upooor6ej8N8vUJOcWvzTupPqQqeK+dw16/4Qnz7L/nPo48fw/KncbX3/Gg1RfcCfNMlKTLDspAb5vS7ZlnkYNBmKOEgaqaViikCgLDjk5O3uHMuQZvy99OZmlY1/eKInLig01MZponMVh4DBtTXjRBtSWrynabaeBUcakvk+fTe6bbaAMi5MfJ9osJlfGZufJyeF+u2VTxbgoqne01QpmHfp82ZH/WoP2nMb13A/Hbh8ImYofLuLnoNFTu6Qmw8pOxGMLcbnW2qlqIUZbaP2KikOYTTbs6lS5hl9uSyzJnKLLPMMssss8zIODJ1EAHoeAQ9tt9hy5ypw2y6W4IuanXFYUC78Vy1RztnKifgqfptkRfAF4GSvfkeZIaZO9akz1YTJS6McS6sSBpNcQRNVCHXfBVcKhEHzXZUCZM4gtbnO+dooYFQ1L2S5tQrMCxFo8jg5NJKUbG+VFMB5o5L5SaCbp+Ch5M/JQWgGzrygprTE7vx8nK1o5fUFyEHtVFFbeRdGI4Q9Gt2CPGSAamdhxcxO8vbPRoxNXlQALFN7WZhAEgqUaBNdrkAY46/Qt3ZDvqNu/l975zH0FE8q80UmUL9uT3oC+2b0POJHpTlUWprRjBx5in8O2NThGypzLCIKMdkhqAzVMFQouwPwJEQGVCdFJlUqM6A0CrDsSnbziyXoQuUVKJRultSQo+JTDCmC6TFKRDiYPshrAJHxGQAuSzdw7+u0f/dX92H6lqhnyOQwsgLiN4pr5pIIFNiZz4yCaMm6qgtNEjMkI9/YOIpE5g6/wzqQ8pW7bWXUM9Jui30/ERGoAhMtkwllhjFqKzl749RqSMmelwJk0oEUwst7J3HpAGKeo4iCmCnDNQ4RvUIpUtUmOR9H3UXqeTOwraWuNc+cmVR+3JZEWsFmpOrcERv4sRVKE2NiWvFKQRT/pTj3HBshbI5LnRZV06gTWa3Db2snr00ec6grYL6ddukMSd/lhsLlCGou2XKeGRRTP0szSq7GBHIUXl6AmaR064ycUAzbZWJbFqEmhm+B6soEPJFgZL5IVFUhm3AFQHk+VVcIFiv1BVlOFA1NaUFcUyUn9/pUZkbzdAJ6UvWGZQWRwz5hIZb8jjAx5ZEMwllK5dR21CkdpljPCFALw0pGlkyCLk04vlEWhYzdeCWOVOH2djAQzwQC0SnibCVKJApHadHELaL/ERdK6Huved+kWnWVAtuLafqqxl1kQln5ShjjFTRoWKPouasis2JY4qX8NtdlbYsYrYKo7VUurecuEmosNdWWT95lxbn/GiP0qGlMzVodSibxnTMVFwYwLPyZHyLVaul6JclFiqKK+x5dC1JO0VBhKKpJsPmvbvEffFFvFKqQk8UklXiekLRuOyS48iiGN1ZkYmzaw+do7RSpDXXSvQ8k7awVWQSzfdoEayOTVEfSeIhbjdoMQp7iu7l2WEiAzORPi9rm3V2LS4R9cyVcygML4p7LVLMiFGfUDEyvpJ2kI62ZjtLxES1XJ7UqOMgpHg46SQGXZ8cYTOv5Dp6c4pak3Sdbhu0+JoJUUTpRGp5lwRZ+w89iMWdvF1Da3ibp57zdMqojH1Ve5IFgRLzDGRcjE+q57lqkZTfu6ItoeeTEGbrvu302eKqREdKUVG3nKYi95LFYF5XZbglxmkg5EIs10FNOt8Tq+h7g9l5ovlkbJTtWhSfaNg6KlNVAEB9k1Chn15JbQn3zBGlHVHxbpvouDgIyeHUocaPfBf9Tg9VWbC6XKdMTul8BN0B+mKeKQznafxSHJavZE7ytkPFr3MAUY1MvJ+FkSqpluuVuhpfsth6YmOTrFMZe10q4gzhTPkJccvhY1ahdsJT+L0LR4V5PZWRGMf0jmsFRZMn6b1eonakNKpWUC+rsRXFRFUm51+ZmViaGiOpFaKC44g2DebkGsR5Pt9FiXAKuemF1sahMk3ToB1EoWMt/v1zpg6dcEVmmWWWWWaZZZbZ76BlyNSTwAgNWmgoIczmIgkJJgXuJOpjOiYGCxx9GLR9WKL+ntR7mr+3gYUdfJc93elh9CSpWyRKiiRqdLF+V5WLkchDHBECEyx2qV0A4JT57olqZUFVsPcaC4gTQfIAFxSVOlPFI9cQ+mFU6jAdmQ3H2xd0fSyKoHDDNkj7SQZ+mnmTAtj3pYuTNM12qCYai2Kqhyf1pgDALogAcUOjIHdJ77iTI7CcBLROEL0oq6HrhM4BShSzODmC/Ooj6R4BTleURQB33GkRjVBcxq9ZmaqiuIoHZOulamr3DXCqarDAn+eg1aH+0A0dhqAcwgTyJYNudUMnVEMiQaZjwi4JjafxOuw6fzZcVFBkfUmh2EQZEb1YVWV9pOaVbtCY8dtd2r0HnsysspGv8Ws5NYfGp6brhK7Jdg0dtRKltRxZ0it1okQI1dQNBLu2AAAWtuyCU+VIydhJG3hfj0wqfa+E2CQLfcqMTWY2qj5SQfhybAWWh1xZBC6P1GCXZSC3kShhpLIzZVvjTguR0CKimoKWSSKPmmlR+RF5zfJRR8IUwfia7SDcvQ0Ap8tkgoQcs4ZtUKLB0NplVBvSqg/T95OB43vXwLPLrrpXK1EDUjcIeZIaUEHXIzRUq4/TWHbHOUIStHsIPH6vvfk+7DLvj6GjpnlfRBFpjC1++xeob+Co+ND6lSobT1wrP1qDuUxQqbURmg9k2AGLI4VMWRbRf/FCA/5ujijLLMPIG1C2bGlqTCV7SH27fjdFlS8V0owJvYs8n8ZnFMQ0F6t5OIfAFSW83Bw0Q5TCEghVaVmRBFXDvo9YorwJ5EuW5Qq23QtzmKNzWmkYcU6Ixhp26uehMN3QUxp2B/x99vuH02TO1GE2Fgaq1l0QUiyHUy/TCysXAJbINtEMnbJ6rKIFXUKy4qfl2hS3Enb7Kv1cKoknTMs5SyBKpuuIdT45WlATv+4UCKKWi2i00EgVMY0TGVcAz+ySFNq456O6cR3/fuCnsrMAvmhIWiroBuRMSfi8MFpEZY2oWVisUvzSvoyFAULhkPqdrqpplpBDUGnVEdFRMpW/P9uEbm6jz8pzKfo1oBTp4uQI7DFBUY1NqSwkseAyr0sLQJKmCxYD6rfk85UmY3H0Ug12XTkf0hnTDJ2UpVW9s4CcmciPSC5AOjX5mqNUz6tFGhss9KHFQqJC1kEbeIjbIhW+p5wHciwTNCCPdxNOlLim5ZgU42MXLVhuQrVfynmIrDanXkllQep7FbmOux2qMQlAFZmeWM4PxDEtViwMUirykt6jmm5RjMhKiMbupfZcGK1RAWdrej1XuAcQ99rkLPkP3Uvnlgr+nPJL1xTU3TLdF6BirahmoVsmcdi420Ewy7MIezMNiouUqf6aoVEx59r6lbBGuYOiJZz+pOo5FZMW1Jfp5MhRMMuVFD1JEiwi42zQXMRgz4Joa5c2LzKeKT9apXHcuHcOM7fyWEopKipFNAHuBPZnW/y840M0n8gsxV0/vQ9jJ/JnWzt2Ez3zSFSHCNptJdeRL5DD6C90logbG06O5Dp020lnXYK/U1KmAb6npCIGS98/3TYTMiH6PoOylcBtl5ze6jTfWNXWTtImZ3HnHM2ZtaNELFuppmQrvC7CWd4fRhRBqwshZEvM2dqho84OWhqBZTRfZplllllmmWWWWWYHYBkydZgtXlxAvMhh3jgIYeZlbbEcIVNyd+k1FmiXwyJGlIluG4RCyaDZwnCeglPHTtpAmiWSpklCxlocKmqgp3ZnFNxdH6edOQBEgqZgArHQTSsV1OrLYPWOoigGorr94rbdKWpM6iHJgOnAC1OBj0RRCXSjvGoCuRUqsyop+Ej301PaTQrx8ol2jBKlSmSmjb8Y0O8SGQs9P4VGyawzuRO2Ciro1p5YTkhD7HuIBXohIfzY66WCoOVuV9KzoRdiMMv1aszRGehlTr2RUGcU0b1a5ZhoOI5opdOQ90ZZ5Dixira455hKVXR3zhOFpTsFsL2CfI36OAl5Ro1d8Hc8KNojEg7imAQ6oyCkuosSPdF0nXbjLIopENrvePAFKieprEGrgzHxvArrjyZqTKInca9NfW+XCnCXjab/ntAi0nSd6POkrlGyXqQSijURiWcuy4GUpydgLV8j+sVVCKHjgon3ItrJEaTWAzthiXPlR6oUzC6tuAIKcbNspRcmERNdJ9Qyauwi7bJeo4vYl8HNfGxajkn16syhkRRdD6TLkyTDAuT80JtrIlcTYqiOvYROBni5F4DXGZQaSLmhCgwxh8hsRNPJpcaeFFyV6ExnR5PQ8+qaMZSn+fthuXm6R/m83NES9aGkQQGOPAG8rFFIteoc0ozigqsJwVDwZy/vUa/UVUkomYWZ+GwMUPalnHV0KAFPTdfp/Ri0FtGfF6KdDn9X8/UyIayGbWBkI6fyK6snRR/ZiAUiZ5dd5Eeq/LMyED1RcxBQSQvxYgsG1TgU75K/tCTSE2WHG5n60Ic+hPe85z1485vfjKuuuuqgznWoLHOmDrclYgGsveBoab4jBOI8n+J6WMTgCNrGdi2Esn6T+OmOljB+6iYAQP7oU6BVxcITCKqrsU3F/piWipmSWUeJrDvNdugljxYaS4unmhYAFd9F1JmYkFgiy8Vw7FT8ilwcpegnoBb/pMkMJnc8MTkCCqJPxk/tvVhBqKHLWoJiYUqm/3b7IQzRBsqcKhWIQmK+R+2WC0HshySyx2uHCbq201T0nmgfV/dWC5eMzZGCm4WRmorNaM4SfUmp1F6XHLNkViBXeRfxJRRbZxDNZrsWZXrKRW7Qjuj3wAtV7A4AU1B5ybqOVDh30Ie/gzsQne2z1AaZTVhdPUn18GQbO9t2o7N9t7jugBb1wAupDbK/ucN9DwBg0nXSqfAAwpltdN7CaG2pIxEGqpYh1MIUegOVzp8oFJwssiufhzvFn7c5uVrR2UFAdFPcbdP4l45KcXKYFnTN0KmepNcQfanrKAupCegG0fqIxRhJxO+EzTkEwvEzLJ2cbXqvx1xy4I3aiNrkJOq7xQnn1SKVd5Fl1urT+NUtkxyFpElpksgbwJOiurvnUZK0pHAM7arKyLRdC5VVolD4Ji5BYBVdyugFQFlz/kKHxqqUECmtmabzxostDGZ5G/2E/ALV1qtXkJsQjp3tINjNYxypLmOtiOIa7gibYyuWOow5h2QpoBtp9XoIar63FQCvJ0lzlB+RAGfQ5WEL0coBZaAOH7N6SdaonDMAPjbkZlmOXXNkkuRqWDBQNf8SYQHS+Ys7Km71ibbDGTP1s5/9DJ/61KdwzDHHPO5zHA7LaL7MMssss8wyy+yw2+LiIl7+8pfjX/7lX1Cr1Q53cw7IMmTqMBuLYyVOCCQQor7KYjLUT5nB57U82tm7YwUKMnZqnApy6hUYOb4L0iyLysEQJdJ9AAu/uBUAp2fkbtdMlAyRdF6S4tNsh7JjZKZP1JwjSs/v9JQooK3oJcOSdcjyCW2pBfhCQDNJvUlUJY4ZHZfB4bptku5Q7HWhhYJ+ydPXVdaP4xJto8026VwSmTIsg+gTwwthC/FUV5SwyY+NEBwf97vI1TgaI5EYzTCIrmNhkNJmIhHHXII2kyhT6BPFVCnzHbY7Xle72cY8iSXq4nkkA4yTyJRm6NAFHSD7m9M7UtvJRBzLAHWBCi0G6DWUFk9llUJG6JnKZ9+cJW0czXaQH+Pt6c1wPbTOtlkqd+ROqAw8uZtf3DmH9o42XVfbC0FNWq6cgyt0uzRDJ3FYSdcNZucpYzI3MUl9IpEiFvhKBwtpwVJCoRI0YJxATmVZFSlWmnxeiD2VPNCYIbopibBKZMt0nRQtRNeXtGmpSmiqDGQPGvPUrkGzQ4kSQTcgvS5pluvwAGxwIUttr9I1WhjQvKFbKnhaIlSRFyTCBtrURtkXAAjZ8ts9eleCrkdzk0GZiTadv75+EsNPWc+vmwiml+NQsyxKsEjSjzIwvrN5C4lraqadqpsI8KBzieboeVdl+yU07MpH8Qxa+4iNQGVU3oxC4KX4pa7KJpmVOiA1nUSN1GDHA5S93Lh7B2lGyTkMQGIuiakPNENP6e0BHKGSSF9vdgG6aKtE1lAfB8x9LMNxTOi2/Bl1e0s/90TZQdJ8EDRfu53WxsrlcsiJdWlfdvHFF+O8887DM5/5THzwgx98/Nc/DJY5U4fZNNNSC2XoK2fKV0WAk3CrpGziiNFgTy5CVJ8qoerLBh40CbfLjJ3RSVjuXQCA2f+7HYsiNmL4GA6P50aHYUBMSHaiHpllgYmJSArvJWOTYj9M0QwAd47ssiiUbJkJFXdV60pO2oBa+HTEYFQMVsS3OAXKOkIYKLVpmd5sO5QtxbweUQtJS9KI0sEwNA2FYeWIAnxR0BNUJ2U0ipgSu1QghfNk5pjmuIpakO0yDHIK9LxLMRXk+BkGFh/imYNxEMKeEBB/flr0cUxZdVqntyRO6tFsb3mJOIrJEe/N9xEmqQipzi3o3nBxEdqA0yhmdYjGgRQtbD2wC92ZFgDAnVhYoiZt2KaieC2DaFXdNiiOTravOFEi2lQ3LSoAK82ZXEZxaZppk4NDNFkYKHrUMKh4t6brql5kQuA0ScWYrqDWhFBtsk4hdEOJ3paq0O10TJTXaFNskVSTT5rf6ak4prwLPeTOiMqCnCGhTLnwAjxzVabYyyLAc3ftxsLW7wEAlj99O2qnPR2AqvWmOQXKVNP6Xbpv6ewVJizqA0DVqfSaXcoYlGY6JoqTw6ItNeoDkp+II5IgMB2bhDD9ZguAosMBvlmwE8Wk40RdRIA736q25RGwRV1RSf3pxSpkLdGoOYuYaNeOcpCTmz5fjOkoUE6JHA+2A73EnefYztPcGDc4he1vuz9FTUszbAOuCK2Qm8/K6kmYQ2IDGvoIu4KelNm6XS9RwSJEX4qwyqxT34NmWPT9WGwM4k5T1ZOUc0m4t7b+E2e6pqkM8cf5fQBYsWJF6vgll1yCSy+9dJ/f+fKXv4xf/OIX+NnPfva4r3s4LXOmMssss8wyyyyz37ht374d5bLaYDwSKrV9+3a8+c1vxvXXXw/H2Uc1i98Cy5ypw21xhHixBUDQGbGCoqXeiy41nBJUWHHUxejRfJdeXbuCoG6ZSaRbJu3SWRhA3ysTJOp3kRviCEx5ahQ9UQakeR9HRypRBDdJP8ryD6GfKpPBr9mnbKlBq6P0jhLtNaW2Td6mrDrDsWFSeQ9FM0j0IoYOU5auERlMRm2UAqLjXkfV2JI1+hJ6PkndJt024dQE6iLLmLQHqcB3WfaBso6m1oKVhBgi1G5alhaxywVCavRiVQXs5xwqxZMUHaRyHLVRQrJIfLA1q0qd9H1FXUl00i3RvZluizLokqVSogRVI8eDYRuEYDKfUV97pEMVo9/gVE/k+WpCiKWIap+oGLvdVWKG8hknEMXID6mP5L1oho583RXnD2in35vv0XNwx5RYpLwvs+CQEKWkPI1KnZIL4l5H9ZEUlsy7JH7JQh9sxwP8fnseoZ0SdUzqBQVdD0wgNESh5V2FxCQCxPVCCUyiVEKUUzN06g8WxwkBUP5z0OpQFiSg3huZvek12vT9/GiNMtWscpmew+J2Tglu/8FdmPkVR01CLyRqjGopFqs05qJY1eaTdHe+XqH29WebNHaCrtImK9T5Mx5av5KoM6M2qvpeUMDRYEDPO4hiSKZdam4Zjk3IU9J024Qt2qNQmwF6uzh1bFgWCuId18er/Jo5F5ooe5WqG6rrRLuyiCOoyRItLEi8S7K8le3AEM/UqNTpuKRd+7NNSlTQdQ05gUbV1k5SsLnUlJMUOABEu7dRwLycD1kUEyIc9kP4HYHeCXrV6rSgi3kqbu9B1OCB7XG/qxIwZK1RfWlZsSfKNGPfmlr7/f1YUK/lcsqZeiS79dZbMTs7ixNOOIGORVGE//3f/8XHP/5xDAYDym58slrmTB1mi9p70G2K9Hk/JNjcGh4jmkEX0HAcxbTgV4+o04ttuXl6iaWjknNsSmmP+90UNA9IeJz/7tTLFKchTTcUtQHTonNB1xWlJc8VhBQHFXTTDgrA678VREowjyfhC2bQs8gxkWZYBsVZwI+QK4ssK1E/LhVflnCW5O/xYks5MolF0HIdWkilY5erDcjR6DctDK3j0L27hi8gWqECJqgFNugn4sL4z+LkiIptyrvqenFEfUuOZxSpOmPJOoLyc4GKdcnViinqF+DZipKCM0pVmKK//XY3IZcRiz40kauJxSihgJ6kUunXOCaHKDl5RoOBuNceLVaxH5KzTvRMe0B0QLKYsNwI5Kol6JZYQNBFIApLL+5apPu1Req3VciTs6bZjpITEP2VdOTjTiuVQg9wp2qw+Tb+HV2nBbe89gi1ICWy36QIadxpKudPxLqxbltliIZ+ivKTKfapgsFS0buQyNgU9xJ2+xSDY+RniA6TlF6uVqTv2WU3EYfnLynQbOZN2CLDz3YtyhDVbCFNknNVTGPok1MgnRe7UlJzAVRYgG4bMMQ4kJsOu+SqOL8oAuR71eMbmP5skxxtd3wIRjLLFoBTLanamAlpEct1yMFQ8aAGxdkNWh2MSoXxURFblK8ApqzOEJODFHs96seQChLPQBdjI1xcpPPK98OpV2DJ7OTmnKqF+LDMwmxTdubQUStRXMWpKqM+oTZPiWLqtKHTDepPpZqejEVjFAMnC1g7E9vAxDiPFhqIutzJMssVmBNcAoayl2cexqGygy50fIC1+c466yzcfvvtqWOvetWrcNRRR+Ev/uIvnvSOFJA5U5lllllmmWWWWcIOWmfqAJ2pUqmETZs2pY65rot6vb7k+JPVMmfqMFt781ZEInhVM3SMCAjeXu4u0T8pT41Slovp2LT7CbqKZkvSGUl0Ixa7SRIH7C7Srtdy8ymUCwCc6dUwhWgh8goN0geLiroSCJXf7qaCmGXdNynO6U4OEyqULDeThMBN0kXS6RgAlFdxys1ZyWu2GbURor6MRBskBaHpBgVxMk8hcoZlUdC0I3eNnk/ile0dHbS38Z1zfec2ca3RxC4/oHuY+yWvN3b71f+LyL+Rf9Y24I7y/q5vWEa1CJUoqYeqCDovHLkOmqxxZ6mAber7yWUwJ6aRtKixS5VKGXipTE9KUJDZk65CRwaWqSgoEig1YQs0yTB1ChDXEyhhsvwK6Vc5Oo0zGXTe3d0lDbAwUcdM3kvY8wg5i7yAyueYjknfo4wvQ6cg5WTfU9073yMdNOgGoQTdLVwTaNfNd6PzMO/v0rIixk7gCGP11NNgLONjWYtEokSnlcq01PfSTmNxrGq15fLYl0kkpjCq+sh0HaKuzEQwvgwAZ6FPVKZEjTRDV0kZtgXD5X2gWTa0fpru5e8Mf44LOzpo3fsQAGB0DacMMV6BlitQv+2NbEE3qD9ztZKqVZigiOU4aD2wE7ZAIMurJnj5GQCBQNJZHKM0xWmuwsRYCvUDRBKLpBTnmujJcjKtDnQrnRgSy2QW8JqYpCOVFxpnmkJNme8RKhl2vSXJGGHXg5EQlaXvyYzJVocyMQ3bUpl3At0e2rQK9tRaAFynCjJAPApS2aB0XvFTc1xCtJJli1IJRFJTTYyBwewcLDknez5MQYkZY1OprEgAiGZ3ILMnr2XO1GG2ztYZ6C0OTzs1h2iUaG4nxTwVlvP6W4XpaYKU/QU1IfjtHr3kMptIdwqKEul3MZjn8QiSoor8kFLpc9USpXPLcw62P0STYqrWXL+LWMLaYkIbtBZpwbTcHMVxSGrOSnDmUadHE43f7lIMgXSmNENH3Of3MrxxCiN/eCYAwJjeyK+vm5SpI7O1+A0r2QFK719ooC9iwXjdOFEPS6aO2yaJGWq6hu5u4SiIgqnOymZK8E/GREnH02t6VEy63/QS2Wkx0Tr9eRG/4kfkYBm1Ueg1TilGDQXdOxP8mLViLdGZ0oGKGjMYzIhU+m4/JThJ8VGJ+6Jjjk2LuuXyBcsu2siV+LHiqBKB1C2Tni3RxklnyvNp/PRFuvig7ZPKtWGZJMchzSz0wcQi6ndVQe7CcF6Jzsr4mSCk51Ws1AFZoJYKHhuAdD7jCHvnNuXrRaoHZzg5tAWVEgU/QO1YodYvladth+oPaqaNSIylUGaJNeapBl2q8HQirV5SvDnb2WccEQlalgq0CWJxjO5O7vg07t4pboWpYtD1EoqTgkZeOUnXkk5Jff1ykj956PsP4eef+CEA4GTxLo+8+ELKeoNuID/K+7AwxuPPjPo4zQt6v0d979TLNAdIaq553zbM3bYFAHeGZAaqdJSLK8bSha/32vxplk3ZrmahT5S+3+4ibqsi0LJfAlGHULdVJhsTsgWxlQdyguYeDWCId9wK1fhUEgRNmmM0Q6fNhV1yqS9pnmt1iGLNy/dvai30YSHWa1qAlHTQdJJXIGNxYnyqrFGKm4tiouQNyyBpG+nkJkVJTddR/akbyolqckmW/s5dOFT2m4qZOhi76aabDvoch9IyZ+owWxyEGDuWqwDXTzhaVY93Cgq1EJNUtNBAOFAIkNxVBj2PUBcZK6MZBqXfdrbtJukDryUQLF1DfljFOOxdkmFh807o4jtDGxowl3NkSDNtmuiCRImOZPwIxWeIIE2jUidZABs8kBngMRcyRZ/0nixVwFm3TVL91mdFweGEWnvsdZWukIxHMi0V02I7hAjolgkm+suXu1InRxNtccyFJ5wh0t5ZbFFJExarmKficu4sxkGIXJlPdIP2gCQX7JKDyBMB8eJexk8+EkNnPoufa/IoxKHSpAK4IrIldsOsPArmp2PYZD8DQHvLLlpActXSEjkCLVFiJg5CGKIP8sMiScELUV7On/fIhjFypgAVGBsmtKwiT/ZLh4pASzSrdkSVfrfLBULcSEvJ8ylmxXRMKjPDY6n2ii/xfLQf4guG12ijupY7NtYYj1nR8q4qbB34ytmXavLCyZXtD8Q4a9yxhdCB2qlCI2liNZhYnLXIhyURSDGewod3or+bX98JfRoHulNIKesDgFYowxROmgnAFPpY8nn15lokQVAYr8MVcgMyTrE/34HlinFqWzT+dHs3JV44iRJMsr9WPiMiB172ZbwwT8gsdB2lTcfydonYo7jfRbhrCwAebF8+ms89mlumjRoe3ira76G1VUg29EMqLO1My7nAotilaKGBoKOCrnn7lVOvGwYFwYfeIKVED3BHRKI2s7fvgm79AgCwXMQNoTRKBX/jfIU2NnG7ASNReBzgY15uZoLugGRZ5CYvX68kZDES7ZAB6gmHmWk6NAgnMelISaSMxSru0fdoM0yyMK6jElfspariURBSoXLeZy1++sQmTm6oevsI5n+ijHfBwcRM/QYb81timQJ6ZplllllmmWWW2UFYhkwdZiuMDaF+wtEAOL2jJeqREQIjKIS406LdU+gNaAfLooiE+JIZNZKX7+6cQ3sH36lJNV/N0EgAVNNVnJKRQAso7XmxC0PGNOgGUUFSgM5y8yjKXd9ojUTs5O6RBT6hZEG7Tbv/KAgpu0VmAObKORLPDNo9dB/kKeXWbo5YmMViSkhT2yvLI1mfTTOMVJp6JH6X8Rl+u0ttyZVzhCItPMTRpsi7GfWNotDr6LCq9daXWUM6ciLzKT9aJYo19hVdVVnNkYWhU58GNnkUb6Odh9GeEfctCuwuX414SAjcaTq0wV7p3KZFNAyLYrQeFJlRxQ7KUxzpkGMgStBxYd8nOlciVO5oCZVVHEkZPmY1zCqnH6NOSwmxJkyq1AdeCKfKn01tLadBSlNjhEBqhTL1kS8EN71GW6F/kyOEoGqGDsNS9RoBjuRIRGH+jm2EGtQ3iti+kbGEgKFPGZx2nbffrpTQ280ptKi1SAhO6IVobeZoUeUYPnb1nItYIlO+Dt2RsVp87NrdNhXZDTo9mDJmqd9VWZU1JUsgs+mYt4hY0DIS3Rs0O/RelVYug7uG0/YSbVrcvpuycM28ygxkUUxIoYznScY2lVeNk1ivI8QRY6/LVdYBGE/5QzDRLq3Laf54ZhtJi5hHbEypyIciHk3FywWoruRjetVznoriqc/k55K1EhszJOsSeT4hcZQZqSulcyApKeLSe0tZuEFIMXT9poe5O/jzKk7+AABQr40gHOGIGDNzMEQhcL1Qgtbak+obFsWJbLoInR0tJM1yHULyBq0Omvfxa8l4wNGRSZiC5oOmA9qjIDRxRNmZcbdDtJ0cu5brpCpYUNHxROyrRLO8RltlHFoWoWNyTA/2pNXEn0jTdC1VcP7xfP/3zTJn6jBb/eg1qhp7zklVEKe0+H3EBkWeT0HfppunhVYuNnG3o+Kv/JAgWxmzousa6UDJgqyAokyCXp8W31RgcnMWnQc4DSAX6aETjydl6nDnA+QAmQ6fpOxKiVLtpSMC8AlFOlHSqTIdE5aYVA3HVsWJZeBnXqV+a6alCgEnJB9kyjsbeAm4fd9BxNKMeo5iqSguqLGImVu4Srw7XqdFnwKMXQejJ3AHySxXKLi/P9dMxKIIXaOcAz0Q5SCCHjmXMsiUVSfAbP4dvb8A1hZOgVyYm3PkHANKCT9qenCq/LqqzI2e0JkyKVZExu2UpkbhTnN6xxiZVPSG7UCSC1KRu7drD1FJhdEiho/hC5osKwMkSiAttoiWJZql11dyHVX1HOxaNS0RAQCYp4WHx2TNij7kC7oLJIpVxyoZQzjvWt6FKRwgM7Fg+u2+CkROxPVokVj0Qw8I1bikc8nNjK9o06jfg558HwFANyhVPlpooL+Vvx9doQBu2CYpuxtjU+RIUDycHyKQ+nC2CXdE1SST/SgtP1ojKn/Q7FDAviUSFrTRKcS2UBpnMYxek9oFiHg9WSBaN8G8Rfq71Dhq3sf1mjRDw5Ev5grr+ZPPBROB2KzDxyYlAwAwC3nq46RDEXdkWIGKwdEtk+L4kvpccjNjOSYWZ/n3dvzgTrrvwql8PoqKw4idEt2P0ZRK6006p4pXcxD2+T3KDYhm6LT5i/2QkhYAfv/1Y2dgrRQbH9MGM8T8xxJRerI0DVSChJZTY06O0/6sKpQ8aA+IEpeUo1OvkMxIshRXbqiy5P0oTAzjUJmuH2Sh4+j3j/T6/bvjzDLLLLPMMssss9+gZcjUYbbc+hNgji5TB8QOmfkeqY5LtEl3yyrg01e7r1y1SOnUqjhrpIQE8zbV+JI/zbxFyFTghYBAp+wy31HplklCm+bQCF13cfNmynYbWj/N/55I4w13bcGiyFaSu/n6xlWkZs0z3YRMgx9SRpfMDuvOdmn3Zjq2qte1nO/szZFJQqagGyr4UwbPhiowWXPLsGVgse/BEtkxcmcf+2FC8M+nLCaJyDlVJd0Q9PpUc3CfZtowBOVXGpkkJKAnMnDYPb+Gk1Bp12SQ/DBHJaNCDVog0IleE4HMKqP6bQvUb8mg2ciPFGqX2EkSleqHJJYo0bLK6knYa47hHyxU1S34XUKZvMYdAIDZu+aJdq2umaTMUlUwu53KFJVUiUT3erNt2vn3ZhcJPXOmphWKKqiiOBE4H/ZDDAxV71HeX9ASQduzLbrf/KgYuyWXvm+XCoQg2uU89Zm3g6MupemdQHlE9HcLkejvpPSCVKzXbRVkHIeBqkMZqNpzsUCU/V07SJBRinY69TIhstHcTkVT55SESCrzT2QRajmHsuGkaW6ZEOvYDyno2xShAFapCkMmL7BYFSeWaJSZI5kBLQ5J4DZqzGD3zb8GAKLYaquGSFmd6WYamRHto2oEAPSBymbl/ROmMmhVbUuTfk9mpQLi/bMNKnYuEeuZm+/AcknBrjuBKFq9OkLIvrPIx9mgtUhJExKxB4COCHVob91D49RrekS9laYUwsn6fExpZo7EW5mVU4iUQDVhWDT36eU68iNK5gAAujN70GsIxfuFQaJOpRBLtUxFR3f71O58vYLcMH/HCpPiGaxcDeCzOBR20DpTB1Mk+bfUMmfqMJuWL6c0VGR2WtRpUYo/OQxhgEgW7QxCmqzz9Uo6RRl8opMTiTNUIcdKKhbHfkQZRPnRqtIHEmnChdEaUQis30UkY2HaStpAFjJ1prbBEtl+eqG0RGOJ/yGRoUelSGIYlkyrV7FP0sEqT0+gdBTPcJM0hl6qphxGokATjg4pZ1s2ZRGyMCC1aPkTcQRN0EJJCYBUGRoZ76DrRKvKsi2mY1P5EaM2Qqn2LKGYbTa4o9HZtpsWkNza46GJmIwoLyid0Icu4lrC2e2IW5ziChYTlMk+nLnkpCWfoenY9JyD+Q7KQgto7GwhM7HuqYhcEc9m2JzmAmC0lEyDjJPiOlIJHapE3wPc0c8NK1pWmlxENV0jmrD5YIuc+dKaaeVU0AYhUJpUQbxEJdtwiyhQrMsijT/50y4XKPuNU8hqY+B3uVOx62buJNqVEnJHn8pvpd9VZTySquryXcq75MDoUAslKWvPNhPxWYoClLF5kefDkoXI3ZJ6R4W0Qt5xkaPNQKD0r5ylJW00XYcmxrdV7pDmmaTmRk9YB2t6Pb+W7SwpW6RZFi8NAwBOkTKGo04LXVHORToyoyceBXua012xlYMWC6dWaD/pQYBIOp+JYufhXj95W0yYeZvugRlLNwARKZj3KRxBmt/uU/iAXqqRAwXTIkdRbticVkc5dHFM17WK/KfX9GjzFnohlc+hItiDPsJZ7lCaugGtJN6VpDSCdCw1nbKHdbcEJtriUtymTrSn1/SoooOcm3W3jFxVhg3k1RwTBHSP5jjP8Pa9pfGMT5QdtDTCQXz3t9V+/+44s8wyyyyzzDLL7DdoGTJ1mI0FHjBIZKSFckdvJLJEhEhmV9WZiv1QiTGWC2oHGyt0ReqX8EwblV0CAKWjxqgOIICE7grfGbUe2Ek7VcM2Ujo3VlnW7hI7Oa+LcH6Gri+DjAlKTwTRRgmVbMM2FRok2l1ZWcHYiRyNKh97PO3KtETRZhYk1Kpl8LMU+QsDMF8EascR0TZxqGrf7R20DiAVbCnbEifUi3Vb7ZRldlDkBaTRZI7HSt8HICoyt4zvLnuzTSw8wHe7Q7VRWAKZot2+3wVb4GhU3JxF2OZ9lgzY1/Wlex/d0IkyUOKceXpek887jwRPJRoV2S6YYdP1pfipFvlElyoBUiUomR+tETIlBUQjXynDW7Waqk0mi+IGAZyaoPnm+xi0RVJFoJDC2EwgWkLHikUxZXfJMavl8lT8tTytkMQ993FEbeZXD2HQvpf/fXmJCoHbJZcQAdlHYa8PU1Comqkyp8KeEnOU4zg3OkKUJIsiJTQprt+d2UOoim6Z9K5JQdqw71MWo1kuL9nBcsRZUlQdWK5IKBibIKpRju9ooUF9YJSqpEDevJsHvc/eei9k6V1zYpWqayi/P7eTKE1zbAVVM/AaC6iIagP1Y9fx+15/ApglsgHjhJK6RNJ1XaHmA08V+RWoaNjtE3puOHYKuSTtJdKh0gnJMh31HknNOQDozfD5KD+2TTXFKSSqIPDP2mU3IeTpwxPzoEzCifwInV28vw3LwMRTOHVdXcc1rXhRZ4PuS8uL81tKkFb2B/MWE9nWzVQ9UGkyrGAkUR9Uzs3+3CzNuYDS+8uP1KhOpEpEOoTIlK6SWB7v93/fLHOmngyWyA4iiilRqFXSIHEQkoOSzFiJPB+GyGBLCgrKxSA/WqVFPzfMKTiZ3k3XFXSYSi+OKGPs/2fv38Mlu8o6cfyz177Urtp1PXWufbpPX9O5JySBhEQBQQUdBZXfGAcQEFGHkYvcnZF5RsZBHPERfJDHC46DzDiKPswzo8x3RNABEZU7IUDunU5fTk73OV1ddapqV+3a198fa73vWtUnkHQnaWJS7/Pk6ZNzqnbtWnvttd/1ft7P55OECVuR1NYW+Vheq6k/k5NAAa8hFwSSTog6Wg7BqfichMX90ICm5FQMT4fofFNaZFQP7gdymYwU+U6jy3w0YCjUTKbMsaSHYzwItZigwU40e4uyc4T85Ovla9NwrCEosoToT7h/zK0f14akjqf7WhS7zbIF9zwN77kbdQXL2rtl4mjlKVJiIcbRToNb35uixdM5OGWHH1h0vd1ahUUmLb+i2XqGEKglVJKWp7ASde3DPiZnlXK7gkFKDQ/ty5Xy9dIeZkrSw8D2XO7/KiYRM5NC9eBLxzHDRvXdNdR3K3ZjWZvomgKFaaRo+XG+QzTQEoKp/G57HnXDYgWQMAqr2G+GGG7I7+JHsTaRNsRpScLAqtT1cVty3KLONl9byxbwFhbVz/YU1R1QRsZKDNdvVvjhycrb9QAVBfPZrUUNvRlyIZQ0J2GkbWaEgLugBVUBea/T3HCac6go1e6xUpk/e8+DDC8u3ZjDUSzbqQcx9X8Nenw93aAM7+C05IOp9l7YHquR02PStELKJhNOomjzVGQ59x/arsPz0+wTokjDCJOuSnA8m1sQCKJLx1r8NTy5gYA2RqWyTujUWmD7Hm8UJ70Bnw8JAxdZwWLBtmszs45Ec0WtqWHsco2V9sUkRDFR66/adOSDHrKO3FiMT2/xPZ4ZECetd8FKG26zKc8hJjmE7SkrsJGSVBn+1efRulxCz3M33yL/XtcM2sc7hP0o2XxPQZhvlkzNYhazmMUsZjELHY+yZwqzZGoWFz0qDYAYO0UOQUasuWbiUNO5adtiGh3H/RB5LKEOYqflScoVGMcvsZUDlY6Fb1h/wNil27Ki4NUDVKjRtj9mD7tSs4rSomK9UMN1HCFXcIHl+Xxc2pGlYcRN26Wmhsscv4RSXe48K/PytfXdNex90fPk+695tmTQwIAZ8hwiU5UW20ZOO2eXqiPjqV24NoOO2P6GwoQdsihmqIZYjgAAqrRHMcLTiqHW0ZpYA2W54/ge73BFUGdolmxEiixnOK53zwnewc5dI81LneU1XWUzjIxtBS8K2+bKWJEVXCn0Apd1mEi80jQJFkGdx05MSOQ1ZqjGymIWCE37Z9mygipEjb0NzF0l4Q8rqKMgvSJ1Xl6ryVXO9KzemVM1II1Shmrqe+pcoUGeaViUqnhJyt/LKeumcfLYc4Myw6aW48KtqmqSmtuluofqrir/TNXOPM6QqGvLFdLA55/d+oCrMaIpK1DBaoieauoONzo8V+xaU7P8XAW5G+bDtu9xpYwqNX67AUc1E9vtZeR9eY9R0/tos2tUNDSsW2Q5msTsI2jP97SJ7iTi35Nv3mizi8FJeQ3dylE0DsX8PkCK+posSpqnTsVn+JCNnYWtG63zFDv4WcKeqk5x47mCap2yy7Cq7Xvat06RNgAgVQy8cWebCRa1taUpAVxAVjpNgc+k11NH6E1VbAE5H4jd7GU5Q/R0X5O2HSAtXnYkDXnGTOoi62lSUBQyDE7rXTEZ83eIOn2eq3T/+M0Kj306nkC4SteL2H7rZ5j9TNA6ANT3zqF5pYRb3TX5bxif60Y5iydSzJKp73DkXoBCJThWMtGigkY/DzNTDPFAJ/AZRnCDMsME9HCf9IZc6qZ+DQCsjswLJuSiTGwf0yeKQhhmoW5Q1guNSsByI3mxa03ubyK4Ix6Mpsq+QokWyu8gk6X2pXIhX/muazRtH7K0DmDaq45ZVjXYhkgpAGRJDOS6b4EWcDfwWfqAehRS48GVJynDK8QiE7ZgSGXSnyDcVIwope47d8kcmocULbvd0HBVnrFyNcFdtquFG4XrMJR5/K8+K7//lftZ/gFCK7fTAz8Jx3z+WZJxEto8tKwX3VWlEJ1n/ABgRigAi5LQiQH75Bnyie7HiRTMR4nI4rV7+LiW4/LDkxPRPNPm2/1wKuEDJBxJjMNKO2B5hmISMTxinmNlUc9Vet9ok6Q07kFdQT2UuNLYAoDfKqMSGjBvLs/B8nQaQA+sqNPnOZmEY5RVQkfemM7SGgKVDA2On2b4MjA8M7mnqlVjAVvHL7EshP5OLQ27up72F6Rz6g0xXJdJKsFPcuxSlFWPjb+qjZKZRZjn8FQCRCr0zUNdDDfuAgBsfu04Q9fUW1VxXIY0RaXGzNciTRiSTh+UczPrbrIYr91o8/vMninLJ+eFKjOBS8oLz5RAcMolOHUF8fqB9lVU37Xc1j2gZrBDQbPKa1CpWePevKQ/QqTGg+aBW9fXSBh9mQSNZ3HGELLjOzwP8vH0dePvKHa2GHAYDFs38HmtzTblfTTqhHwNJr3BlIsB/Y7Wm/J8BS3lf9j+3h9Avlf6KqYKRs+7nW99Ho9xmCKrF/r+p1rMkqlZzGIWs5jFLGbBMWtAP/+YJVPf4bCyBBZ55KXRFBuEyu7uvGwytWzBliJ5kuqG46pmr1BJu7zYYtHNNIpZSJCqMdVLbN51inKAQu2cfWIQGpUa2/cYRigtznOJu39UHjNc3+Id6Nzl+zQUIwwhwnKJz5UqWUk4RkVVz6pGE6hVUjBAniLrKPjytIRcismYNbXs1qKGLEaqejHsMYNPBDXW1Kk42vNsvNUDICspXI1KUi7NE2QDAGmoYIbTI9bCWrxaXo+5K/dz9U04Lu9SJ52z6N4jGUdUzi/vX2H7ExoTADh7t6zODB+8HUvXy+9AYw1ouCzuj7ii5tV8VFclXNa+cj9XF0gotIgjrjyJSg20ry7Miohhr5IbTDFqhm3ubfDxiRGWD3os8shQjRA8H9JRxDo5cUjN+jk8pRnk1gNuALdKPpMesrF8vzCqd9XVlCsw/ePye525e4sbvefGMUNBtIMOlttcvSiyXFckjGb+ZKjglY2zmlXqOnydamo+2e0VnsdxP2QYzvFLKC1O23p4tQrKdC5CIBmN+feAhF9NCyS+BER46IcYKgg5j3MIjxikNlddfDUlhOOyflt46iyIj0sN8qVmDdUVIoCEDBtyc7frwlfrSpEmmDwoGaZpNGGNLrq/inGI0Tdv4zGm5ulzNe0oqFmcCBFercL3tbe0oitbAIsAk05cFid8L6ZhxGNIUV5o8dxxqlWes4BmaPLfWwvac3ASccWKPzsr2Lqm1NAMPRKPtWyb7ykR1LRGXp4hVyKlFgnNCgE7JXHYAI1zzmX7yIPon1T39ZpAsKK01dRa5Lc19O1f9xwka9cDAMYQ8AqyO5q2OprFEzNmydR3Oiwx/ZBTdHBRTrn3iErpcDwITzOA6OEa98OHlCGgknOpWWUYgqIYh8zygmdz4kZJldMbasp9s8rK15YfYLIpMX7qBzp7X4fhk0lviJWb1WEVq89vN3Q/RqXO3mZ+rBWS2SR1u4NCqS6TeSygFc6HJ05xEunHESswUyIxOHKM+7Pq+1eYzWSKmJ7LlAOmJRuotyIOY6byu1UXc4fkQ3T+mkPy+7XneAzzNEGqoMbekXVOAKorMikJVhdkwgWge9cDOPNNmWyR8bRbdXks4kHIHonCMJ4mT7fq6oKWZGjOMSOLIj27xYmIpFirOaUeEFOU9jxjavfg+Gn+vLlrpHdfaf9lfNy83+FeFe5/CarfdhdaZDlDhsHy3LQpMvVMEZRjC4aAw1MdnTQoht64GzF86Dc7+uFd0UbKeSb7xtKRZsXFfc3kpGRKKl+TUbfP9w3NndZVNvcElhdb3P9EPWWATuK8eoVNm+NByD08RIMXtdYUBEywJl2jUSc0DMgFymUlLmtbWjpEJbFWSbNho842i3VW1CbLsgXmLt+rzivgvjJaS3gOAMhOH+fNle26O/wLRaONkrpvs0GPr32hhGjTaMLrjhkk2ltebMHbtZePxazPNNY9jnTtDbgsT1LEpxRrTt2L/lxDQ8tCMOSdRhMeZ/oskzGZdTcNKRYSDrZhq3nk+g7DbMyqdlwIZaRsitoWcaQ3IQT9OZ7e9AJIFRuP4PLtk31eQ0r1Eie1dP8G11wPXP7dAIBhqcXQtC2AXHkhUo/oxQxzvbmw92cP/6InWcySqVnMYhazmMUsZsExU0A//5glU9/hyP06ipISpHQzw/sphqV0XSwFh1iez2w8sxqQhNGUTQwg/faoadarVeDV5O6J2Vr3HUND7UDtpTVtYUEwh+8xS6q6usAsJ6Qx8owaOUmrRbBNSBZnLN5HsFYep9qLzvjuRZ4b1S1Z7WrccwJ7vrcn3792WGskqd1fde8q/yz8Cu9s076qXK1v8djU969MaRiZ7EYAKGp6N5x6LgRBIrFuRA0W5RiU52uo7ZnW1xJBnWHZ9NQprhJ07niQF5P6PlmJcVf2MYwQD0YYkl9dR163Vr3JlUSvFsCpq6rIYdW0Xg74s8xGWcvzmVTAjc1pzA3uUaePNlUlCKIwqhDFaIB0S0I9RZZj8TqptVO59Ap+D1W+iiRhokOhKonuOVU+qh6Q4GapXkJTNdXWLj2sbUDyHDlVQEifK8+4UjLpDdiXLYn0Z5gijlRRIGahE/hcyTH/Loyqo7Z9SZEoKNJ2HfZPCzd1had5uaxA2uUKX5vYaHimcHwPlq9thwjmoveIcsBN20UcIu/LOU8srqgb8fcKFgP2QpTjoMQ8VTW4ND/HxJI0ivm+p+9V3b82xbJlOyU1Z/I8M6oqLipLstoqK6tyftG6IVwHZaVj5a7sg6eqScQAjDdOsljoqBOidVBWgQmmdncfYpakeR8WeQ6Qzh2RSRyXK7fpKNK+o4poEay0GbI/VxiTq7cGC7FIiSma8N/LijFMGmqArFIxOYbgvEoNhaPgPyEANf2KJOF2gsKw0SGWYdwbYnBcknKINNE60GKos7q6wExo8jwUfgBr84j8jvVFZHU5hjE8xMQQdeT3KnzNvp7FEy9mydR3OArHQ6HKqVaWaAkAS+ibWy08+WjAPlBm5m/ZgvsG/LZ6MHUGGKzLRbHIc04E6H2jUx1+8DQdl29uU0CUStHu6kF+4GVb6wzFEJOtsthimK66uoDqHrkgaNbSiOnDbsmf6p2gqO+WC0Ww0uaeqmIcsu8WG6rGkVY9zzIgIu869eANdY+EJYQWJxU2J3ScDCapNoP2PX4fJZ62IT+RhhH3zXCPzm7IxRaS2k39T+NuhF03qgTi0D75HtfjB1rU2eYEYeV6OVa7n3MtSxsgTXTipB68xajPSRT1KAGKPUlyFxUN5dCDfPvIOvL4qwCA9jWq72dB92Tl0YiVyFtXHeYHsenZVlA/Whzt8F+L+6Mps1qCUl3D5Ld2ufSKc3cf5Dmdh/0pgVlAqo9T8hD3R0xhJ2/A6mIF1V1yHlSW28x0M3vRuHfQtvl62q7D19kUAqXeuCxJeRNCvUvencf5+F57Tqu8B2XeLBBT07IF90zlWc59W/Qey/MBBdXk4QCjk7IPcPuofPDGwxj13fJ7zV+1xg//wfHTDAXS/PZXXNiCGI+nkcdaMV59QV4vUGvynCPm5Oj4CYa5LVswPGkqlNNnbR9ZR+9euUGo71tBsGuRP4OiqtaIJDyOk/8ok4LOnTI533XLaTSuuVq+pdbUDNMs4znLzOA44vve9j29CSHh01ZzSpyTroFlC2ZK0hpBrwFkkkgMUupj8gKdDFfagYZjjfdPsalt7b3HfyaXhGGPN3LxQIsQuwHJISQs/hr3Q8RfuAMAWGbFq7pssFxZaPLaWT58HYpdkqWbV2XCG9rTPWqPZwghHtJx4Xze/1SLWTI1i1nMYhazmMUsOGYw3/nHLJn6Dod76k6IRcV+K3KpNfUtwnJc7S9niym2nK92XSk7r9sYq0rJ5tc3uFGUIII8Thli8+oVBKraRCVr2/e4KgRo6wurUkf1+mfK3yldmv7Xb2fGVKlVg620evi960e0xUSeM/MI0LvFgDwD15YMLSyfK0vMHBqH7CeGOGJ/PYKtLCH4XMZbXdgNufuXpX8tDgmopnOhmWDE0hIG28kU36RKBAnzRZ0+V0WGx09zdWDlhlWsfPf1PF4AMDl6F0MiWZyhquDD/km5S974p29g9dlPAwB4q3uxI/KMG0ItofWvskFP24P4PX4tVRWzKGbtMYqFmwK+RnZQn/IWS0/JSgQthsLzedwSowrlcBVDQ8xCCB6P8rLc7Zf3H2CbDpTrwMRoOqfroRr3Tcsfx/fYEzALVBNyq8wQUn3fCs/PwtDUyuOhGoKHb4ClalSR5ezdR2HZFt9LHgBnTsEzkzFXbqhqNOlPmDVXata4QZygWgihvfG6mxic2OT3AUDrQBPLN8lG/8rKEsKTG2psJ9pex4BTyccvDSNm71JF8FyGHZMP1FiVAcTdHoBpNiuAHTpPXj3gqsqZ24+wZU2ppYREheDrJW2miFEo/x6sak9Dy/G0F2YSIyfLHGoraC1yxbri+XDUXOaHshBcmZ2c3eYKpmULlNXaRM31lm1rEWEhuEpqsvqcsoL+FlsorSr/TwWH5/2zEGpOifocV6YKtwyhin4m1MjzoTvkSqG+P2JsH5ffxQtchnPZO3CstQPTKMbpL8rK1fj/+0dmHNKcty85iIsVs2Tq/OMRJVPXX3/9eR3Usiz85V/+JVZXVx/+xU/x+NIb/yOe9i9lclJ/xi1cajZvVhaNy3OG+YTjstyAJQQcpaLu5foBQYtf/2Qf64oRVd8jF6FKu8y9AoPjmwZV14AmHF3e5sTKKbGAJjHoADDM4S0salhSJSKWECyyl44ncNWi6FR8hhZocRS2QG0vqbQHQE1+bq56ToSwGQ7IxyEvsATB5UnKPTrVy65gNl8ehZw00OLl1Sqo7pevddcO64cz9UFtrvN3AMCihBST3oB70PIkRWOvTFSbh/fww4si6mxzj0wapfBVotC6RD6kF552GOUr5H029V5KOMYhJ7RFkqAgn8AoZujNqSjow5l+KBKk0L2/pz5/guXvVqKJy2saFkpjhlDJ0zCPh3ztSvNz8M+BZ9LhcEqkkpJjd1mN6659QKUp/2hZPM+KNOYesqSvx5ggmSzRTE+SpKgstBAYHnckN8BQkUFTz6IYqeHdVxhsMUAmS/Sw8uq6p7ChHrilVhWV1RX+LIY9tzs7WJ9RN2L4sNSsTbH4KOhemawfR6IgqsVr5RjNX3NQe+hFWvh00o9ZYoLm92Rzix/epVaV5QzIw8/yA+3vmWXaJNdYT+iec7McqdrkTHpD3aekkiHb91j6I+psc/J47nEA6f8ZHDggj7uyT33/JhslwxLMiks3HtAyBCr5s5fX4Ci3g/TB+zHakBsAWsMqyxNOiiLDbw/QPVM1w3uTNhtFlhsGzMq7z7NRUclzfd+KhJ8Bhi+Tk0eQKUFiu7XIEjKW5++YR4BO5uNBiHFHrmNejTaHC2gelOeXJSkGx7fUz/I9wVIwxX4kqRg38NG5U7oj3PmnXwQAdHt/t+OzZ/HEiUeUTN122214y1vegmq1+rCvLYoC//k//2dMJjNtjFnMYhazmMUs/rmFZT1K0U5rVpn6lvG2t70Ni4uLD/9CAL/5m795wSf0VIuz93Tx1d/9NADgkvUzWH6OrFKJWou1ZbgZUtga5gvqZBsny+eCICAlRteqobIidzzBZoiz98oKClUnsjiDr3ZncbjJMAVVdbxaAEGlcsfVTBqhm3mpRO/VA+3MHvZ5F8wQQ1CHZ+hJJUO5Q3Sr2l4kXJc7tvFml6GHdsmHq3auVD3JtjvIuvK1+aCLWGnekLZPbW0JjQO71edqwT2zWkM7fzfwuRpltxZRlBRUQo2ewkY6Inf3PkMtVKFyKz4S9fcsmsD2daWQRQkTs1FbVS/qJYbh5m+S1Sjv0huQ+6oqaQlt2aHCymI4RqWjMCow51oAuVWbmVFu4DO0MDomqxtn7jwFvy2bhZuGFVA2mUyx4QApkMhQq8HIosZ/J8+4CjDa7OpKgqoGVKKQ547lVxiizbqbzIgiLSTb95hJ5vges6CoEhOe6vA1WPQ9LR6pqmXwtL+cGOlKTJakO76XF7iorcrxrK0tMcOTPguAJjpEIc/pIuyzVhBrq/UnXGksNavwVtT8o8pZHCFTjElLCKx+n7zH+Z4yrFySXo89JIssRx7L86ZxdXwP5cWmOu+9PH9NeyiKIokfspKiIVyHf86iyRTECsjKrUnmIMHUSV95U5Y1pDg4cZqZbHOXS5jSP3i5rExCQmRMqjDIB1T1KWrzKBSTWVRqXIXqdiQ0Pji+yeQaNyiz0KXwnB3wpCgHsLyMx5PmDOtR1QKGo932PFfyaO20PJ99E5POGXjq2tjtFa6k8XxI4h1zCwBX/cvtOldrx51tDE+eUdfAUv8Khsnp+9DYty+X88hvyrHI7zoNnNjxUY9LPNlgvouBrj2iZOro0aNYWFh4+BequOOOO7Br165H/Pqncuz57lW4I3kzbh/dhON/BQDQumyvhgkeKpkSQtOLk3hK0RqQpW5SQG+sDTDZVp5kPVVqH6fIlJhiEqVMQ4/VQllebHL5ubG0Z+rhzj0qMSUa2/yACVYXWPCOkqkiyyAUxBafGiFUcJfteztUk8PNAYqjster1KyiRj5iBqRDpszdux5g6IEW3/q+FTiqbG832rxoF2nMY0OQ4uhUhxdlZ/chwCG2kFKZ73e0mGOSchJFytvSfFiLlRKcMDp1dsdDLItihk8cv8Q/m35n1C9nGUbEhUrsCscDVLJltxZZrkCMImTKj47U8dPxhOUC8izn/hCi3NdWqvwAmpzdNrwK9YOBksTB8S32Ily87hBqhxUkYsxJx1Ad7x1RqviqH28BQIVYqZnu+xL1NkAMTZJe6J3l60i9fQAwUn07SRjx9Rid6qBG9HK6D6B7/oosRzqmhHPC4o8k4RGszKFJqv7zc5ycEhQ0OL7JsGy5XWcYMM8yfviZxyRx1spyeydbVdhw98i+Me+w9qVLz8h5nnfXeYORhGOj71EgWFIq6srvLgnHsPvKHHwp0cw6WhfM3qQs0z6VfL10xUG4DidLRZazPIRmpPm82UnCMcbq7yQt4PoOartVb1y7MWXoC0AZKat5WrORGgr95IGItn5YiVFPvj+O4LXlfUn9Qp1vHkX3PrmJKrd8LFwnZSuqlxxi42keizxjGBEAQ2ck7hr3hjw/B/ccQY3WTNVzlUejKU/M7JhM6ErhgNchHk9DesEJyvDV/UMsx9pB3f842uzCb8m50Tq8m8+NpDZGWz1mwZkQKvXDtS+ZB/4es7iAuBjo2iNKpvbufYiG2G8Te/bsOa/Xz2IWs5jFLGYxiydGPNkqU8Djj65dEJsviiLcfvvt2NzcZL0Nihe96EUXcsinbNTXFtGak5WONIy40tK5/Qj7lJH+kOV6KMw30+4oz9mriioLeZJyybjcbqC+Z9rrStiC4R/LFhidkbttggFLrYCrELahS0SiovKEVaNsd8i7aae9DGtuhc9Lnvemrnj0R+geUTvyOENtd1N+hq/ZVNvKy8qrr3PliHf7ecYN6JYtuHTPQoH7LudmXjglQOl2Fd1NjLeUDUZI1bcWay5ZbgnIlIaSghEnp04xC9KraeFGqvrYvgfPqDbRd4wHIVc4CqMplsr99P+A4YPmlmQlAUAxGbFODsOU5UA3bwubiQpuPeLfU4Upi+Kp6htVUGq7FMtqWTe4jzvbuvoWaY0xgnS69/fYDqaxf4iqIRgKSGiQFk6/XUew3FTnQvCnrggCGioUnq+hEnU9nXoDjqFLSI3ltDM39cwAw9+NoJc04TmXxcmUJpYbyPlF8Grj4CrDbBA2wzq5AXXRNUrHMVe5pDaT/D1pXuVxpj0HHY8FcGluFY6GR600YpFU+sx4e6BtYwzIqDJfZr0lqq70jqxj4/P3AZDXdvnmZOqzpoR9bRvFOVpeyHMNZ9k5V0Bs30ORKValqk6nhv9hebHFc4oYqJN+zGNQXmwyVErHFH5F60mZBJBxyLCm09/ia8BkjzRhFmx1rxrDPIe4T41blDCjdtIb6oZ6VSG1hOCG/bN3neCqO2l51daW+LWlVo2JNlQhjdYfxFC1HRRZzuLFeZbBVXp5wrDnovWg3K6juioZwcHabr4etJ6UmlVe022lWZX2t5EraDvph3r+lT1eE3N1H1juBT2uLyiELbSY6QW+/4kUFwNdO++r8/GPfxyveMUrcObMmR1/sywL2SOgJM9CR3X3IsqKlZcYpd1Jb4Dhurw8LUW1thttvvGlma16WBiMKuodKvJcK0B7DuPu1OeRjlMWjnR9h6EgCtsvcX+AZduaHuyVubmQS+GjMd/4otHmh4cVafaPXSrxudA5DB8csnBi84Ay+2yV2YvtxD8cw/YxudAsXisVvWtrS7x41vevcImfHoz2OQwiRHLxoz4rAFhQKt/lA5do2r4lUIxU35da6LM4mWI2UXDSEifMdvKaVVABOer5/OAhYcaoG6FUl9BCbXeLe9OoZyQXDixKEo3eJHrA5Fs9QwQVU/AOw66kBh/FGJNHWDdkNXKirleW56bkIdjDbhBx4pWO5d8d35mSDciNHitA0uvpWGkU8wOVJS9WF/jaiPocJ48AmDHFcPHGaU7K3aAMl4yClcdj46DD39H2PS0JoSCdYhLxpsL2XH7g2a7DsGHzEgkvObsPsshptt3RiRePRQhBiUCWGclhAtt3p76j7Tpa7bzRhrMor21OPXhFrvuv0oR7xUjsMY0mLJ5p2YKPW1tbQvXgfvl7de3DUx328SuyDhoH5XWuqodzEYVajsAPtFQCJZxJzOuGmbg5fomvM/kfZpHuuRK24LkRD/UcoHt5vNnjpKNiQLTMLEyTqaSaTblpPhktDFPtDGpc/HYD9UyfCyevtsDwpLy3zxyRfYDpOGG2XOeuDo6vy3Vo4S75mQdfILB8o1T495ZWNIOazME9h1m68SBC67CCg9eWDJV2vXGhKC+0eJ0glnHW7fL94QZlFsjV46OZplmSIh0rpnKSwlJzjhK/8nwTs7iwuBjo2nmnj6973evw4z/+49jY2ECe51P/zRKpWcxiFrOYxSz+eYclpIzJhf9nPfyHPMEiDEN85jOfueD3n3dlanNzE29+85uxtLR0wR86Cx3+rhUIVX1IOzHvzE2dHQorqEvtJSjdJLXTs+xt3jlTRaTIcoYjTCiWNHvSccrVh8TYaRIrSRhCg4XROFwY0Bm/Z67B8ImzuAcZeQpauimWPbhMT8EoZR0d2iW7gY/GXlkx6N7fw32fl6X9L/y9pLHsb5exdLUs19b3zmHusn0AgAoxxjxfsuEACUmS/2CjjeAAaRypKkGeM/RgBXXtt6WivDA3tQOla2NCWMT2Ky+0NOQX+Dz2BKGR1hMALN14Bco3/QAAMIPPisey8RzKvoIsbdRONj19XJ+r4041wNJnEAkgjSYMTxZ5Aa91jlecrVmK2TneellMu2QFWYYJV0K86gYzyaghO4tiPkYepzxGVBUq8lx7CTruVIWGYR1qAPYcWArSyOIEtjquMycrHaWlNa27NewxDEhN1nma8M7f83y4CjKPDIFbEmY0q7wwtKOosmCFY4ZXiixHFsmfx90IXlXZ3JB1Tr1iwHwuiokSMZ0aWLKT6bNFEFU4bddlwVjL9eAGm/z3TF1z+l7CdVDfIz+rutpGsCarJtQ8nXW3kHQkauBUq1qzjGyoSrkmqxjX3vY9roBwq0Ce8zwab3UZ3qMIlips9WPZgsVKiZ1ZpAny/ll+vVmFonNgLTrbBtTaZpnsPFWBdasBGlXt50frUT4OWUSUwrLFVMWIbIlo7SuynMdebJ0GIDWtTOiOxmLc0cKmlhAM4WZnFRFis8tN+m69wlUoateI+yMmLBRZrmFT1Z5QZBpqdXyP/SIBzT6s7ZFrWzr/yGGqRxtPxp6ph4v77rsPz33ucy+4KHTeydS//Jf/Ep/+9Kdx8ODFU2N9MocIGhCxvtnoxk3HCTM7uGx/bv8DHcN1+ObPWIIg4gdbnqSIB+q4EYnZFbzIAJrl5FX14sgPqzThfh4UBTPNqE9j7rqM2Tl5KQAstSuhBCzPWLU5GUUQatdCCzGgTZMriy2GDJMwQWNTjs2iMjxdunqRacWjzT7cilwICWIoopD7qyyD5QUjiZucOqXGYoJgn6L4r+xjVpizIqGVzN9EvvGAfE9vMAWN0e8o4RWuw4tfnqRTytKAVLluXymP67SXkQ/kQ0ZQYppnhoq7g1xBpQSv2q2Ik70iTXRyUPJ1z9SIlJhDTlJtz+bEh5hypnq+7TrMqExCTY8nSAcAi1ua3z1R748HI8Mnzd7xvfNY+x8Kz9dsKGHzz5ka95IfwFXwD7HbAA1xWSVfM9WEDYjpRU94NsNC+TjkPqciy/k7stmz5+uHe55NMdgAeQ3p2uZxwmNgewLltnx4E2yahBEbS9fDMWokCaJYrchzLWXR3ULak9ee/f72Xc7QYDEeIN5SbNU7j/FrqNfG8T20r5SQRfPygwxTk/RHkSbIzsjjT3obKKsNkWMIT3Lymsbssyk8h+cJrRtFpo3IByd7vHZQMldbqXJfmfl9iE1rOZ6GzLc7SHo9AEC40eF7iZOLhRZsum9dFxBKGZ0YwfVMSysMuog78ryizrbeOGQaAqYEpbrSYFPxzfuUl+Jtp7lv0G83+FxIniUdx/y7OEzw4OceACChTLrmKYvmTjgJE44L65yEdMor1Nd9SMzYFDoJ9S7bi3qke/PIC5HGc5g/9Po/iydGnHcy9YEPfAA//uM/jr//+7/H1VdfDdd1p/7+hje84TE7uVnMYhazmMUsZnFx48lYmZqbm/u2f3+0bUrnnUz9yZ/8Cf76r/8a5XIZn/70p2FZGhu1LGuWTF1A2GVVJg582GqXkycpl6/Npt1cMZjyQY/ZTICGXaiRNR7o8nTU2eZGb2pKz5KMqw+O76AyL8+Bdt1FlrPNh5smsokWgJWn3OBtL0jGSrq1jsl9t8vXjkM4ey+f+n5F2GcoKulrZ3W/5XNztNk8TfAKAMxdIiGe1n55I/jtBpfQHT/nXSHtKp3ugJvC7VpTN+AKm6EOr9UEAEyOnsDgHtm0WndcWKtqR61K+TAqgedaVACySZ92lcJ1+PeWELzjpu8VdbZx5vb7AQAP/tNdzKRs7JPwaPPwHrhtCfVMWVj4CsJwXD6vIgqZpWX5ATvNa22cCPGmHMOK7/A8YlZSnPI1MKtUwlhAqfpXZDlDf/Ew4TllNuSbrDn2klOw2KQ3QGmvZiTCUc3secqMRYZXhc3VxGJ7gKi/zecIAK7jsjil3VpEMVGWN4qFZTY4x70hV1XyLDcsXpr8WcW4x+8n4gYLWroOChPOVY3Bk34Mx1eVOMMbs3ePhKHzJEFlTZELWgqWsTVbsBj14a1dAkBa+QAKGlQaY9mgp0VKNwdIQvL8k9ewvNiCO68g9aW1HbZFIgrhBA8CkBAUVVAaJH7bWtSV7kmk4U3XQU7N08acHZ/Rmlrzl8rPIjHgPE4QdZS2WRTzOsUsSehG7CKOuII56Q1ZhJRYc7U9S2gcUkw2o2ppkYZUmjDEizTRmm6bPV4Pctb9KsGtkxBsCVXFYt24V1am7j+2jTnFKJ6//nK4pDVXURpp61uIzqqWgKzAYENWtsbdCG3VcE/N+nmWaw2yNIFQ9yURgrIo5jH2ahWGhs37h0gPSTjmv5eWlxm65bGcjHCx4smogD6ZTPBv/s2/wdVXX/2Qfz927Bj+43/8jxd8/PNOpv79v//3+JVf+RX823/7bxmGmsWFRzEJGZrw6gH3XpQXWiz4Zi5OheoxML22RK0FoVj3jnrAWLZgmOOhIoszfvB5gQdX0d9NiQKma+eZZgM5xt/phskznP2GhDny249g4WnyZ4LL8mFPQyZZzga29d2NKVYOoEQL1XnXdjf1Q1CVyuPByFictFwA/b28tMBSDqIcaObSJOKHLSt6C4HBidP8+XXqSyFVadtm02VfCNCIEyTp2mJKENA0W6Ykz4QEKUHxW2UeW5KJ2H7gNPt5ldsN7k0iaYipHh9ha8kEz4etrk1Vfb9xp88PltraIgKlJE7MxyIb6r6YOOUk0bIt2J56uCZaNgOg/qmYH2JmEkkPhiScMNMrS+RoiW8eZYZfJc9gK6FNCMEwG81/UQ5QqPEuAbAU3CWYkeZNPWCoE9Die8GAjZOEExHbd+E2m3ocASmxQWKhYZ+vEyfExs46S1LuIZP/P82edIMyz788Tln1nplsec4CvPbCKieE5LWYbhyd6tfT51KwZAklsfX5JYbURa2pZRcM9XAyZXZOdbiPjmRBKkGd54FV8rVEh+fAitQ9qK5x/2Sf+4xalyzAn2vAjNhgA443ezjzha/JzzguE8tSqzbFXmPfxqDMgqkkWBmubzEDtXl4G9XDl8rxUpsKUakBxrH8ie5fJKkTnfBq+Qy3HrCg6vwemeyNH+hxH2AeR3DVnCCYv5LnGG31+Bh039qe4E0phe3ZnHxOugM4ZQXTGQbqtImRUhHTau3scgEpU9JVSbmw7+F7P1iR/6Zq030xwrJthoAv9P1PtHja056GPXv24JWvfOVD/v1rX/vaxU2m4jjGT/zET8wSqccqLBtWRVWg3C4qSnW8srYHrqqUUCKTjwa6zwNae8nyA92QSQ2dvR4vynF/zA9XU1uKHnzpuG/YG8h/ycoDkFUwJ6YkzdMN6BO56Ipqk6n+20fWsfEPskpVWZbN47W1JW5Qr64u8IOqyHLeVY42dKMqNWcC+iFCD6ZSs8bK7omhy8UVlXIAZ1HpYpXrsBK10G6tszxCYWglTbry57PjY7zYlwxtJ7ZCcVyUzpEgyKKYK25Wd8CN2MIWU/o9cizacJUZdZakrEBOD7NkpNW9h+tnMFIPFurFcXyPNYeqe1enKhLnSiNUV+dZ78YNynqH+RDWIubYOb6nafGqGmW7Aql6NqXjlJtpzd4onntZzgl6zj0jMT8wy2mirV+Ezc3opno31bmLSg3ClXMiUw9OEYUojD44rnoQpb1Sm1KeJwmDymJLW7d46p6JQ75X4u0Bn6MZttEPlBtVXJIZoUjCMVfiMkgFbTOsks/yDenp41MPUEBanpB6vbkJsmwLeS6vB/d8NdrcRA/b1bpvZAReDrgiVlne4mMR4aAI+yioMuW4ep5Guk9ouCHHJRkmqB6Q40WGygB4DuRJwvpdo06Ik/94nxor0kpyMHdIztOlG69AaY/cXMHxeDNor0t18e6dx3HqttPq87exX/X3+eSAAPD8NddAx/e4CkVzLk/SqTlNzyraxLUedBAP5bgMjp+GuyK/L1fWgpruc7It3mhW5itYuEpW42k9S8Ix3/dFnvO9Vl6Q67ioNbVGntnzSpu8NOH7J1jR99fw5BlEPZlYUYXVXntkgpOzeOj4oR/6IfRU395DxdzcHF7xildc8PHPO5l65StfiT/7sz/DL/3SL13wh85iFrOYxSxmMYsnZjwZe6YeLmfZs2cPPvShD13w8c87mcqyDO95z3vw13/917jmmmt2NKC/973vveCTeSpGdPI4qrtlxcFdWEL5CllVsee1+ip5xcE0NHZ0ZUqUA81yUnEu3k2inIT1Z3HGLJfc+DuJG9bWllgssYhC5L0t9bklFLY2PwUUnVv1+1SNag3tqBoHV+Hu031UBFVm3S1k6jV9ZZK6fayPkmLu+S2f2S8l5WlValU1ay7WfWWsePzl29FSx/cOXwfL7JFREGiqVIxNWYCoN+bzLu1XDCc/0KbNnjZFLqkdcO+eE+zx5dUqXI4vNWtTLCf58TZXo9IonhJXBaQUBf8dMbPKKIYb2xhuyPObH4zQukyxCMsBsy4JojI/3xI2VzYJxrBclz3EALC3XmpUm0jQ1VQyLvJiSlSQ3ku7eNuzYbvT826yPeF+turqg7z7F9Umw63C6GvjKlOtBTuQYzvZlFT/YuMkXIIGHVe/tq6hUOopdPwSRptKOPV4j9lwNcWMKuKIew6TcMzXg8bdDTQUa3UE3x+O73BfC70nHoyYGev4uneOwvJ87v0pxiGGJ06p8dTq+N/q4UNVEaqaikpd9wFmupcRSo4EtstQqDu/hMAwGAckS9IVHfUeYaihC67y0rX3Wz7fd2bvD13vNBxrNqttcd8lxejMCOGmPKbte9wjlo9DJKqHjGU9+hPcfVzet/aJPspt+blrC6oak2da8T5NWASY+iPN80rC8RTMxEbHqjLV2Fvn6xl1+mxCzWH4TZbqJa7WLl67G8v/4gXyJftl342VJshPPyDHY2tdMyUVa1TUWtMG4ees03kcIVPzOI9T/g5uUGKYmsZ4/GAHFyuejMnU4x3nnUx9/etfx3XXXQcA+MY3vjH1N7MZfRaPLPzda3DXZPnbnlvmnqSiKGDF5zTo5rmmibvB1E1K0BVBF1OLn+8ytZsd4YOI+2Pqu+vY931ycWg87WnyPa1FVpPOOqeQduQDwC0HsGqkXSPP1fIrfF5ZkvDiZUM305tBMEg2Hulep3m5+CRhwglfqRVMabwAsk/KXdkHQJbQfbUQ+fd/EwBw8lNfwfYR2YC7ezSGf/gqNS4DVpymh8akN2RYc+7wLt3IrRbtNAqnYVWSEyjrfiFq0B2fGXFvkG+YvtJ3F54Dz9MPRtNIFZA9J9SLlY6TKRsaQD5USW26c+dJ/nvj4OqO/izhOsiRquNu8fUgaMJutHWzu+8hVtpkkS20TpStoJwsNyQ0XDhlUqSWSZFXDxCr72omp6a0grbFSLXmlBCsw6RJAg4sJXdgbg7onIbrW/AU/BmsLjDd3+aEWfDDymvUUFYP99FdHfSPyod3+TL54BSGGbFwHdYKomtoPkxKrZrWYMpz/n1q9MNRb1H7yv0o7b9MHlclNYXtMcyYtztI7z0OAOjdc1KNZY3tkEqtmk5UfYdhNCJNmHIf0j5HrQ2kIyUE9+XY7RWGpqWekjxXSmDk9w749yQxQHBYdbU9ldQLg+IPyLlLczIOE9RWdJM8AHhBlzc+dnuF16uiu4XRurwe1COUxRkWSnIMv9GfYOMr8u97vl/13i3Vkaoet2zQ4wTcqfhazuOcdebcIHjW9R2e05PeAINjcr2gtCxPtRWRsC3DhmaRldtFR86jfOkgsO9a+X2X9gHKrJnC8nxOdAuzKZvkZdJoqu3A1NsjMhI1uGP527PRZnH+Ua/Xcdttt+HAgQOP+ljnnT5+6lOf+pb//b//9/8e9Qk9mnjnO98Jy7Km/lteXua/F0WBd77zndi1axfK5TK+53u+B9/85jenjjGZTPD6178e8/PzCIIAL3rRi3Dy5Mmp13S7Xbz85S9Ho9FAo9HAy1/+8m+Lxc5iFrOYxSxm8c8lHp36+aNjAl7MKIri4V/0COPiOSdepLjyyivxN3/zN/z/tlHufc973oP3vve9+KM/+iMcPnwY73rXu/D93//9uPvuu1Gryd3HG9/4RnzsYx/DRz7yEbTbbbzlLW/BD//wD+PLX/4yH+ulL30pTp48iY9//OMAgJ/7uZ/Dy1/+cnzsYx877/PNh9v6f4ocVqoE85LJjgZbEy4AgIIqPNsdJGrnSbvONIqndjkUtOManRlxtap9WZurMsQ0gtBMtmISITstd9PxqA+b2EQVXWLnc8p0EyaVqYfrW3Ca6/wdmBKf5bzbZT+yLOdKhm3IDdBut7T/UrhrkulTCAfFtoQHzZt3rJg6Z+86hpbRkExMNKp2CSEwd7lkTNb27tK0+ZyqI1pBHcKeam4GZPWC2D2DjSErV1PVBgDSsaK8G5VC4TrMlKHzdgKfr5MJrVFTbRzGiENVhfNsrZpcr3PVw6UG1zTmHXQaneYKCMGu89ccgtfWDexE4446fW6AJXX8LMkZ5nB8h4kJJCholfwpBhxXcwiqbTeY1p+EY2x/6rMAgFNfPcbK+3uedQgAsPS9z2a2XzGJdIO6iiLTitylZgRnQYvCAkAxiqYMomlOOeVt9lpLT8l5zKxCSAiWBVnJVDYTfD2kMjV59o24oVlT2iN4daUyb8BOJHdgZQlfj3w04OowQWgmJGU+iNygpO9d+o4Tw7A8zzTDU/kAFsIGPHm9bMfVY6PeN97qItxQ0HQ90Gw+1+HqmGOQJ2i9yJJ0h3mtrGrJYw0fHLIYL11vr15BoKopdqPN908+DplwcuYOZSren6DWkPf9QRMmJQauKTbq+Vp2AoDlKLFNQ2yU4lzIFVDjqn6OeiNsflXKo5jjQhBudbXN93PcH+HUn/5fALKCDgB7nnc1Gjc9S36WX5nyiQRkCwQLxQZ1WJ6cJ/wIFw4zFsv7tVTFaLO7o6IfbQ93fJfHK2Yw3/nHI0qmXvziF+OP/uiPUK/XH/7FAF72spfhfe97HxYXLz77wHGcqWoURVEU+K3f+i284x3vwItf/GIAwIc//GEsLS3hT/7kT/Cv//W/xvb2Nv7wD/8Q//2//3d83/d9HwDgj//4j7Fnzx78zd/8DV7wghfgzjvvxMc//nF87nOfw0033QQA+IM/+APcfPPNuPvuu3HppZee1/l27zyCmoLbvEPXcE9JMdFGxqwLU9JJUR72WV04vP9+bB+RyQqxd9zA5xK+H/h8Y/Y2qUch5n4MSwi2TSFrmyLLtPt8yWcGUXTiBJL7HgCgHxzeki7hl5o1Q41dWXBsduEGkrXjtxtMl3aq1R0JiqnmLlyHVb1pUc+HPVYPt1wPmYIfmfHiOmya7FZ8foiaDwIqn1dX98BbkewcUWvq3iPS78pzo0dN9+jkbLOTQyiYUNgWU+aTMNoB82VJClBucI5NkDxmyhCT8AyKv3pAACEnON5uF81LJTRcuvzprEVVKMZlvt1hKNUNfIYyz9whE+7RZp9VtEvNKicow/UOJ6KU6ORxhmBRJvALVyxyMsWaV0nCsGkajlkygfrHhOsgPCWvV/fuDfSO6fk3VirtSXQXAJmENp6ukoM0Zhaf2Z9Fc8P2NSOM5kARR8yUy8YjnbTUPT0XN+QYVFyPGaLCcwByC4g1LGtCfhRFlnPCScl5Ok74e8f9EPbxe+Q5qr4gyw+MZChi6IvuTzPGW1obyg18TuK6dz0AAGjXmnAPSOi6aO1CXlbMV7JwSiKISBl2hwMem7ijmJFxyklmZbGFkiF3cO54mya8gIbRKEFJo5hZn6MzY95YVHcpk+vlNn9XCKF1wQZdDbUrmHDSn/DmbmWpitVnKHmTlu6Z4rYGQzPOsm0IZfLst42ePzVuJrOP7vsiy6cgQTZuPtXjY1ISWF5sccI53urCb5FKvBzjra/ey9p+lUsu5fWC+7uikL+3ZZpQk2K9EMxSFLUmSovy/srihBmYlFwPzvQwi8c2fvInf/IR5zUPF48offyLv/gLbG1tod/vP+x/29vb+NjHPobh8OJl0Wbce++92LVrF/bv349/9a/+Fe6/XwolHj16FKdOncLzn/98fm2pVMJznvMc/OM//iMA4Mtf/jKSJJl6za5du3DVVVfxa/7pn/4JjUaDEykAeOYzn4lGo8GveaiYTCY7xmoWs5jFLGYxiydaWMLi6tQF/ffPxOj4d3/3dzE/P/+YtOk8ospUURQ4fPjwo/6wxztuuukm/Lf/9t9w+PBhnD59Gu9617twyy234Jvf/CZOKT+2cw2al5aWcOyYrJqcOnUKnueh1WrteA29/9SpUw9ZcVtcXOTXPFT82q/92kMKgpUNb6g8HGjGVcnXmjy0C3NcbT4cR0iVbtL2kXV075U/k45Ufa/2pxK24N30pC93vaW6h9aBJgBg7vK9cKrTZqFIY2ZGWY5mCJX3u7A3TvLnAsDkq/fwDrTUrPKO3va1gjSV9YssZ4hINNpwqYxPcJdfQlnpSBW5rgJwtcqvaCgyjXk86DNJ7wqQTd2RMiStLLdZp4k8Bae0mqKRLtErqEgENRZbLJKYjYZJEygZRVz1KdVL3OBaalXZB4/CTVLNqAoj3WCudstO2dPmwFnOlThmRp4ZMwNp7vK92pPNr3Jjq27k1lUAMr4GwEy7/okB0rGENhr757kS5gYehsqQedQZ8e923SjHdOWWaxniJWgq3TzJ1dCoG6JQukhU0fBqgWYZ1kuYu0Tp79gWN6mTqGJlpc1zvoCuCBHUmYYRQ2uT3hCuqkY6FYJHbR7DPE6n4Ec6Bo1HqdXjCqntexAKji1spZHkl6ZUqk1xSwqqdsnfu/w6Pkc1T0y4xvFLzBSzle+iaaIddfoMN402h8ysi3ryenr1ClpKDLdo70XhKgHOVFUxkjEspf+WDXtcvWax1XoFlVV5H0yJAUchIEhrS5EPoKulmeltqXw2hyfPoH9S6drZFvt6ckWwWdXrSp7z/ZWFw50m7rbQAqEHmmgp+J3mdJEmuok/7LOifBYaArRG5SxlWNbwaCSYMc54XKnaC8i5DkhmLl37NIwY+o37Izjqvq7tVnMzTtFT66BlC64sUYVKVPQa8lCsviKNp/Tf6DW25/L3oUpivXYRRTsfZd/TE7ln6td//dexb98+/MRP/AQA4NZbb8X//J//E8vLy/i///f/4tprr72g4z6iZOpTn/rUeR94dXX1vN/zaOMHf/AH+eerr74aN998Mw4ePIgPf/jDeOYznwlgJ+OwKIqHZSGe+5qHev3DHeff/bt/hze/+c38//1+H3v27IHXrGJwXEIP1Sxn+MRc6EjgLR+HWvxv8yQzlAYnuwzPED251Kyx+GXKUBFQXZE3ZuvQAkMxUw9+6rtxPG2snGvIz66tMsZPjLAH//Yfcexv71KfX0Z9ryqRq8+3DBFLy9bO6yKo86JCEgeT7nBKFJP6U4jRYpU1ZJKHWmixvFcuvkWeIz4tx2X7yDrGHbnw236JExOXYJTRgL+LGXx+jTazvrLtDtvrDE7I3qjRxlmGOUp1j2EbS+h+A/MhzIryRh+HTnht5Ap2ypNUK6f3iR6doqZsMSrLbRa6RJ7CIraQgiGLOGKYT0IxGY89IPuv6CGYRClWb5b2JrU9i6jvk+NFDyO/Xed+OtFoa2hN9QCNNk5r09pWgFipTw9OdtVnbjM7s7Iyxw/aqLPNUAyrvNeaDH9A2JzsEESbJSmrXedZzr83xRrp+H67wUnL3OFdfO1JZdurV1BZUgmQ56Ok9k8mzEeMsWwy4R43N/C1JIJKUBAlcFVC57cbvCEi2Dju9tg2ZbuzPqXgT2NM96BXq2gbqN4YIJkClaj77QbPz9xkh5FEQjENmzNUpD4zWNsNd4/aGDsu96XlJX9aVBKAcOMpmI8SUYLows0Rz/9dNyxj93Ou5HOkz2R7oDTmTUoaRtyHR3PDDVzeCFbmyzwePKfTmO9Fq+Tzecf9UI+dYjy6tQona8P1LbaDoc/0As1uLrd8FrhtHJLPLK+t3QaKyZgNmuP+CHk8LUNi2YLnQfeeE6iptZbHwHE1A9tYu1i4NUp0b+yoz2vXaLOre89UK4KX/fOo9jzR4/d///fxx3/8xwCAT37yk/jkJz+Jv/qrv8Kf//mf421vexs+8YlPXNBxH1Ey9ZznPOeCDv6djiAIcPXVV+Pee+/Fj/7ojwKQlaWVFd18urm5ydWq5eVlxHGMbrc7VZ3a3NzELbfcwq85ffr0js/a2traUfUyo1QqoVQqfcu/z2IWs5jFLGbxRAhL2HozfYHvf6LGxsYG9uyR1fb/83/+D2699VY8//nPx759+6bad843nnRsPjMmkwnuvPNOPOtZz8L+/fuxvLyMT37yk6yTFccx/u7v/g6//uu/DgC44YYb4LouPvnJT+LWW28FIAf+G9/4Bt7znvcAAG6++WZsb2/jC1/4Am688UYAwOc//3lsb29zwnU+4cwtIVFibOufuQ11VaVqP+Np7MFFjJysuyWF4QD0j25wRWvSjxleoVJ7sNyGv1tBXo6HYE1ZZ3TkZ8WG4bDte7zbpTLzlBBonk1VDEyGGyCrYKTbcuq201wJWX7GAT4XgkeE6xiNpIKFR3knJwRXOkzLEoZX8px3dZbjapsQsmcYhwz7lJq1qSoQCXtSlcFzXON7CdDtnxuiorkSOCziiJl55F1GvmkAUG7XmPVjGw3kFJaYtpgx4ShAVuEyFliMWAyUKlOtA01uGheuw5CjKAd6F63OO9/ucGXJdh3W8CpyNQfCBGeUnUZ1e8IVysrVNyAgKPOEtLGJ+yGSofy+ruNq5pmaA367wZWB0aaPIjutPkNV/3wHgao8mVZCeZyyoKMWd+3znLMcl9mVpWaPx4VMsNP+CEm40+W9vBioY63CW5KbJsvzNXmA7JZcT9t8QDYHA4BNc9vxuCJspYluQk8MMkRCjK95tC7bJ9+/sKorPDRGtaauCvZDdO+TVaoskRXO6mLA5sGlZpWbnyuLTa5sBkrY19m1jysdIg5RKGsnYgFb8Zibn/Owz3OWDXYXViGaEooqbA9Q1XQnGSMzbGYAqQfH1aTONl+n3v16bhJrU3g23190z3n1AHagvTGpWipFNZVtlaq2luqlqXlC90qs7GacShnOLglvWp7P8yRcP8MVyNqayZZV1cw4Q3iadOPkWNV319He3QQg2wKCfQpSNOaDGbavWw3omlPlK4smzFqOemOenzRHKlkOq6LWBaMSyBW3PON5lna3NJEoipnsQWucnT52NP6HDcP/84Lf/wSNVquFEydOYM+ePfj4xz+Od73rXQAkupRlO9eURxpPqmTqrW99K174whdibW0Nm5ubeNe73oV+v49XvvKVsCwLb3zjG/Hud78bl1xyCS655BK8+93vRqVSwUtf+lIAQKPRwKtf/Wq85S1vQbvdxtzcHN761rfi6quvZnbf5Zdfjh/4gR/Az/7sz+L3f//3AUhphB/+4R8+byYfIOnTBHG5Wz4b75Za96FGZW0lwleM+gxXRJ1t7qPI4gxuIBfAxj5ZHSvv3cuq45bjIj0txfGsroQ5Jr3hFOwUqKqZRV50fgUWeWHFkaZYR6FeYM/Kh0IepyxsFw8TdI/2AAB+S4rh+e26Nvt0phMN+m6OojoLx8XotFS8Tg2YjzB4yTJUCZDrcQLBfQeOx4zIyvIcJzjCdaYENIFpqQnLtpERhNWVD7nePSe4Z0v61hFbTxnoejZqalGu71vhB5apaG0ma646L8txubSfhrKXLOoNOAEabXZZDLS1Xz5YF647DFf1TBRG/0ke1Dk5zVQilA963J8lXIcNapnhZAhqVuYrWvTw9HE+L2JBDo+fZu+zucsEHMV8ydXDIOmPWFrBVFCnGHcjuIGcs+XFJjw1p23fYyYkPZjSUaQVzj2fryMp8Xv90IDYRgg3lTSI+j5e4HKCUmQ5Fql35/B1sNoSwikIckkmwFgln2EfRawSToPRmal+o6izPZXo0vxZuVmy6sqHLtOwfJ5NCb0CQFHyUVJdD3NZzvOwc7e8f3rHtrmHp7aa8EPUqwXcr0Oq/VbnlO7pq21pU25XVb2zBJmCv/NBjxP70opyVmi0URAs7JWRk1dhkUMoeQXe7HROIVP3VxJGiJSPJbUUWMLiPr7tY9vsrUfQ3cr1K9j13fIauJU69/EVec4yDGQULlyHN4env3wXj11tj1zPWlcc1NC2EAylAkD/AdU/pa5RqVllWDXqRtyn175cwmVz11wKd/ch/q7UG3quFAcA5HnGcLPZDmEpBmwajjWLdxhjfEZ5LAoNQTcC5b0a1HRSr2By5BlDqePNLp+3V9d9W7RRzMNpz8fHNYTQ432h73+Cxotf/GK89KUvxSWXXIJOp8PtQbfddhsOHTp0wcd9UiVTJ0+exEte8hKcOXMGCwsLeOYzn4nPfe5z2Kv6ad7+9rdjPB7j53/+59HtdnHTTTfhE5/4BGtMAcD73vc+OI6DW2+9FePxGN/7vd+LP/qjP5rSq/of/+N/4A1veAOz/l70ohfhAx/4wMX9srOYxSxmMYtZzOK84n3vex/27duHEydO4D3veQ+qiiSxsbGBn//5n7/g4z6pkqmPfOQj3/bvlmXhne98J975znd+y9f4vo/f/u3fxm//9m9/y9fMzc1xA9tjEcSYqa0tcTOt7bpcIaEdOoTNr3X8Eu/sAd14zpYhpn1DHLE/GzWN+wMtnDfe7Gk4gUrKrQXANXZGBKMlCfK+3FVRlSwehLq5s+pOWYlQiIfQyiomEVeZqBQuANiKgScMaEzDfBlDXEWeGeJ4quKgxgk4pxk4y1hjiFhWbvUUMwMtv8JVCYo8STFcV7DoMGH7HU+xfpqHlhiSMb3c7JrHPn5T0AE1zkcjZIoRNabG6M3ulDZOdaXO3wGQJAIWYa1XmF0pak0Nu9Lx02QHW3Dqe2UFFhryOixdvw++6h8oQl35JI8wEksF5HWmqop53rSzditlrSukonv0LLbukPM4CSeorcn5NekNWJeIxTErPu9oTTsZamI2j50lKc85Zrx1I8QK0vGbZW6+tk8fh1DVBxo3lMq6GTiOWI/JtGOisQhPnTX0vqCrKlc+TZ73imFFcU4DuDpZZKpCWYpC1Nbk/KNrNOpoDbFJb8jH95pVbN12LwBg82tfle+vl7B4nfy8xqG9cHbtk9+R4O4kZgYfhED5gCQXkC+eFL9UrLciZ4g4d8soXEV+UadtpwlXQB3fY2sbspvJktxYr2xm4/XX9fcjLboF1+F7sXHVFRqaVtXgfNDVNj3jhJvRqbLsLK9podU01qw330OiIOXto/IaludrmHS1Rcv8lfK7L/3o/0+OwdyKZjwalT7WlDP8Zi3H1eQbozpN94GpQWZ7NtstUYw3u/yelm1rUVr1vUfHTzA8Ot7q8px2K7oKRmvcuevT4xmWbU+JyV7I+5+o4bou3vrWt+74/Rvf+MZHddwLSqbSNMWnP/1pHDlyBC996UtRq9Xw4IMPol6vc5Y3i0cYQnAik2c5xgpe6R/dQKkly9cNRekvzTX4tSZD7+APXYu553wvALAycBFHfMMCug+C/nWDMi9UWZJqeQa1EOfjBZ3EQTPn8u0O4m4PgGb3mL1NpXqJF9hRR5b1j33ydlTm5eKwcvNVCK6VvWaW5yMfqT4L6vcJB5wAlBebGoJSJXy730GuPLqKiTY0pWQMRg+C3V7hpCYP+yirEjuJExZ5xt/XSmJ+cJBXnXAdBMtNAIAXRkyFp/6w7aOb6N0nE7QkShne2HXzZWgYMAJ9Pl+PVNPCqbfDDcpTbMBkRBIASoYhHDPMULOXWO1cymVMJ1PnKkBzn4cyKXbKDgu2CtfRPTJ5puUu1BjU1pZYbsKuNTnZIBjRFJ40ZTEcQ3V/1Al53AbK0Hp0ZsSK7vU1meBPmcKe0xsHSJFXL9HmwpbqM6JEJx2nWqqiVdNQSzjYIQ5r20ZPiLD5e5nfn5iDJo2/urqA2uUSPrd3yWuce2WQ1xosoaUqMuXvFg00TJ5l3NNXVRsfvx3xZwTLcwiUT5jl+WgodmXvPiXNcttp9E/Ic93z7CEWr9dioBT0XZ1d+9m/0OzjKpQkQ+EFKFzFmhOO9pBTf7eCOptIV5b7U71QgNyEEVMuCiNOasY0/06FGByXsNX8NQenVOcJThYKZhd+BXWCu7a6DOdyr1drAQia8rzisSHaqZOZlOUOYlakT6IUW7c/ID/D+wsAwNxNN+l1YdBFologCKb2GjXthgCdxORJyusu+WhOCfeWteAw3QfxIGQYMk9SNA5qX0RAzrOzd6nPH6fMhA5W56egzIseT+KeqccrzhvYPHbsGK6++mr8yI/8CF772tdia0veLO95z3seMtubxSxmMYtZzGIWs/hW8Wu/9mt4xjOegVqthsXFRfzoj/4o7r777u/0aZ1XnHdl6hd+4Rfw9Kc/HV/72tfQNvy9fuzHfgw/8zM/85ie3FMhkjNbsFNVFYpTQ2Mp0e7ugnR2Et6xRZ0BOveqqoq4H7W9uwCcA49wNcqbatAGpt3WiyznBnGGp7xp3RmqqkzOnOXmZNJXsWzBDfCWbbH2DFVwom7E7K5geQP+brlTc1b2a/sFqhqNRwzDjbZ6O+Aqb8HmKlbv3uOaNUP2DwtzLCzpLK8ZPnuZFukky5w4YsgQ4YCbfCNVDcqimHfGwUqbd6PUlB51trlRPOpGmGzLXevidbqSwRWJNDHEVz046ntX1Q41GYy42jPpDZkxSGH5NltgJOEYZaO6xZ9FYxjFfI4mA47CCzQUkYaR9jwrB1zpI6jW9jVkKfwKQyJsfbPgcJOzW6twwz1pZvntxpS1Dul+5XmB5l4J27VU5YshOApD8wyYhl/cwOfjjjd1xZCgJq9WgUNQSZ7xeecEN3u+Ye3hsrBiqbnN4zKhKliYsM5T4+Aqi75yNarI+edCOAz1WcwwHWgoKU3glFX1Tv2bxymPV6lV0/dEru/L5iFZYUrHKVeDHvjbe7hitXDNPjmWV10Cj4gn7VUUiq1nZQmfs6VgPnuwCXv7QR4jCmaajUOeD3Z7BVUDWqOgezzPcq40Dvu6ak5K2MLzudUA0BX0qUqkWmNKzRq2viZZfKe/cAcAYLU5B++wqqgBuu0gy/kzCH4vG3Mui1MmjJiWUtwIHo20wGdfe4ayiI2w9bpgaKPxuuQ68GpaD43gOSa52IIh8yLLmRFJxxmubzHE65Qd9iXNohijk/LauIHylcwfAkJ+vEKIR1mZOr86zd/93d/hta99LZ7xjGcgTVO84x3vwPOf/3zccccdCILvYIXuPOK8k6nPfvaz+Id/+Ad4njf1+71792J9ff0xO7GnSmRRDDhK/bvssYChP9fYYXQZ90fsL1VebMJTPmcnP/cgnPLnAQB7f1iVmVcP6oeFbfPkttW/ohzAMdg1U8JyUIkGwWmGD2ASjjmBoXADnxcMYU+QeXKBTcdqIRUW93S59QpDhunWOi+KJAI56Q04EciiCav/En3Z3XOY5SHiwV3YPro5dS7B4cvg7pF9IoVwYCWK1eYH+oGmEqgsiqfGOD3Hnw3QrBy5aMqxIbZV1NnGxhekD1ulXcb+f3E9AKD5vB/isadzNY8FYQN0bQzTZ4J64n6IqDfN3Kl4Dlx3WlX920VqKKhTYkSsI8d3WEojz3P9YBlruYy5y2VC2rz6Cg0dJ4mWK1ALbW5Ayeb/k/wECQ/SuVQWJRy7dMMlqO5VSvTKWy0f9hhqnUp2jN4/m9W1a3y9QmJpCguNvTIpqu9f0b5uaawZdsSMGvR00hJrg2QW56xXEKix8NspyiR74XvMmnRI3LXSQOHy45d7kiiByZNEf76wGebjl7t6vtlBTW8AohCJYo3R/VXdVYNbVerc45QdDTY+fx8ACZFVlo/w8UjENFBz1llY1Q4CwJS/Z/8BmZgRvFlq1liywW83dqhaO74Hvynv6yzOMD6j2MUGg5/6rKxyMN03abg6ADK5oevVOLjKKvBn75PM3iL7DHapTZCzsMqJV21tCdXd6rsZ4xqukyOEwxsiWluRZwzrIo0ZcjPZeiQHAugkK+6P+L4yxWFNkVLBEhj6/qW/Uz8roE2V+yf7DLk39i1NtV5o+QUl4FtcPGmEi62A/vGPf3zq/z/0oQ9hcXERX/7yl/HsZz/7gs/jYsZ5J1N5nj+kFsPJkyenWHGzmMUsZjGLWcxiFucb29uyUDA3N/e4fs5wOER+TsXvQo2PzzuZ+v7v/3781m/9Fj74wQ8CkAy54XCIX/7lX8a/+Bf/4oJO4qkcRZbBIn+2is874yxJMN7sAQDr+LhZDstWcJzraFaNwZ6jxk5L2BA1OREL4UDk01Wuwij3Z2dPIVM+f4WqEE0JHXY3GXJMwmjKcf3ccIMSqJif1/QkJWsZv1nTJWDDWy87Zxcmv4PgcnjSkTtUZ2mNKxXldp2bj6lJ2llYZcjFMphVhVmdoCrdueKZ6lhTYqYkMpmkEGqH6yp1/KizzbvKvd93HWovkF5PuV9n+IRgRNaVUZ9PAoYEaaajaKpxPM927kLpps+TdEdDtTyuAcuqY8VhwjACNcoSUwqQ84gavZPBiNmJtUul5Yi9sMqVxGJkNNEb+l/EmiuynCtHBE9Zhi+kZQuUF+TYVfcsa40kgn/iiMcp2dIuA3QNiixnKDRPUmZB0Q5+/urdWLz+MgCAs3YYoqIqXqOBZusZsC77ACYJsvF0JdBv1pCpZuIiyxnWzJMU6YYUNGWm29Ie2HOq0dsxrgux5gxI1nJdwwpIMeEcjyvCoqK1iIpBTzc8E3tMCIZpvcBl9pcZ7MPZHeDsfXI86Zrvuukg2s94Gp836b6VlwZMOijUZtkJfK4M27UmN7nTGmXZQntL+g5btFRVpb3Z9LWOVEU3dRelKgpbPXpIV8wSbBfjzC1w9Xe4Iefe2fs6sH0J+S1cl8JpynnqLa3sEEnNx+GUzyWtXaTh1Kw3dLXTgMCnmtmV2Gk6itjbz/Y9biegapMI6rrCGfa1Rp5auy0h+LuUFhdYNJnWtSzOUGmXebzZGseEJMm6Zqzh08c9rEfZgG4pZqey4KJ4JE4gRVHgzW9+M777u78bV1111YWfw7eIo0eP4nWvex0+/elPI4oM4oayhLtQ4c7zTqbe97734bnPfS6uuOIKRFGEl770pbj33nsxPz+PP/3TP72gk3gqh2Xb3HMioR55w8T9Eatgk49akRXwW4TPW8xcal8yx4seYfKifA9sglwqNRTG5wGSsk+sHdv0XKOkKk14ccomE35gJqOIF1szaPGy/RL7lHFS4jlT3nwkCyDFQEkIc8zf23xgxh25mJ4O1UKapCjtUgKEvseQHIvd7drgB5NlQC/SHkElAArmEOVAL4SRLutTQpeOtSp5keUMB5hBVP/SrlVWobbDDlJ6eKvkIO72kClfr4dSSM8zbeo82txGohTKSw3dV0Pn79UC7mOC7aLIqB9HJaRxwlBNMoyR53T1Vf+LZzO7srzYnBIrJKVtm8ygTUankfyykrOR1JkGzUxzjyY8bk5Q5vmZhhGahxUj0FAqt9Tn2XnGPnq0qUijmNlSpWaVJQTmb7yWz5nFM8t1fmA75R4nUZSkJeGYr4NlC55H1LtU5PmUUOc47vFr6fuUWvL8gjxj+4xp82wF4aaJhj08H6AxNJioBHUCuj/R7H/k/sY81/eV63A/EMlDWLbhGmALrN5EMgqrPNbU82W3d2nmobAxF0wjC6YxrwmF8vFdB4IS0rxgMdhFpUK/77n7sXDL0wFIZmFRlte2cIzj0mflqfbErDY5CSNHh/7JPk5/TULmWRSzkKxb8Rk+cxfkv5brwXb1tSUXAZp7lcUWXBKfjbUIK/XYJcOQ53V1zxI7UVjlgK+z6eJA7RBZniGPT02Nkd9uwCOoW9iG40GifiXgtwI+L689p87b5kSPEn0rvnjSCI8Vm49sWyh++Zd/+dtKEwHA6173Otx+++347Gc/e+Gf/23iZS97GQDgv/7X/4qlpaWH9eZ9pHHeydSuXbtw22234SMf+Qi+/OUvI89zvPrVr8bLXvYylMuPvKdjFrOYxSxmMYtZPHnjxIkTU7DZw1WlXv/61+Mv//Iv8ZnPfAa7d+9+XM7p9ttvx5e//OULciz5dnHeydRnPvMZ3HLLLXjVq16FV73qVfz7NE3xmc985p9Ns9gTJUqtOoTan03CAUMX4akOoq7cuROU5AbulChcuW02QSrrjZp2rM+V6CfSREMetCseh9rqxHU1k4oqNeOQd9ZmRSaLJlz2FgYcRpUxp+wx6830MCPtqTxOUSi2XJ7lU4xC81/6XGpgnfTlWGx99R7MqR2aJQT7u526TTIE94URll6gyuZLexj2zLY7DMtwZa1U1oacwuYdP33fIowYYrX9ErN+6O/CqLjFpzcgqlJg0a41NXxhCP7R+6yHKOHT2AKyUZxgGWIKVZbbqO9XemMHr4A9v4vf91A2GGxnYwsI7IQECUacdIcMYbm1Cos72m3FDhUOBMEn4YDHjrS6AN34W/gaUpl0hzxGXGWoV1jHabTVZSjQUdp0Vppw9SMZjLiaQ9DKeKvHzcDV1QX4hyUEQFW6ItHvF46LwpFQTFGqchO9oyqFWRRzFdgSgqtUdGXSJOV5noS6GptFMVeDaE6Xj6yjvk9Cf8HulZ3wpWExU+S5Focka51G2/DDCw0Gaj41PwDZ+MzzM88BsjZySa/M1xpIec5WVd6CEuNtL8NW2lNZ0EZhq/kpbD4HIoPkwx43audJalTqdOWYvejijC2lVm6S+lvzz3m2JoPYHkD3nRUDNtksqe8i9BpjuS7PjXK7qr739hSkSeMyXN/iKlJbwe+WH0xVws99T5HlXAVzzIqgOk6p1kRFaWKJRltXfAc9DdkKXdEzRXMJpiO4HDDQAneboVSKxt4G2lfK6qG/ew835iPPAEfpwqk1xLMunsb2Y9WAXq/XH1EPUlEUeP3rX4//9b/+Fz796U9j//79F/zZDxfPeMYzcOLEie98MvXc5z4XGxsbWFxcnPr99vY2nvvc5z4qo8CnZDguclXGjQ2fM0sIVFdUn5HC500F3iLLp3pJevecUMcgMcUyl79rB/eySSgxarLuJkN6ALifgRW7jTKvJWydCBhGxDR9Sn4JTlkplbuO7nMyhB2J/VJkOTNdpL+gKmErenOpXjYWQnuHgnf36FlOrKq753mBHSq6+Nl7HsTCLUoBemmPhi+31jE4JvuY6GFTalZZoRnQon3Ug5PH6dR487VhllcDlRU5xulwiOjInfL7tts8jgQHOE296Jo9OvRAT0PdM+U3tYBnZbGpzrUGW+3qinGIvC/V6y3X1Q9qUpNOUr5e1ZUaPyRItNOruszCSkYRC4OWlpfhLMmyfO7LcbGymHtl8t4mkl6PxwZQfWUKerPyHI6vIKq6FngkSEUMh5zsA5qhNhUkKlurAAr2ZGV538PoPnkNB+tfxZr6fe3GZ8nPD+rIFHsyWT/C30W0dzFcSYmOG0ewDLHZcx++wtNejibDtMjyKcV1ANg+1sdoUyYdi0mKmnoOENyMPOO+tCKOtHq3giRFUNMJfp5PQad0Pp7yZXQWm5y8xoOR3tio95isu+H6FkYKIq3tVxsBP2CYzcpiWInqFRucQXr6OABpuAvIOUlK90l/pHv2Yi1iSfdSuR2wYfbcdVeqc11F4ag5azuw1DwV8RiFIKkGBbEUuZGU5CzmSQy8+p4BG4tHvRECQ26DPP3KC035nn379GZCCJZsoI1XK05YjFQENQ3dlafvWUDBmySImmd6TZwSl1X3X5ZpSQb1uySMEJ1SBuP9kOE9atEIltucOBZ5Dssw+jbPAwBEsbM94HGLiyza+drXvhZ/8id/gr/4i79ArVbDqVMSLm00Go854vVf/st/wWte8xqsr6/jqquugutOj+s111xzQcc972SKmrTOjU6n889GD2IWs5jFLGYxi1l8i7jIOlO/+7u/CwD4nu/5nqnff+hDH8JP/dRPXfh5PERsbW3hyJEjU8iaZVkXrwH9xS9+MX/oT/3UT01hn1mW4fbbb8ctt9xyQSfxVA5RrsAudFmedvxu4PNOjyC0LE4MDaYYUJs7U5OEwqsF/D5RDpgpw7uvOAKoObpzFsUZWelgsblzbga9Y9cMosgo97OoZq3C34EF/wxoIstirjQk4QRD5aWWK6HPYCnlipzjubCy6fOYbE/QPyF3mJWTA7aQoMb8ucO7uHm6cMsayoRm0JjifGYwC0qV4tNwPNXsmxnVGAAoHX4aiz3i6/+Ejc9+RY3BBuafriAoEniEwewbb+6ogmVGNSlYXWBojMayf3QDoy3ZhB8st/n4zupBPj5Vw6r719hTb7TRweCE3LlTZcqMYHkOtSvlsbx9lyGvNOUfSHgyHiNVcHG0cZoFTbkRfH5O+x+mCbxGbWqMsijGHrpyWwABAABJREFURM2tLElYd6rUrDIkQqKIhcH8kUxOOb+oAT0ZjRnmru5uwFdVQdGS/2ZBG46qbKWnjmP8jS8BAPzDV3EViCHBOIJwFLHDaCA3m74JxsuiGKGap5P+hKsKgqFUC70HttW4nGBNJ5esXPKMIeY8z0FbUapG5eGA4egijhhuE34FbqCrjYCs/FKluryyxCxZqi6akHwlaemKcsnQeKJrm2jB1iIzqi4kEhwnPE/HnW2GN0mvrMhy+K2y+t4+31/hA1Jw024vw66p8XZ8De3FI9Z/Y0JDnukxSPRaRvOlvjYP2z3L405rixv42D4mK9HkY7gAGOLHMbNZT31NzuO7Pn0M+6//MgBg7/OuRG2/YgIriFvU57RnqOMCVNUUtoRhAWaHFnGkLZZ6PWYBEnRuuy5rhUW9Mc8jYmBH3YjXmNZlQs/P3OZ5wtfFuYiVqYscxUXU0Prpn/5pXHfddfjTP/3T70wDeqOh+g+KArVabar05nkenvnMZ+Jnf/ZnH5OTeiqFqM/BzrRYJJWizWDhSM8xFnAtG2CasBI9Oc9zZo/lgx6SXAr5Ue8UAH4Ieq0ciXqQUc/LuNPn4wrX5UWNxAsBsGBm/+SAF4fq7nmGbzxVqncD32DtaVgpDuMd1G7z/x8KBsqSnOGV0dkxbEXDXr1R9jjMP/0qiEUp8Fm4vk4eS/50rwmmRTstW/CiRwbQeZYjUKKFTuDDU+V4d16xhjyfe3Tk8V01Lqe4h62uetGsUpkX3XB9i9mH1IciPAe1PfK41f17GJYis+vSIJTMOwDBrkXNtqNkDlr8ssgyCIK77lvH4GR3amxL9RI/kKsH9zO7q0gTiEjNP8Xyyntb/OAYd7Z54a8sST89e2GVH2z5WPf7QPVUpdGE+6fyJGXPPq9WYdh08M375bhsDlhpvLq6wAk6/VvyarxB8GoV9mOkvp/CdlGU9PUe3n1Uvf8u+CrRZJjPcbk3qIiNpEI93O0853stjWKEm/Jc6WEI6AS+VC/xa6PumBOQkunvRszaJOHxYtZeyZd9doBkfJFfpWFYTXBdGo45Aa+uLkxBzgDgVjVD1asHWqmb5qFfRcG9XDn7B+ZxtAPC8upagkO4Dm82yPx71NWJiu2NGP6kdaN21bUMKRZemY9lWQJCPTwLEtDtbu4QVgW0kGZlscnJZ5HnnMzbrgNhy2OcvVfet45/TIuUBmUtJVFR/WFxBqHaCuL+SPeRnsP2BRTMR0lvFHIfam4yGwm+dB1456xZcT9keLTIcoyUsOnGaXlPeEe6cMryPa3L9k4ZozO7Uc1zuzTGxYons9HxsWPH8Jd/+Zc4dOjQY3rcR5xMfehDHwIA7Nu3D29961tnkN4sZjGLWcxiFk/GEOK8obod73+CxvOe9zx87Wtf+84lUxS//Mu//JiewFM+8pyhBcsWU5UZ2pURZGNWTzLD8iSLU9Z4IQ88cnAHVGOjULs25QfmNptcmbLKAWtSETxjuw7GyoMvPB2yhUXr4DIqqtGTPAM7d66jf1JWNGzPxtzlsjJEAo15krKf3+hUB6OOsmcIE2atOYqx6Ld89qcSrmNoVSkdH9tCrna1bsnG7ptlVeXgi78HAFC65lnIyg31xQs+RzjeVFMqjacJi3ClRDWzl+oeV8dsz+H30a6UmsDVibHmVJ4kzMoMVFXH1B+iMaFzAIDaniXUDu2Tn2VAg1SZqu3fA//a75LvDeYgxspDbuMBPh8iEQg/0BUFT49hTB5lns0QWto7C2dJXnurHOhqiTpm2jnF87N56X5mxXFFTAh+j+W4bJNjB0r4MYoR26rZfqAhXsdggOaZrlqONnUVK1DNx8GqrIL57QZigmCjCbNNSd/LSidTzEaq+o02OvDW5Px0msoTrrnAO/9s0NupoTSJpuYGVRRObE/gqarGqqoo1FaqXF2or7VRWlRjZGh0Edkj6fe5+kvzyfY9FsLMs4zvUdv3WPfKDJMUQbDS6JS6vwNfCuOqMaI1hGAr0pWi8WLoedDTkBuNgesYlcCA7w+u1GQFV6biMOHryISZ1uIUS48fsLbL9jssnBqFWlDVZMgZQd/F9j2uTE16Q66K0zUanOxxZaq2tsjnS2tYpR0wM7a80JIWPucEa9Q5LnuBFpMI54rlWratq99BrtmoqtJ/rhgvxVit89tJjnHX0AYjSLHWhFWqqA9R61VyGrN49PHCF74Qb3rTm/D1r38dV1999Y4G9Be96EUXdNwL4lp+9KMfxZ//+Z/j+PHjiOPpXp2vfOUrF3QiT+VgNolhGEz/DxgP3kxoReQo5nK67TmaTaeSjkl/wsKNeZzq/hRW0e3BpYVBGKKF8c7ejEl/gv4JtTiMUzQPtKdem8UZSnW5+NTWlth0mZhZ4fF1FmDMsxz1NQURuQ6SkeqdUAuOVwuY3eIGPn8GsQEtYcEtye84d8kcdj9bMi+8w0+Txy8ZFdPCoKEL7ZvF0MHyHMpLctFNh0NtZDwk/y2HS/TpODakDRRMk0x7vnHyu9DixZ5EKEVQ5wcEjas8ljyn8mJrmkVECZu69vkogrj/m/L8dx/kpEVUNBOM3pONQ34wVhZbaB2UvTudOyX0N3xwyEKGlm1juS7PxzNYZRnLasRwd8sdnOVXWLWbYY480w8+YTP0JtS42+GQv6NjKMqnUcysToJ9J/0JInVepXqJk6jgsFQ1t4RAFknoLh6EmravklohHGDc52tjJkM5PxAVe9Tzp8VnDTkCQEo/0PnFYcJ9Up6wOJlylbGu3/JR3S3PtX3lfu5jMx+G7u6D/B2KTPb29JRMBG1aANkPRw96ACyWGxvG17bBcKW/U4KWb3aRLsrf+e06w6oMYSVjgKC9sP8tZRDoX1bftjVVnvqBvMDVm7hhjNou2QpAYqoiqIFH2BKcFBQALJVkneu/CMh7UTNQtXwFKYl7zSqfY9Tpsz8h9U/Kc9Qeju2ryKRar51Taud9xVjsyuvgrQ709fKrOik2JUiMdgnegIQD7g+k3sKkP2L5CNN5IFZCulVHoL5bwXitRZatKNwyC5o+VGL5uMdFZvNdzHjNa14DAPiVX/mVHX97NA3o512Le//7349XvepVWFxcxFe/+lXceOONaLfbuP/++/GDP/iDF3QSs5jFLGYxi1nM4okR0jHi0f33RI08z7/lf49G2um8K1O/8zu/gw9+8IN4yUtegg9/+MN4+9vfjgMHDuA//If/gLNnzz78AWYxFUWWMYwiXId3L2mUTukdAZjSXDJ1piwheLdIEXXHGHckJOK3R6ynJKC96KgULXf8mlUGTNuE2J7N5xWHMfrHzqqf1Y7LFVi6fh8AYO6qS7gRmjzdhOsw5Of4Hp9L3A9h99UOUokLBmu7uVm2iCNMNtanvrtTdrgKNulPcPauBwAA5YNSZ8ttLE7ZVfB45Tnr8xB0UVpe1npQ45GhnwU1Fhl75zm+p93hydcrCo0KjT4+sTABoJjIylu23eEqQBKOGU6lce4f3UB2p2RBlReb/Fl0XYbrW+gqLbHanntR2SfH224t6AZw2iFHIWvj2L435VYPAPGXHmBm06mvbaJ3n4QPDv5IF6X9UsiOLDIG9xzhedg4qO1aTBaW1tTauYBatuAqge06Uyw/gkJHm0ros6+r3OXFJiprSieKPN3Cvq7WZjlDfk5HCrbahrVHEUdMGCg1a9oaSVXcLM/nKlsR9pltR95p4UaHxRZtV6B1oKnGOENITddKKLM8X8PcZRLa9nbt3aEPVFiCq1TO8hqovTkz7EEITi4vNrmalMepro4N5Hi7gcdjCID/3j+pYN8o5QpsdXUBjoJlqVKQD3p6nhgVTACa+arug3SsbaRMdi/di+XFFixb+d6dDhlmo0pjJc+1jpQlGPKzoEU6C1dBd61FrvLa+SbPe163PF9DglmGtCc98Eab3SmYDJDsSoaTm3N6PVGwcNrdmvo7zY3enfcBADrfPIq5y2UFtHzZNUzQEM0FhvS4orfdYcuoydltrkgRIzjqbDOLNs8KhoMXVHV99+E2Vp/9NACAu3ZYr11CaKsfYro9gROUWVxAMnX8+HGWQCiXyxgM5OR5+ctfjmc+85n4wAc+8Nie4ZM8ivGAHwpRZ5sTFC9wuTepNKeYlHnGZW+3XplaVPkhk+uyPC1ubrBlUNJr/HfqmykMJXJaiItzWClkquyUHUy2lX+ggsOqSxpaG5/eglOWD0nB/UYuH3/SG2pz4SRlhhAlIPbSGguLplvrWmZBLeZ+vcQyCuaiyf0zecoGzsjiKc89NiclU9lqUz9ko53MwmSYcLITLLfhzC1M/R2OB0f19UDYmtm3tY50dA71G2BTWdtzGbah5FUqa8v3WB2dHJuijTSeo1Nn0X9A9mJVFpsMqxKkKBW3DXq5mj807pPeAN37ewCA7cGE58l4qwtvVT081TVIwghn7zrB5zj/9Gniyejkg5yE+u2GZjoa6t6+ITFA38eEqQme8QIXtd1NAMDc5XuZCs49K3kOO5Dz2G9G3E+UGSbS9EC2PB/Vg0qo1oBkuC9HjRMgk/7xadnTFK7Lh3QyGvO9Ul5swSnLv4/OjBEqyHvUUddLCDa/tow+KWTqXOTJ86/pgUzJou25LI6ZRTH3ReZZpj0rh0oN25++LynRJUHLUWeMUl2uC0u+B6GSX1Nhfcrc16Tbc8KpjnnqLMOHTlDmNYQERM31p7ZrzHPqi+/9GwBA839/CYdffKP8+Xk/hHxO+bTZrh4PkoGoNWEb1456OE3ZAdrYmIzg0eaQ/fsWrpRQ69pzr0VwzfXyo1qLvLHIKOmuNaeYi8y0VHMz3DjL9+eeaqDZrl4ZSOScpTmZb3cwOUsm8GOjXYJEO2NeL7NEr7O7Dsr5cuCHrkHpkqvluZQqKAyavqU+i2Qkpubu4x3Wo2xAtx7Fex+HeP/734+f+7mfg+/v3Gg/VPze7/0eXvayl6FW29lP963ivJOp5eVldDod7N27F3v37sXnPvc5XHvttTh69OhF1Yp4skQeDrkPCgBTw4OVNjee82uTlG0vqMkUkPo9tJPjXoF6iRfY7v1d7uFpHCTdJFf3PBm9EfRgTKOYsX6/WYFYlFMlHce8E+Sm271z2my02eRmV47eWf78zKj+ZHHK8gr07+5oguphWR0pYq3BQorgfmvIVijlls+NpqRNk22dhN2a8PvTzXU1eBlruFBfj+W6vECl0UPrB1ECVlqc5+Zru03GvGV+KBTjATLqbXBcZJF+OAJAac7mJnS/tQhHSRd0VTVquL7FiXQlivmBRTvz8mKLr83w5BbGxzfV+zoskdFS1RHL8bTxbjlgiwpX/a6+fwW7nykX6PrJAfe6CNeZ6n8CZALGWmDZg2hfLfun3H2Xy/PKMpz+p68BAHr3nMDclfK13Ofk+TqBOseolYgGplYRKV4XWY7o5IlzXu+xCrxbr+hqqjLOtlxPJ3HtFa5kQNhaxVo9sPOwz++LOtuGmbKcO+WFFmt9pdGE+5qEbSEgKruqVlVXF3iMi0nE5j3cmC9sThpgVHwpYXXVtebf03iFCV9zuj+zOJuSSqGElBK7dJxywmXZwlAV17ZJoqzvT9Z2Gg24Z4jIIuGpDhNZqkFZ9wESoWEw4r7MUr3E40FklK07Owh/99MAgMu2elj8gR8AANjL+7kBnaJwy1M2PFz5UQSO4cktrhRO+mOuYmZJhvlL5fsWn34YAFA+eAnLCQC6yZ2qqlZQ10bdkzFvPNjAul5mI2UrqKPwlI6a4zOhhTZZeZpMkQT491zdS/m+jsOEN2yeaobP45TXoKK1qLWlskQTXSKVXA+3cbHi0UJ1TzSY701vehNe8pKXPOJk6u1vfzue//znP77J1POe9zx87GMfw/XXX49Xv/rVeNOb3oSPfvSj+NKXvsTCnrOYxSxmMYtZzGIWT4QoigLf+73fC8d5ZCnPeHz+ml7nnUx98IMfZCjpNa95Debm5vDZz34WL3zhC7lLfhaPPLJoDEft9IKVNtOLhS241OypTZZdrjDUZDku73yTzhmE5yhqO74HT7GNto9t4/Rt0tOMhCXr+5b5HExfOOrXqLbrzE4rspx3q2fvPM7vW7pWlr+Xb3kanF375HkZvSjUnyJchyssSThmEcfRqQ5XuWin6X3pHs0WajX5sxiGdB2uiE36E4RK/LLMdOy+ZJ1BMtWIHUP/AtC9Mmk8BfNphpvcH7YONHUvzL7LYbXl9yUYMes8yF5w1B8m/yfboSRvlYOpXhr6PdHNe8e2mWYedSO+jgvXSaPYyuoKoCopk96A5Ruob0cec9pjjD7nXDp3ZbmNZVXBnLt8xNVMv93YQY8HtNhn/0QfwxOyUtBSlSln1360Dsseuo1/+gY2v3w3AGBZ9XH5q9qQ2VT4t2zBUhJNxf4yGVYme0wzt7Y1rJvnhgekqgDZRxmKqiy22NyXTbwBXalJtbr3pDdkVin19jUv3c+9f5ONdb4vAc3iY1/I9S2+3m6gvSWFCaERnBXU9TwwoCbb1xUoOpbZF0lhezbLKEifS12RAoD5y9pY+74bAADe7gMa0jOYu4QfmNWDYhwy45buqag75v5Ev13n+5LmLKC980wF9FJd3hO1lSrqe6XobXV1gcVfkSb6mpCsgOPq6l1Ji+2SmGl1d8zzOOqNWLjXb/k8jwiWRRpzZUsENYb1+fiRZoKa852r3+2G9moUQkOSheGbqKpZaRhxX1k6jg2Gs4L7soKlG+gayb/L3016AxYCTR13qqpv+jkCQD64iD3JF9lO5vGO85V0+pEf+RHMzc09/AuNOO9kSgihtXsA3Hrrrbj11lvP9zCzUGH7ZfhVmbREnW0kqik3MkxYyew2WBWwlTZOEWe8IEiYQi6EWhU9Yc2pLMn45mWXd6N/pba2xDYgbDvhB7rPYjTgErhXr2jtmV0y0bBbi3zjFXGEfNDlnwEJO9l+zucanaWG4zEnfK5PD6OShoPyjD+X/nUDn81Ce6dDuIFKOFXi5e69DFmgoCJhswaRiAYo4undhpW6SFQpvX90g8vxgeoBKy+2dF+I8WAsRqrZ9/QJxKdlH0Yep/xap1KG11a9VIYLPCVeknavmmGVUW2RFVi8WkKle77/mXAUNZvgiKyzwdd4tKkTL+chytaiUuOHURH2UajmaoI73GCJe5sKk+6dZ9z3RX0go1Md7mmKhwkrt9fUdxHVJo99bW2J/x4qSMZrVlnHp+JX9MPC0BLinpbxiBMcOSYEbelzNEkYlJSHSrE+3Bxxcu76DnY9cx8AYPGGS5nezj04A20qnscp0+7rV0h40llY5XmchGOGfucvbXMie+Yu+R37J/tYe5b83LnL98LlxCvi8ydI0vY9luOgZM0qlWE+tkiBWzh9NoYuNeR5u4GGTaPONoZKmZ3m7L7vvwqVp8meVtGYRxHJc6WNTTEO9UOy5BuSEBmvHWQ+XmTFVJ8Uze+y+reyrE3P437I146SzPJ8BXOXyWvgr+3j/sXRnbdr+H5JQuZ2a0E3wAvBaw9Bcx4Al/rK4ow3PNWVmm4xWNylvndb2wNFI6QEo5kEDQXNiXIAUVPJGJmSb3Y1pLixDmdFkRaai0wooWOl0YTv4SyKOSmnNSpLMhS5bn8R6rypBzVYafP1yLqb04SAc5IZs9ftcY8nmWjnxdDHvCCdqV6vhy984QvY3NzkKhXFK17xisfkxGYxi1nMYhazmMXFjyeznczjFeedTH3sYx/Dy172MoRhiFqtNmUSaFnWLJm6gND09zMYnjzDv/dbcrdJO59JdwDHkEsgps+kp0XuaEc02BgiUZWWuUNzWH76AQBAS+0URaOtxegc9yGF4ahKwc27AIJ9e+EqUUJh+Inxrm+Kak1NtxkyJcMQ90e8Axa24B2a7cvXNg/vQXBAnqvl+ShyWQGh5tc8Sfn9XuDCDRTrTVXUUOQQkyF/LiZEh97kRk+Cj4o0QXhcediFExbPKxnN/QR9uP2zcIhirXbQwq9ILzSA2XvyFDJmJJJSeDEZI1VVkTSMeEdP36u+u8ZijXZ7md+fqbFP+9sM/ZXna7paFCZcscqUKKFT8vn9eZrAJq8xs7qmjmvlGVeniihEpjz1iF02ONllY2nLthB1FIvqgQfkIcslZnylUYyKgsm4WrD7EERdlcvTBBlVCUb9KcYhBTP0DA860+SXWJ9uU8tHsPF0vcOmt537ujjx99KP0vE9NA/v4bEHJFRF91V5sYnqJaqxXs3tIo1ZZsESgudEasDBw4k8r3KaY9zRIqsElRPMl47GfI+THAQAVHbLv1ueDxjGugQD5nnG8g5ebVrWA5AG0Ili+TX3yrlb27uLqwJFNOT7mqo+edpDEavvFbnTPpVk5O3a/Jk0xk65NAU/0liSFAB9PwBoHJQVotraEkp75biKWpMlBNLjJ7GtBEu9mqzsti7fC0dB8SKoMwPTonsuy1BqSpjQCzxuCxC20OQZdX8hz6ah1HNIFValzveHyezLjftzuLHN5+fvlefoBjXtL0j+hbVAM/iSlOcUoQJFVsASRGyxGDZtXSrv9dr+PdpT0/BHLPKM70WGer8T4p2zeMRx3snUW97yFvz0T/803v3ud6NSqTz8G2bxbSOLxoi2VQ/RxlmEm7LE7gUuSvWdNgQmk8eKtB2FTarFmX7w7XrGbgDA/DWHDCVkzephVWTHhSVI24bw+R6X5fM4YvjG6WyjTiwkSmAcT+P7ecYLDpfC+9v8wDV1VygR2vEdDVo9G892djJZgqUAzUOrU++ZNkxNtPVFv4Okc2bq/abWUXmxyYkNmRR7tUDrQU3GKMbTJtRWqcxwmkg1lDPVo6QeqJYQ/EDLkoQTBdrBOWWjv0YYFhXqGkgNMofPK1iU13t89xbO3icfUvX9ClrbHemEr9rkRJMtYrbW+cEGYeu/TyJONui7jLsRzlDSYFvIEjme460eAAUxKz2zymId7RskTEZ0b7vW5H6ybLszZT1DrErQ74xEvMjzHdpnlVqF4VNRb0Oosanu1kkXQVSu77Dkw9l7HuT57xi9MMTWK83P8cObzY9HfaS9s3xc8/2UTJ1VEh37mi4a+yVUVDu4lzcp9F0dADbZ90S694c3KY5mIYqgph/6ccT3O81Nvo8hH7KVeZkoZ+pcNr9yFxbUQ9dZWtMPZ7qXQ53MnRvkPFCFcijwPR6vPE5ZR420q9xljzWzLKPHhqBcy/On+wRVUu+3G2wmThIHg+On0aB7xXFRqL5HQWa/QY1bEdygBNsdqfEos/QHsXXheAxpW54/BR8CANKEE+Wsu6kZeOraZ+fozVEUec7HpU2SG+uNUWJA1MSodHyHf554E4Zjq0rdX9SaetMpbK1hl+cQarPB8F48bXn0uMaTWAH98YrzTqbW19fxhje8YZZIzWIWs5jFLGbxZIxZMnXecd7J1Ate8AJ86UtfwgEFxczi0UUWxdx0nkQp7zSbB1dQVo3npoCj6VllKnafK7q5fN1eLNwkfevgeOjfcZf8DNYkinlHZHk+iw3aRpWCGnCzKOadsXAd3t2Seavp2VaMQ6003NfVqJHS8Zn0NRzmGHo3o015zPXP3sFVm7mbb2HRwVJLMYw6fa7QFHmOcEPuJi1xOwCgstKGIDZfqcw/i0oNVPuZnJJwQdQbcINt1djhmqbEqWIgJadP8AJBTbGmGKTluBAmo8/R3w1Qu0tVMbBdF3E2Uj/L79K+cj8aT79J/m7PZbDULpSgydGpDo8hAFQVjDZ35X5uaKamdeEHDKFZrqurE4bGEjWYW7aYUtzW0LH8LlE3Qqb04xo1H5VFOU/KSlA27odMbigvtOAuSziNDV+7m7zbFrUmwytFnnHFiuZLkWm2lMmeE2Y1lrzcXE8LtRrG1SRuSVUpQMIrxPYs7Vrl9zA0PYmQbDzA5wBMQ1h5nPJcdesBVxqWfTmuh37wEuz6gefJa7C8pr0SlT5QurWOkhp7v93Q80fNM3MeFdGI77u0u8X3glD6cnmc8rUpspy9PLfukFXX4198EM1PyHv90A9dhbkrpXApV4jShB0XzMiimKuSNB/K7QayhNS7tU4baYwh0Dp4Vjphj8SchHKF0PC7sLnyaNea7HhARIXtI1qgt7o7hLekKk9k+m1UvpygjOYBec3r+5b1OKpqkeW4/B2LNDHU+tUalWgxXxNay9U1EkKg0pYVpPr+lWldOWJlVhM+lktivZtdXptsAxIlSN4pO6itynOsrMpjikZbw3eTSMOyJtOSzj/aCYvP4okT551M/dAP/RDe9ra34Y477nhMHZefqmFSn9uX70b7BgmPOEtrOmlRzKnJ2W1e3ADNcDMfPFQ+ru9fYfqxVSqjukc+fNmx3vE0kyc2bmIDbsh7m3xcog279TqX60lRuMgy/h1gwEnUn2KYffqtgMUaAc0upBg8OIR9u7RyaBzaC+/AlXI8FLTglLeYdrx9bBt9JeyYxXfK9+ytY+UZ+wAAC0+7hJMpc6dEIolee44XYFEONOxJD/w0Qb5xEgDQf2ADLTJ6XVQPZM94CGYZhMHc4+9HqsVpzNCd19R/F6oHyFtaYVFQWJaGCtWxTBHVUrOGxmH5kPSvvhl5IHuSxFj1Lm08wA/k3PP52hATCdCQjknfN93tiXIfhwl2qT6PlRuW4auEkxJ5rx7AsuVnnfzs3axov3Tz0+Tn7L8SVn2ej8tGxIPeVDIDkAp9zufCvTBmXw8lrI6n+1cMWyV6cIVpht2H5diufd/1qFz1dPka9X2z7iZbFQ1PamkDzxDQpETX8T2WCcniFJX56ar83JX7YV8mlb6z2pKm0quE1tl3LVxlLmxlMTM0LTIcHvSmDIfTs3LjMOkNGGZzDPshYjH2j2+yQCYx6FwhmJU6XN/iDVllSV4DK6jra55nUz2O6bmw6mILJdXPE3W2MT52jM8BAJylPTpJs3XbAPc72UZ1I411gu9pcVbaDHXv20I6lvdanqRo0LFoY1QOuAUB0IKvblDeUQUxE6giiTX8aGsYkqDIIsv4OtG65bfrDPW71QD5SEGjBkPtofr9zDlLkSUpQ7CVdhmtw2vy/NvazNoUcp1qw1DBm15KTC9CWEJLk1zo+59I8eY3v/kRv/a9733vBX3GeSdTP/uzPwvgsXdcnsUsZjGLWcxiFk+AsB4lzGc9sWC+r371q4/odSah7nzjvJOpc6UQZvHowhICwbKsLJSauvk0625quIy0S5KEM37bcxmSyeOUd9EU48423JrceTtLayxcl46kqe3w2Dqq6rU2gNyTuy/b0HdhS5JmT59vyedKwuSoFGg8e9cxtrXw5xpcwqcQnsMspDxOeedruw5raJGejiUslOfVztZ1eTdGFSSvFkzZvZCAou3KJD7qRujcIQVKy+066gq+tPyAq24uCXm2FvXO2tilm3ouTl2+P+rchXv+7DMAgKYSppy/5iBr21gGI7JIEyDXjdYAdpjfegpe5CrYZIz0lBREdcx+BUebBJu7PWIhFvGnNOyiKgJFYlRwwgGzLi1DOJLmQ5HnvDO30oSvTaIqPLWVKtuENA6uclN4/wFZlfRqAUMXZ+89gvv/SlYIaU7PHbqGRU6L8UCz+cI+z+9sLKtZSThmGNq0KqEKrCW0PUox6rPdBsFeVBUDgMXVGut2eUsrU8xTQDf2A0AyimAnWsdMjreLXM0zxy9NVZBrK/LatS+VlcTqFVcj95V/pnAgIuVNGSqRxWigGaR5rs2vlf5XHg5QqOpH2tfCpJWVJW54Jsh8vNlly5tJXzML6XpVd1Wx+gxZOV268Qo4FVlRozXEAWARzFhr8lwvZRmq6rgme5Lte4Iya6MJpa1meb6G4VyPIVyKIs/19UqSKZFSpy7Hiw297zzFUGWRF8xs1evhFkYb2oORKvDeym6u6FoGnE3CvaI+p1nLylwZ6YQrxll3k9sViD3n1QOumD3w//0jhpuflNejXcbCtbK9pbZfmXAHNS2Wa4sdBuZpFKO6Iu/LpadfhsrlsvWCzq9IE03eSZOpqjaPlxBT/87i/ONTn/rU4/4ZF6QzNYvHLvIkxVCZqw7Xz2DucnkTlvbsh6jLUrhDfQtJqg2N45SZaFFnWyswVzTcxo7vhhgcPaxCY2GqBzWtsqsewiKoaa+soG54fGXI0AOgKelFlqNzt4QEo+5x+ErugB46frvByZ7wHKbN+6u7+AE/vO8+/i78HYTNiz0lHaX5OV6Avc2BVhVWvSNe4LJC+uD4af6OXi2Y8tAC5APCbStWTb2tlZKZWj7iEnywusDwIolE5kmC9pVKub09x/DN5Ow2J7q2oS6u6fHbDBv5KyqpSRJMTkh4Mx/2GKIldWQA7NXoBj5sE14n2EjBGMK4XlaprBXhqTckjhjSQBwxZGHCFNUVOcZzh3fx9bJsgbPKS3BwUkJ75XbM/Uj13XX0T8o5SdT36iV3wV3Zp8bV1pINAKycVO37fPycjZ8nfC6lBfkwKrVq/MBLz26zfAMldv2TfYa8WweaPF7CrwBl9UBVBqyiOoa/X3q5LS0ZkIsai+HR4+jdIyHk1OgZ9NsNHHjpCwEA9tO+V55rfRk5bTwyw0RYJZF52EdGyVue71C2LqKQkyXLFiyGawV17dumfPMmvSHLUxRZzvea7cnPL9VLDKF5q9osOlc9YcMTpyBOy/WmsrrCfVCiHPCGh5LTSW+gr0ecTPVrAoAXhZqd6bqAYgTTGFtINByWZ5q15np8X58r9ClfWnD/FM1jUamhdpm8XtX94yml8PT0ianXWo7LvZZ2axF5uQEzRJFzT1U+0ibXlIwLW3CPXHmxyYlquDnC6P99U57DohzPxsFdDAk6vsftEJR4Ajo5DTc6KC3KuSqa8vzy3iYmm1v8WpbV8Ct6PVKbwIta7bEsvo4X/P6nWDyiZMp0XH7/+9//bV/7hje84TE5sVnMYhazmMUsZvEdCEs8ymTqiVtF+7Ef+7GHhPMsy4Lv+zh06BBe+tKX4tJLLz2v4z6iZOp973sfXvayl8H3fbzvfe/7lq+zLGuWTJ1npKMxIsXS2j7Z513hCoDSimp0VlUIr1HjHVU03p5qdmThOGXb4vie9jaLRph0FTtL7ea3j/eYcVLdu8owmllmLmy1+7O9qWZZFnxUEFRlsYnairZ6ICYV+WeV6gOuUtX3L3MVLQ/7WnNHfRe2bwGQ9s5CVBSkoJqorXLAO8FyO5ja0QKAG7i8S7dswSJ6AKYadyka+yXk1zi4qqtUhpcbjX1lscVNwBRePWDdI8sPeOxKAFemSI/JZF4O17e0D9geCRfY1SYSJWw6OvkgyisZf19AVsb4nM7R7mGGG+lzVRqw57UnHgdVTcYheObkGQqjN4JFItW/pWaNq6HjzS7PT7rGWZwz7OqUnYcUPmWtrfo8/+wkE2RUNVHN8oCeB3mc6oZow4qFhB2dWLPtEiWQWFupoqF8/rx6hSuYVjngKhFXTcoBrOU1HgOqyNK5ePUOQ56nbjvNje17vmsPFuj7qHtCTAYMIVnxCGKk7JSU7ZBp2WMyyQimzJTnIiBFQx11XsU41OQT9V1Tg9HllB24VaUDVVfrQn+C7j2ykbu6ewHlw1fJ46rqYDnLueI23uzp8Vpa4flPEXW2+XMBff+MVUXcKZdgLxAZw9frBVemALLUgbA1DOckDO3SvZiOU6w9W5IqVm65ltnFKXlfJimcpoSOTf25fLuDkaq0UaVeuA6alytma6UGy56+b1HkmmFabaLU6gHQ82xqjH2PNcTal3u8zm59Q47xmf/7dcxfKteA5uHdDEnzR2UFWxxZ9mmGLz0SI00S9j0db3V5vUrCCdvQNPbJyjCWz88rbhYPHY1GA//7f/9vNJtN3HDDDSiKAl/96lfR6/Xw/Oc/H3/2Z3+GX//1X8ff/u3f4ru+67se8XEfUTJ19OjRh/x5Fo8+LFugdblcPL36FrOouvecwLx6eJMqs1XyUSiGXynPuSwdD0JE3WlBt2KhOWW2S5BfuKkeQMOEYasijTXlV/WWFJ5hlpsZD4AoZCiEwvY9fnA1smKKXQgAaZRidEae67j7APpHpdyA367x+whGKTVrvID37jmBCps9BzxetGBVFlv8ID/XWJiORYrZtu+x6CD1dAnXYbgNAPfzMLRQbbKwpJtl/KBnGKSre2GcaqLhwTzjBIReS6KngOx/KquHmG3Q4z1FpRdntzSNWyWueZLq3iFD8sFeWIU1JxfozFVwXhZDKOX3YrTNx5iii5O6vcHkFK7DRr/cyxVHbHzbf2AD4WnVx6eSC9uzWe5C2Bbqu9U8UN+P2ZQAilKA3Ff9cPEYQvnGmUxQepBN+mNWuSa2YCNahUvnFYV8XpTYzV+xxNfbW1iUopUAxPJ+ZOdAPVaWwFJjhGhajBWQ84U9KIMOBqfka4/+zVE4/l8BANbIQ+/AtZxIiGTEjEVO0MbhFHNWm+Vqn0ySbHB37QNsxTjsbPCc1CKvAiXljED/AsBE3f/jbsQMv+371nlDRkmPt3YJqgpa63zzfoZj2/U6M8wIQE7C8VQfGgW5NEy6A+wi+N4PYNH5kBEzvB29ggCACKzaTz6Hjb11rDxbMi6dxd3cPzg8IaH6LE5RJdi32oS7JiE/CBv2gnxt8vnPAwC6dx7nxGix0YZLm6NCi3OSV2HW3ULSl9+Rkuciyw0hzjFfL7fia9kIBa+Ozox4bSsvDrXIqXp/qRWgfdU+AFLQlWUWSPwzjhgmT8NIu130Y4bMBw/KMapdp9mMj3cUlkDxKKpLj+a9j3csLy/jpS99KT7wgQ+w7Eqe5/iFX/gF1Go1fOQjH8FrXvMa/OIv/iI++9nPPuLjPnG/8SxmMYtZzGIWs7j4QTDfo/nvCRp/+Id/iDe+8Y2cSAFSW+z1r389PvjBD8KyLLzuda/DN77xjfM67iOqTF0MjYancvgGJFJkcicWdbQFi7ukdqXlAFC7YbvWhBvoplUqCVNVqMhzrSfjuJoF6Mp/G3vrmLtcNro6C6tcISlKioknBKxYsQWHPbZfKMahhi2oKuOXWJ/HsgU3m1MlZ9zZRtQb8+/oHMNTPZy9+zS/DwBKdV2SL/IeV3YI5vKb2h/LCXxUSGvL2ElStam6e4FhuGISQdjR1Bgl4RCx2pVatuBzCJaVhpJhhyHKAbxGwq+lz9IQVMywZ5Hn/Bpqph+fGWD7WJ+/I1VuWNsqqMPdc4k8VmuBG3RzxfiKT2/BKUtmVeXQHlgrykPOrYCAToKyrDwFiEGXaD88OlYxDqc0e9iiqBwwe5AqV+OtLsJTsuE+7o/Z9Z4an4Ww2APSDVz+XqX9l6qxslnM0ak2UbhK88opAZWmPIaqHNiuy6zQqBuxXpJXlfN40h3ArcpKyuj0Ga6yWuqcbL/EMLHdWoS9IO2UslIVhUvikWrJmwzBXROGBlJhVItI18uyLQjVY9ENE5z8nITJmoe/KP+t1PT9kybM1mP2ZDlgSM9kfaaqmd72Pc2Kc0rIt2Xlx6ya0L3k+B7fa27gG1C/vI+czRCuEhUlOBwAVzrtWpOhZeeBDRbNrPd6cHZJmI2IL25wBpOehiCpKkM2UMONAc7cLv0PV+aX4FFV21akCrfEVSrLKaFQ60nWOYWzdx2DGa3Duw1xTJ/HKDe+t1NVFeWgzpA2oKvp9X3y/d07j+PIx+8AIKv2u39kWmw37ZxCckpew6izzWtApIRskzDiCpNwHb6HhecY7Qjy2pZbPkoNOR6267AIMJE2vFZzmknK7Eb93bntIdeitV7VZcicCDUXNSzr0TWRP4Eb0NM0xV133YXDhw9P/f6uu+5iaSff989bJuERXaVzNRq+/OUvI8sybtC65557YNs2brjhhvP68FkAgxNbcBpykUnCMXuLZXHGPQCBgn+scsDqyoB+CNp+CX5TLbAKDvNqgb6JHQ9eXT7QqEeotraE8mEliLm8xmwneuhYWcxl8SKONKto1NfnkOrkgnpsXMM7jCCCPEl5EfJbZQSKbVRkOc7eI2UMiBYNAMGigjHqJViChPSUWGSWMSMxDSPNKIw0tEgLmtdua1acM4Krzpf6mdIw4vPKRikSBSnSA2y+WoVj+n1RAjJUvS5RPO3Hpb57GkZ87Qg68FsBJx15VuixUeNqt1dY3NIJ6siU8nreV15xec7Jtbd+BB559wUtTaFOFbW9f5Zp98VEwxRMzzfFBw1ItsgyWKCkQkO5fE0Xm7B9lWQpY9/RmTEsouWv1FE7LJM8EjbNtjvITksYpkhiOAflgycL2ihKqseLpBtswXD1qDOe8jcD5HwKH1Ss0U4fnmJwMvPwsr3wFPzjLO1BQX1MeaqFGW31fYtCz+8s07AqmT4b42J7Nj/QsjjFmRNarR+QEgYkLmuVfM00I/hyMmYIIB9rZXROkCplhmCzzoNM1S/CPjNQ+eFu9ILZjTZ/r8zwh6uqjUd176pOjol15/mc+JXbdfTuk/PszO33YRf5HiqmmVMp87VPwog3DgS5twKf/552t2Ar6Ewsyk1a4fko1APJEg7QVbIs997Hkg4LV8iko33zjXD2SokPK091H939sjcpPHWWN0nOsoam5bFVsqSSsdbla+gdk/fK5tc30Lzk6wCA2nXP0GNQ0sLBO+6PLGe/yTwreANaqpeNjZQ8f7fqoboqx622toTSorqHF2UizybfkMxBYuem6hpPugPNIhR6I5qKhDcuuXIYiFX/5SweXbz85S/Hq1/9avzSL/0SnvGMZ8CyLHzhC1/Au9/9brziFa8AAPzd3/0drrzyyvM67iNKpkyNhve+972o1Wr48Ic/jFZL9ld0u1286lWvwrOe9azz+vBZzGIWs5jFLGbxBAshphTfL+j9T9B43/veh6WlJbznPe/B6dMywV9aWsKb3vQm/OIv/iIA4PnPfz5+4Ad+4LyOe971w9/8zd/EJz7xCU6kAKDVauFd73oXnv/85+Mtb3nL+R7yKR226+im294Qk2254yk1SlPMNgBAnmtLBM9nTzY3KPOukXZOplUKoIUPuRITJ9wEiVKA4hwvOXkwEovT5eksHPBnURRZro9v58bbtWcase5olwVIS5P6mtzVEaRz9t4uzt7bVWPgMVOGhyDR+lp5kqBMdhtqh+wEPkOCormo3ePznJuhSy19/rSjF7GuTJHuV2XlNGrEVir5O/z28iznKlYep3qXHsWsM6N1elKUlQ1JsNzm6gFVptJTx7maA89niIg1ibKc9YPshVVDbDRFoRqpyZIk62zwzjcNI54TNJ/OtYrgOWGwyui8LSG0kKXvaU2dsvyswYNDZIlqDG7WppiQfHzVAJ9sPMBVNHftUhSq0TqnuRUn3Nheqpcwd0h+X/IhFLZgSGbSG/CcI3jHP3QF7N2yMpW7JViZ+g6J0bibqzHIUy0mmiZGtTXmc6Ex8gKX4edqGGOs5nL3/h4AYPu+Y5hT88QpLWs9JWJJ5hnD5EhjLZJqa8ICVSIBDbGmozEEa4fJqoxbrzAkaDfabDlVW5PHryy24CqhWRHUNHHEqDTSdy0vtFBSVkH9Y2fhf016+s1dK19nGdpTcX/EkDtVxoLlNlfOkv4Irpp/dlsJ2aYRV//EqIfJuoQEJ70h5q+U5ID2zdKGxz18A0OCmMTM5qMqdtIfMSTpBHfxfWE32lzVo3ui3G4gWJLVs9GZEUYKpg7UvSaCOh+/1NQWS1RlFq6DmtIoq67Os6Zb1Bsw6YEiWKyhtiYref6ePQzVEymksD2ef3aprKv5aqyiTh8D1WQ/6U+4GuX4DsOpxLoeXUTo7MncgG7bNt7xjnfgHe94B/qKQV2v16des7a2dt7HPe9kqt/v4/Tp0ztKYJubmxgMdrJiZvHtI0tSoKQWeFswnFBuV1Eh0UH1gBJ1LQxZTMZMm3dLPpyEFmhbv4eYCuFAU9q3ZKJi+x6qJHGQpyjIT4z+PVfpnh54UcwwGYX5YLaENmM2f0d9LXEYM1zlQ5s4N9bkdyyyAqe/IResYTfCshoPWlSzJJkyeiX2GbG43GaTy/0iqOn+rjzTC5nQyQVLMxg9UwRB9I9uIDjQAwA4ZZ3A0ENcGO8p8pwX4zxJ2ZiWjm97minXuuIgC6KymbSigAPqIcliiEp+YrnN38tur3Dv0RSERSKQBhVfJrLavPehouAeMs3eogQ/N8QaLSEY4iHF+sp8BdsKUhmun8G8gjG4h2gSsYHspDtAHkv1+Lzf4fGkhDJPUuy6+TJ5XMOwOlUL3nB9C2M1f5Mw4r6U+tVSVdredyXykuo/LAoACh5PE51QUV9ZmqCYUCIc6TFUfVLmHLZsi+U2fN9BNtasL0B5CpJx7iSaguIBdV3ovk0TTi75+I43dQ9BPbzdVgveObIXotbUit7AlKo9IJmDpKaej0Pk0TQbz85zfo9TKXNSH4cP8kOd2K6VlSV+X56knES1LlOiop6P4VHZezTqDbn3h+d8o82flRqGwq3L9vJGjxJDK4sBU/yb3AoW5Dm4pzrcvzXe7MIuq+RT2OySQPPfNuQM8ngD24o9XFm+FwAQHL5Ms2GNDStBqamxvpWaNXY5KG13ePM0ONkDAEz6XTgq0Q0OHICoSVgvLauNrKOTKct24JxTsWkYrOz+yT4zU73A5YSQ4OzMfWJZtDwZ4twk6tHEeSdTP/ZjP4ZXvepV+M3f/E0885nPBAB87nOfw9ve9ja8+MUvfsxObBazmMUsZjGLWXwH4kks2gkAH/3oR/Hnf/7nOH78OOJ4Gmn5yle+ckHHPO9k6vd+7/fw1re+FT/5kz+JRO3iHMfBq1/9avzGb/zGBZ3EUzni7SEytdu3XQfBotK2qQW882Vn9zSZqjrQ7qowdpu0g7XKAcMF8foxttygBsfa2pLe4WYJhGLaUNMuilw36Bq+dXmcaqsHFab2k7BtZOdUpmzP4Z19nhVGs+yYKzhs19HyUW6SH5iHucsk88hflbvDPOyjfaVkHZUXW1MaXOoDprRtWKcp7LMVCYVTLvEu2tTGilRlKr9vC42DDwAAqtXmFGx5bphQp1euaPE9BfdlyTljxk7wclebbXdgqWZz5JnBmNRMJCYUTB1IMPwoKpoVSvPAyTPNIKLrYv4uSbgKlhmehMSqS8fxlOAoHUOo6ontCYaK3KDElVEYTDauAnhaYyne2twBhfrtBrwF5RtXbWqIqiNhmjSMpqAYgveIhZa7Fc3as4SG2cSYBTatZKL+HTPD7tz76twwhWGFZ8OP1XdQ0HS40cEcVdeCuq5MmT5rxs82CY8a+lqmPxuxQi3PZ0uRqTlN5+24DFdZho5VpvStJmfOchWZqkY+prW/CLYNFgesO0finJYQXDWxfY+rWOzz2d/mCqYT+BrqV5WxDGDfPLvR5kbxZBwyJM1V96DG+lrIM66q05z2mzWG2AaRvo+recZVXgqn3sCcqp4B4Cb7rdtkZUrYNkrzqoI0ijSkfQ4cDkyL7cJxeRxpjUjHKeYyo4FdrZkWrZ3GOmoVmq1H19NpLaC+T9v3JENjfVfVfBrX9BxE4HGNJ3Ey9f73vx/veMc78MpXvhJ/8Rd/gVe96lU4cuQIvvjFL+K1r33tBR/3vJKpLMvwxS9+Ee9617vwG7/xGzhy5AiKosChQ4cQBMHDH2AWO2IyiBErrk9Zmf4CEjKh3p1FtXjUrvGZ+WS3Vww/vT4s+j3RkycREtWHMTh+mh/uJIfgH7pCLmBQ4oJ5DwAYOrRKFf3ATRNN1c+yHTAeAORQCuwGc898na1K1LarYbY8Sad6igC5ONHDee5QixWDWXTw8HXwfSNpiEP9HaBYaLlOQkkOAGnCiyVDc1nO55JFsRYxVQ/Ps/edRakuGVv7WjU4La1CTjHN+lLJVC0wxPcUczBKWcpicuYsfJWM0AM96Y80uwvQD19KlBpths4kvd5Y5EuUQMsHo51ncKgfaDLihy/LW0zGRrIWwTL6abhPSMF4wnUZVk3CGJaSl7CEfk99j7weweoCny/39jXaMqGDTBxJNiCPRoBKpujhPdrswTspH5jBShuuIbcByAe2yS47c7v0cyTKvH99BamjWFquj8JTmw1LgE7XIrgtjqQArboG5yZTtutyom/ZFixhqcM6PD96PTkWd/zl3cxuPPDDNzE0ZY4pq9Q7Ln8WXY9s0JuCYOnh6VTKKIjpSMmU4/HYShbidOKWRyOtpL/ZRaLEeh3DR9MNCHbSmyC/3eDklt4D6Hs4CSNOrMrtLn8vU7KBRWWV0K3TXuZkTx5LnyvBZcJXXnVlzT4ukljLeKix8ppVnpPhqQ5GBrOtpNi1bpXWLp/nRLA8x20FUVfOvc2v3qPbAgz2MUlO1NaWOKk3nQ0s2+YEfkmN1amvnET/uFynm8eOafhSJRNZ0NYyAXmu70UF7+fjkPvi/HYDjb0EMxcIluV4ELQ+2tCM51lcePzO7/wOPvjBD+IlL3kJPvzhD+Ptb387Dhw4gP/wH/4Dzp49e8HHPa/00bZtvOAFL8D29jaCIMA111yDa6+9dpZIzWIWs5jFLGbxZIknsWjn8ePHccsttwAAyuUy93q//OUvx5/+6Z9e8HHPG+a7+uqrcf/992P//v0X/KGz0JGOUwyGcmc+3Awh1A44S3L2dIqV99ihdgPOtdoriEvltSZru8jGWwDJKb0LSlKu8NSulF5dBDUAQBEPeKdkjZRAXX1O74An5+q6TFd4TNgri2JmXBHEUGQ5i9wBYAsY+hudIwVVpsrzNdiBEhGlBvitdQ0h+QELVnLzdRxNVT/oZwgbwrOnjgUHsD3tx0XVBfIUPLU1QvoPUucmWJnD4g26okXjYNrY0M7ZrKAQvJlGKWzVbC88h6EYqkgk4ZiZUZat2XZ2S2sxMcMvTXY0TAPQ7EzH09YxSay1k2hchj2GP7PJhCsSUac/pZsFSLiPGvKjbgRbsU3pezllh3V2Ss0q2x2RHYgwmpDtRluLV9o2vPq0F1reG7JwYhbFDEGxEKfncLMvvQYABqoJ2l64F44n/54XDRS2Wt5sR4qE4hxmH42bEACzI5W1juewQrLjOyzM6JQdJlNkalzWxymqSietffk62krkkeZpHmsoKYti3biurt14s8f3SnmxxY31VlDfoRNVRCNdMZ5ErAdGEBocV1eIbKHhWtJWi2K4ylbJKXsMb8u5rBqd1Xsm3QGGGwqC6k9Q2yXvRXq/8ByMFMMuCSc8d+aulXM2rzUhxM6maQnJy+tM5AJ70NWEhEh7EiZd5XOY59wYP+kNuNokziG/AIAjbB6XPEmnm/vVuYYbinnoOXxfVlelRpS3sKj16YY9xFuSVJHHKc9FgjybnYEhAjxmmxr2oFwCWyihKDSaoKqSab+PVI23W/ERrEj4MYsmU1VB+bvp3p7HMwrLepRsvieuaOfy8jI6nQ727t2LvXv34nOf+xyuvfZaHD16FEVRPPwBvkWcdzL1q7/6q3jrW9+K//Sf/hNuuOGGHVWpx7I7/qkQRZYjHU8zh+hfWnR7Sjm7d88JePtUX42w+YEqgrrW9TDZa0LDh5UluVBQD4Pl+fohm2ea9cOCghn3Rkg/MfWQsW2maZvJ1EMZ1E4JWpZJUdhlZWmzH4ce2HEYwwvka/25hvZtUwtLtt3RiUS1OSX/wGNqMrEUG85y3CmqOiCTEjHSCR8xaU4pv7BTUYaGq+CTJOFzpX/TKObvKiUuJjwe3EuiFt/6vhW0rpK0aVEOtIgiwYwGay4NI3gNuQBzP0jQYkNiK0t4sQZCpGeUwGdP+Y2FmlUrPF+znVRfTtrvIx7sFB6N++GOBTsJJ5xcjs6MOImqtOV1qe1uokmq5/NzmkFKMI3Rzyc/nKQeMv3wU2OU+d60iOhDwMmc4ARlfh95LhZxxKr9lu3BSo2HAbFUaSPgBxAEXQsbIIYd3VOuww9Op+yiVDfFTeWCmxXyvvSExRIejYOreqOirlc+GiA9LeGssUoCzLB9jxMof20fK3VDCH2PqiQ1727pBMoQ4GQvRWPMym0ttElmunH/LFPuSeAXmGZtUk/kuBPyRq65t4GF6w7J4yqWsSlOG24OmGnJRuhGIlWksfaIzDIttkv3deeUXoPSGKOTUsw3YlNlj98TrC7oJG40ZlkULQ8zMjYpkTbi9vXjLosS/rdE7gtKBsJuL+u1ot/hxC3uj1BRZsMkIEqyCICWjACgxTnzTCu7m0kdwbJGW4TpHpFFE23SPiZm7TRLdBYXFs973vPwsY99DNdffz1e/epX401vehM++tGP4ktf+tKjItGddzJFQlYvetGLpuTWi6KAZVksxz6LWcxiFrOYxSz+GcaTuAH9gx/8IHKVxL/mNa/B3NwcPvvZz+KFL3whXvOa11zwcc87mTLV0Gfx6CMexBAFWS5Y8MrUwKu1bSiKLNe7vpJvVG0y3pHzDrzks6VB4HrMiqFqk/QoMyAiqigQNGgw+JBq3zmvWeUdJ1Wr0lHEVZk0ipnNJIzKFZXSbdcBA3rjWDOiTitoMEpRW1E6N4utHeKVchw0c4l26aRLY3m+hle6myxqWDguV7FMuIx2s3E/ZAf7TJV6v+uGZVz+rxS2vncv6yFRQ3aeaKHPUTjh3X+pVWNLm9XvkRZLztph/tx80NON5eo72Z4WRbSE4GZc0uHJyg29QBW6+iBKAWyqsKjKFDX3AoAT5BAG5AEoPSn1mjTU1y4Jox3VoCRKEQ8Jjkt5TpIGTuuyvez1ZjmunjNU/Rv1NRRr2Lbk8c7PEq6jRUF9j3f/FHmSwlW2Rbbr7GBVFqM+irEaQ6/MMIWVTLRAp2Lz5eOQq2f5ONQVM5Mt6+nlkT3ZvJ2w1a6yi9alsvrgLa3wfUlz1nJcrqrkccpVFc1qjbHxedlMX5n/BlepqqsLKC2qSrJq6oYQfB2dsg2hqlh0fxfRiL+LEwx5HhKMGA8ixMrT0AsnDL+b0Dt5HmZxjpVn7AMANA+uaj0yY37R8eev8lFeaMpfqnmebXemqsAaul5kJvH46P0AgNNfvIOvZ7ld136R6hpIwVhZ+SkvtBhGH2/2uDGewjFYb7bvMTRM32vcjbj6XZkvsxiut6IsYCp1JicUScIwXhrFXCmjeVpdXdAVzGrVYJDqFolctWNYjrtDYNQx/BWLPEcWmS0Tyv5KCdmOuheTzffk9eYTQkzBw7feeituvfXWHa/7+Z//efzKr/wK5ufnH9FxzzuZes5znnO+b5nFt4kszeDW5c1ema8wHXayPUFjr1w8SMiw8fSbprB8plMbIoDcQ2PSi+uaCYZAJhSFsGEJQyqAICSjT4qPKwRDRcL0A1OLxKQ7YEG9NIr5GCbFmOEbV8M6gFzcAb1geIGL5iEpg+AbooHci5DnU2KklPwxhdwPtFntdgdDJUSYZzlqa4rmTYKSScxw1/bxHpfRr3nePgDAJT/+XIZs8n4H8bZ6yERalZwW2sHGkHvcqovbWLpeHoMlG6AZh6yGfU5M9StRr4xpDEwK7MauL7dd2A11HdU1HHe2+cFUDUx6vfx+nvEd4sFIC3WOk6mHKn1HCtu1Ud8tH9rz10hJiuDAAW06a0ouqIy5SGLdJ3IO05PgJGbr+d4U0/JcSMyrVVBf1jT4WM25iERcj5/kh5R3yGe/SQBaoJOS62ikfzZMnzVza7qvz5RHoJ9b6kG//LRFhjrheFN9eoBKphRzttSqcjI1fFCe92BjeM7xJWw7XN9i9ljrGulbZzfa2vsvz/Q9yjBfxp8rXIeTEeqHcnwHufqsOIzhqOvhBqVpGQAA1ZUa9xEJ18FwU/nJqXH323XuHXJbLU742OMujpCcUerevQGLgLrtFdCsovvv7N2neG7MX70btT0ySSRI0Q6qejMkBKo0p23BrOcxCxKXGC6LByEGJ+XvUyW2Wm75nBS7gc/fwYRXp2QtVLiBz31blOjbvsfnJfwKJ9Ime9NsL6CNKN0zdkM7M7j1CnJldB+e6vB6kiVKZX70reU7HvN4ElemHmn88R//Md761rc+fskUAPR6PfzhH/4h7rzzTliWhSuuuAI//dM/jUaj8fBvnsUsZjGLWcxiFrN4Asf5NqOfdzL1pS99CS94wQtQLpdx4403oigKvPe978Wv/uqv4hOf+ASuv/768z3kUzrqexqYW1CNj56D7WNyF9U/OUB5Xu5yBsdPq1d/nndEli1YVwXChhUZEBJkJYegOWfXPvaKyn21e0xG2uJiHE7vziGZYQSnWa6nxUA9n6G1VOnRTHpDbtIEwGV1sorJklQfyxas52JHMYbrilWjnNlbB5poHpawkWgu7jgvWSVT8E8ac2Uqo4Zuo/k6T1KuHIXrW7yjbh1WTeO+p0UghcXQFVWounccQesKNR7lgFlSfCqug1JLVRw6Ie8k87zQFRhubE6mNIG4qqjOO400GyqNYtQUu5LfYzDSUBTy+gGwUl1dpGuURdqyx6tV4O1STE/SgHI7sEkwM06QqCbj2BAMtD1qjNeVqequKpaeLpuQa5fLSomoNbWuVxIb1RhjoEioMM+nKl3EXjRFYKkilCcaDqO/ty7fy828SGNkZC1j+iNuSBaY5fks5mn5VQ01qibnrLOBtC/HqMjyHcxUk3UnXAd+S1cYhRob0tdqX7GL4ThRDjQ5wBBGpapNZWmeIVaCnWzPZgZrsBToyo45XlRtarR5/qcPHkW6cVS+dqQa0X3dVG42gFOlptSsQrjUnD3hZnSyrgIAr076XyG6dx6T33X/CuuoEcQWLLcZGjOrksyMTBNuBO984yi2vipFM3d9dx+lVel9RuSBsjG+wfIcKvv2ye+rKvHMVKXxVJ9RWZrnMaJ1Mups8/cddUJuJVi+Tt4Hi8+6Uc8jIwiCy7tbDAGnQ+1XaTaQk46Vs7wGi8ST00SvqXyvC5hQJzGszXWNWy+MiLpjbjvgBvXaBdU+LiiezN58j1ec99V505vehBe96EX4gz/4AziOUmZNU/zMz/wM3vjGN+Izn/nMY36ST+ZwSzYvUkWW80MsiVLEisXX2C0XYjcoc0m71Kxi7nplrrq8BktRwlMhF7/BnXciVAafizcKOCsHAGBKCZo90UYDDW9QebpS19CeH/BiVkwipNRPwBRvzeADpntNAMmEo56pUrPKrJnwVIchh4phAizoYWSISVKPhQjq2kxXiB1+dMU4ZOVsQAvxhQAGx7fU2+QYNw/vQYPgGQDr/yj7VnrKa66yuKUTO6+tF1BSlTaSq1K9hMUr5tVxd2t6O8F8QvB3KKIQSUdeRxYU7PRZosD2HKaMe335OuHXkJNxb5FDRCp5HXSQKgiUlKdt3+N+nHD9DPz2+tQYpr2zDO3lScrwx6Q/MSQP6OGWsyzAytP3o3WD3CxRT5clbIMhV8EOT0eTkTYO2dA3PLnBSQUxPb1awD1RWRRjtNmTX1HBNKXmWQQHVNLsuAZUKcfN9xw9J7c7nHTYbW0+bCqJ03hnUTwlcUHjQseihBmQEgOuL99XVcl3fd8yRFP1LtXneE5milJPptMAIByXBSPnVKJhe6f573mcYcLj4vDYUFjChlWXjDKru4nwiEymHLVRKC3O682G4/KGhiD3SW/AcF59bRFzV8mE0/7/s/fnUZJd1ZU4vN8YL+LFmJFjZWXWXCpNJQkJsJCNoLENmM82bSwDXjTgtt0/oG0w8sRgA2YwwwIaFvwA0zZ2e2xwf9/CXm7aQGMQZkYgIQlNSKpZmZWZUREZES/ixRu/P+49596oLEBVpRJCirOWVqUyI95w33v3nXv22XvXmswYXPv23QCA9gPKLxIA9xbRvV1Y2sX7ynptxGuCgacnzNSPV5pt8DG4zSbfP0UJ/TUvC/l5Ku/bqzz7qL9R7+HMUrUw8KtsVkyLJcOyePFmOUNU5fxJz7LhekhIemH9pGLr9VRSrvdqUYw6PWx896j8PyHmO7V/G88hlufyApZYuKZfGeufyjWhWEAkVXQfjzqqXcJyLW75GHalp2jhEUxQDFMxxM/1+4+zOKfKlJ5IAcJO5g/+4A9wzTXXPKwH93gIy3NYn8jyXO4RqGxv8MTe2C9WcXrzt719D6ztFwEAslKDkyG7KTVL/CI2bhcaSf3jG9gj+ywKlwiXdr0nwPRKyDOZOJGSemMW8MXPue0BiZzITq2olZY2adKKPhnGGG6oFTcAuNUSfEkp9rcvjH2fKzjc5Dni3iRXf1FTL5eW2HEPEaCqI9qkm/T7ynTVKyAZdsR4yIS0sjzHNjXFmQD+rHyRR4q2TH05XiXkCdIn5fheB6YjElY9gaQEDtBlCk7ArMperSzjZnMyl42DkCtidtFVMgxdsX3br8Igc+M0Rh72+RiowTVqtfi46d7ZPHwS3aNrcrtqdU/7cvwCartEEljZrhIIquiFGKKxV1RdZp76FDjbdorz2lQSHdyPZ1rjxtLyX+4VS2KuauqR8T7TMWmGrVpdI9UonqWanpm43sWZBktKGJaljhEYs9oBRMWjOCeONWp3OLFKtH44/Vg4SYsSTi5Jodpr1lR1IYmRyuQpPC70r/on1vme8Bdn4Ej5mNICaT+NxuQ2qH/Q8R2u3HCSN+iphNC0+LiI/GBYJgrzos/P9KtwaLEhdZVMx+aXv5BxkLR910Mmrxkda21HFZ7UOaMECgD6UqU+ixKULr5cbLcxi+SIWMiRMj2g5AamLtsFT849Zm2a71+q3FZ2aaQKze7mdDkTCq7eQSU8dIxZlHDDveMXWTrBlvpfRqEIS6sG6WMPjM9raRhxZTQOQsSSjNE9Lu7p/oN9zMlnubZnUcxv0HumlObb2PnI52S43mYHgKg3YI0vy1HVSoqk/MhVpiZx9nHW6WO1WsXRo0e3/P7YsWOoVCpn+MYkJjGJSUxiEpP4sYnHsAL6hYqzTnWf//zn49d//dfx7ne/G095ylNgGAa+9KUv4fd///fxwhe+8EIc42M6nEqJabZuVfXl2OV9zCQjvzzRl6CMMo1YChSObDbWpFXxYK3NK1yjGyE4LFaNBJFZjVlVxrVd9odib7/ylKh4ybASTWGcvMW4lG5zFSGLUgw2FEwBCPqwv03CIJU6w4v6CpA+6/hF1bcyVOJ7VPlxbReZrAwZbsrMOKrOZJstjKSKdtjpbWGMAcDGPZKqbN2J2aulsnoYoSBZlfNPEESK6YN7Udh1kRyvmXHhUAAYBrCLYvWYxQnTpkedPlfiqMdtuNaGYYlKoWGaGEoIa7AmvkP9VgBQaPiKSi/hgOTkUYYQ9OqOYbvcj2M6osqVhBFDx5XlGYY1CQ4btvrcH6WLpFqew99LAwnPNH3MXLVf/L3W5CoTSVGY9RmeOPOwr4QZSY4h6CkBz2GgGSUrphldo1Gnz314pqMgOxJbdPyiEqeMQk1hP5d/95S3pCZKm/XaytSYIom4wml5LvsE0v2mG1NH3YDV8dMo43uVTZ0BzTQ54nsxjSQ8Y5qqJ0szLy7OkBijunf6K5tsduss1/n+YcmSYcBsvnyk5CWov2y43kZNjou/vKhEMVm8cxODtU0+16nL5Bg3ZvjasdDs8qxW1fH4GEml3q2W1Bg2ZlHcIXqSCrJ3iSrAgOhZtBsSkjwTfGSaSmC36HMfEjMX9e+YFleqTNvlSpYp++GSU+vM8ARUhdM4Q2+S6ZXgNsWzarJgZqQq7eEIgxVRHQ47Q4y6UnZC3gNewxvrt6Px4Eq61ktmWBYL77KBueMwlDsmFdIdch8pCeRmVU389kLHhM2HF73oRWclQn7WydS73/1uGIaBF7/4xUgSWY52HLz85S/HO97xjrPd3OM+0pF6Mdq+x5Ne/8gJlGSJ3lkUNHSrUlf9J1GI5KSoEJqlKjfYxsdl38+9x3m7c0/YifL+i8b2m5w8Okbdhm6eCtGXQwa4RhrDGEoF5qDHzdOmJoFAgFsyjJBl4mhYN2a2rlShbRegXq1Y6RYVm1Jban5qTJOHLDfoXzdTyuxGSVNI5xdnZ6yxmUxb427A8B2ZLgOqiT4ZRsKoF0DjSmG5UzhwNUsTGGmMrCdNMCmZSeIx9WJ2d9csdXStpM69AvYJ2wFyOUbUM1aoFlDbJRLO2SddDme7aPRmW5hhwLIXZtFXquK2A4usK+pTcixbyKT+T3lxBlZBJHyxNIQdrLUxlLDQqNNHIpPuYTvkn6mPymt4aMgXUyFRDeaZTMxgWmyYDajGWpKySNtrPMY6rJvFCcswmKf1BdHf09Oo+qfrSikJDnH+jl8cI0oYWuMvXTO9V8U4g4RAxsmHauwfrPVx8naxSBkGEepSB628IJJuw7S4X02YJtMLV4y716yyWa1Z9DkhpB42r6n0i/I0x9Q+sYiZf/IlbJpMdk+JbkKsSXMQRNV+oINT94kkZuayDZY2oGeKGs4BcKJE40Evffqs6dqcXOrQcWVJHJO/vKj03WyHNa/IuioJR9yH1L73GMNZzYMt2HOidYH7G7OMoVirMauSZk33ixvqzWwMTibldBqj4Vob3UNCcT4ORvxclhbkfahr1kWhmjvI8ieOkYfKyoUkOoKTShGeyCq1HQ0UZ8T18po1pQdGkaU8RjAtlSTK8/OKPgqyV224fgpZtCGvgcP7oMVCP3oEpREe4xGGIW677Tasra3xM0/xC7/wCwCAD3/4w2e1zbNOplzXxfvf/368/e1vx/333488z7F3716USqUf/uVJTGISk5jEJCbx6I7HcGXqX//1X/HiF78YGxsbW/52Pi4u59zRViqV0Gg0YBjGJJE6j4i7Q15xW7UmrIpUFR+OmPLtLMhqkV/lalG62WLIJR+FzBqj1bpbLQKQZfnWJgsUusSSKXhc1s8GSvySVm22ZcH0JUyRRgzNIYkY7mLorVpCTFUGy+TKj1cXVRmvWVPN4kmEdCjp6XECry7uHVrdOacZ2RIExJIQnlrZ56Y9VqERBzD+EFOFIewMGPYsVF0+Llq1FjyX/QvtOcH6gWEKHzwASEZjZsqAqBrR6t6plLjZVve4S7XVJFVlusd7TNd2fXHcU/umWAjTu/xaZGUplqixL1n5PM/GWEF0PATh1q95omIRZhlfW8cUUJAXJXxvBWEHvQdlA2wQb4HWig1PwXD338mVCoIMK3t2wLv8WrGvYhUGwV0EbdguLE8pZ1OjdDwI2TCXaPmma/O+0jhmert52r/iAF1ulKbnx6mWlFedV1Jiob0OMlbzV1WIPNXgUnnf0DbdSokrFZtH2lypa2yvYvfPCBHdprxesB0Wp0yCkJ8Lah4vLCwqpXLP38pAzZQ0w/yT96FxhTQjn1lU8DVJZUDdR3Ew5OvBfoFRypT60eYI81cqA2Uaa1bv3rdXtRKYFs8Rnrx2UW+gTKjDiK8He292OrDkvGAUfZjyuSSZiHI3YEZx2NpE6y7BoOuf2EDjYlE58iVD0C4VFSSpEQdyzTORYbAxcdhYyYxoFYacCSk5V6dJ5sD0g7EmfnpWbDnf5WmGKFSwL0G8o+4Ijd11AMCOn75KjOuefZoorsdVWp6jnCJyR5ps5xnM0TjcnEchyyWYlsX3gWmZyDOay+T1Hj1yVm2PZaPj3/qt38INN9yAN7zhDZibm/vhX3iIcdbJVJZleOtb34r3vOc96Mubs1Kp4Hd/93fx+te/fkymfRIPLShRML0STyTJIFSMFTnpCjVdOb5ZpqCFNGXIgGCYyvIcs5yGrT7WvnE7AGBalsTd3ZcqC4o0VX0elOi0VmHJxMv0K+OJBPUrOKqXRe9NcssiQShK+wfTdpR1R09BTICCFFj5WlPGTuOYX0yFqRqPAfWF5ckJnoho+3Gnw/TiUaeHUVv+Pc3R2C1eKKR47DWrY8maJaEHUkLOLZcTGH1qYEPiQYhkqNiTxBYqzhSQkQo79ar0Bgg7YmwHG0Meo7krBZtw+uBeVskOvvZZ/h4la1atyXRxYlwCkipPMAJp8hSKmsZRNCYHAABuEsGW0IVhGvwizqKUjbYpRt0RButibAuNCh8PJUWDEytwtkvJifldSjKBXrJRiHxIrLshsxjTMOLeHO450XuLUlO7vzz+19A0jOzi+PftxgwbecMuIJcWS3kUAqQbJI2t0zBi6FjXuSJ7FLfqj2mn0Ut0589cgqmrD4rtynuvf+gYszKdUhHTTxAaXIWLhZVQXp/nnkYEHWTyueXn2jTHjI7thZ3is1mmbIfk820DYyxD6hsjo/A4iNHpyCQyShHvE7+fklYvpeUlTqBYYkSOJ/UUEcOvkmUMxQ5bXU6i6LpkUcJzUD5qKi0sud3ibIOh2iQYIpYMvs6RTWweF9+buUSc9/TBvShJXTCrMavuX3q+wwCgBR8wJnWhQ4EAYFhtnClorHByZbzPiZiSEbH6Rkh5DkpYa62yUMb260Wi61/5RACAPbcDmSfnUdNWCTq1AphahSdNVAJNhvKDLid5cTDkYxy0Ak7gaa6YGB0/PLG2toYbb7zxYU2kgHNIpl7/+tfjL/7iL/COd7wD1113HfI8x5e//GW86U1vQhiGeNvb3vawHuAkJjGJSUxiEpN4BOMxDPP98i//Mr7whS9gz549D+t2zzqZ+h//43/gz//8z7lJCwCuuOIKLC4u4hWveMUkmTrLcKpFuI06AAHjQYoaRt0BVwEYyjJt8Z8M0jAybYdXrgY1gWraJnEQcgVoIPVm0vAWFJbEStD0K6yhRJWvNOgjOXQPAOk/RZWvLOWqC4V5muksQXelhSn5AaX5E3cHqtpULyv1as2E13JUQ7E7I86HG9hNi5ubs80WVxr076vG9wZXofQGcWqcT+NYKZgv7YI9u6jGGYCRKJPSdNAba1ylYJ8+DWIwNfFIijzNmEGXxin82ToAsOaPYZo48i83AQDu/d/3IZIN6nOyItLcN4W5Jwl4yd9/gFfuWdBVgqZUFdKaq/MsVeaqpNllWkrFemEKaSz92coOV6nI3DgKYhQlLFRYWMRIKowTo2tMVPIM9gt5rFSwdWHX073vxAGoqodhmVt85Ry/qODiSFVuCSa0ZhaRSz++3DBZ98Us1/k60sp/uN4ZUzin8aB7QxftBJSQ69oth7jBmpTlK0Wfj3XU7quG/LKEHNMEeUdUrtL2uqrsysqw01BK/jAtxWqj5x5Q+lrDYMxDj2B9qiiarsX3zrHNEbZJaJvEMe25ZX7GdRVuw/VgU8VTPmtWrQnDvEPsfhiNGXzTWBaITFLrqkoXVdM0WDZLM5imqnpuSkHimIzO13qYkizA5hUXwZZ6ZqrB3QUK8nqk6RiTUsF/itxAkKQz63ETfnFOzAVZFCI4QaznDpNu+Fi1a5+EkWoLaPjMUOwd/SQAMYfVLxYvZWf7XhgEM0toT7QiyA2b5hnaEiw+/jgINZ/MhAWcqW3CPIPJ9gWLx7DR8Qc/+EHccMMN+Pd//3dcfvnlcDR1fQB45StfeU7bPetk6tSpUzhw4MCW3x84cACnTp06p4N4PIc3VeWXoOn5XGov1Mso7xK9O85O4WmSeRWYQzGpZ8OAX1KGFcGQLwsWvDMt7kOyS8ptnF7+3UMrcCWMUdm1NJZEAWJCYaf5E+vIU8FEc6slBUvKCSvPMn5RGpbJ+6V/jYLHL7bClOacbm5qPR8STjNNFKZFEmbNLMKenh8br2wYqMTRdmDWFLsRAFzNWDcNlZFx1B3wPujFmWcZM4yyKFFO7jKpyoIuK3YjS5UQn/zXqdfZ0ifPUvWS6Q547BhqXW+zYWmpWeQJmlh/g5VTaD8gjVptE2VWIid5iWn4u4WKvT2zyAnl6NADiHpHxsbbXdiukl/9hUyJiO2oXrF6GVMy0U40e5/gpOrtYBsN08Ko3Rs77sKlFZXEpREnzQy7drs8Fqcb6eaaWCcA2JYJq6j6L22SK3C2qlHrUgdq0eGqPg/T5l4V06/yYsEuymSwtcl2Lq7vcE+RL5M8z/e2KPnzeFAiSElD2YW/UyRWafg9HPnkZwEApa/cDEAkBwQ/Gn5V9XWRune0OG7dRFCmoaj2zKJM4rHxpP4n+n6e5hhKaZKvnwzwv/75XgDA9d8VScBF//EgGheLYzVdT7kclOsA9XXJZNCsNWEviAVXeaBkGFTPVojhupjz/VpTJT4sC6Age70vzHKV2Gj3mEzQNKPnqBegsiSuU2W/SFTshZ1jCyoyk9ZNw4lFaXkuL1K8Zg3unBTSlEw7K4lQ0Z6LPidWSqZktKnYnJVtZbldZaC8eVzMC5uH1vhcphyXZR+UkK0NnKGh2ThNIgGAdCPYytgjBuHpC7QLGo/hytTf//3f49Of/jSKxSK+8IUvwNASP8MwzjmZOuszvuKKK/DBD35wy+8/+MEP4oorrjing/hxjg996EPYtWsXPM/D1VdfjX//93//UR/SJCYxiUlMYhI/dvFIvE//6I/+CG9+85uxubmJw4cP49ChQ/zfAw88cM7bPevK1Lve9S485znPwf/9v/8X1157LQzDwFe+8hUcO3YMn/rUp875QH4c4+Mf/zh+53d+Bx/60Idw3XXX4c/+7M/w7Gc/G3feeSeWl5cf0jYMw2RmVh6FXPovLTRVI7RcYSNL2F4ka6/xCtWwTDiSiZPLFZdZrsMlPZvWKlcUuHlaM8NNo4T9wrgBcuUUN48alsmrolGnx35ftCo2LJMrXpZXQHm7WIWTlgyylI8rzzKkp9bltvpcbWDoZHm/1kTsnlEfiMN2ubRP0Eka9Mc81+gc9CoVwRV0HoDSsQIUozHTTJMN11N+YATTVJSNT57EzGTT98tl+zBie4hSswifIFAZSThis9epfQ0MN6T/n1zNV3ctcJXAKChxSrdeRiAFG5OhgElqrg2bmoE1XSNQFcKvwmtKDTO/qMEMQzV2soqGQPMsC1QTMjU8t777AArzt4nxnFtWFbMHRWVhsNbmeyMJI/4508yFSY/J8svMjNKvM90jVqEwZivCgpUSurZnTsCRHnm5a47fG3I8yMqlUK+g84D4XvuBDsqzyvgZGIchS9NFrhAONoYMEVU02xM67sqeHWy4e+izdwEAekfXsOPZTwYAuLUmjII0xiXjateHmcmqXTJiVh2yTJ0vXU/XG2O8UlWOoE7DsrAprU6qrSHulXDtzYc7AIDGd47Clf6HdsnjMbS9VbhNaTtEjeCVOov4FpZ2KR01FjaNFSwadJFpxAhAtB9wNcqx2WvOMA2GrEIJQwYnA1SkfpfpOKy7hXvvF+NqWqy3ZxS8sWtLFT6aL31NnFN/bhkqTWKuyHnNGmt1UQU2jVpcmY2CmK99ZXsMSxIUSrOCEBP1Bqoi3dpQOmdUtaxYqjUjz8aYwKdHnmYMuadxyppvpI+XP4J2Mj8Ko+OH4336UCKKIjz/+c9/2MlyZ311rr/+etxzzz340Ic+hLvvvht5nuOXfumX8IpXvALbtm17WA/u0R7vfe978eu//uv4jd/4DQDA+973Pnz605/Ghz/8Ybz97W9/yNsh93qj1OIH2qrUldxBLF5cRjJik2F7+x409gpWEUxLsF20MDWWS57EsJjSTj1KMbPLgHVmVpG4oNes8oQWDxRMaHkFfrnpiVnMkKPJiZthCgFRu1xWxp+2A8hkyrBM1HYL13n3gGA+mX5VJSg61VkT5eTkM02Z6p6OVFme+qB0f7UhVBJF5XwAqO0kAcLtClKkF5dfQU7XwLQ0J3gFyTA8k0TIElWOJ0YhJSeGabLIo1NSfmFM6/eL/HdxCOL3U3vFuLmNumKBtVYQnxSwa/fQCu/Da5KIpNaPFEcahKReOgx7BV0FzWmsNurTsItKroDMlwGwtMPGnSdRWRIvvFpZicqS0GH38Aq/mJIwYVVnf06pvLP/XGFc4ZyC+5lqyiA3G/TG+qvEDiJAissahglDJijZMGATX4KC3GoJ5W3iPhm2Q3RkDw+9zLI4Yc/MNEo5EXbKztj4iv3GY2bGdB1KTTGuvZU+1m/9HgBgToP58qK63pDMQyR9tWAKulqPjUwom/MoUMI5GnJ/lemJ8yovBqgsCAiqfH8bMwVxHa+YEQnU1EXzPO5RT0Hf+rXnfiRNcNJqzDD855LKfRiMLTjoZ2baFTxO3MKWywmUaZmcWDlyLIdRilP3SR/Kog1/VuyLFiVu9YQS9SQIDSJpocQFlMxlGV/nPI6VRAYx6EZDldScATozLJNdAQrVAhtaO6XimOgshX4fqn0FPAYKzg3VopDux2HAC9gkHDFjLxkmSmRYjpvjP4LefD8CmO/hep/+sHjJS16Cj3/843jd6173sG0TOEedqcXFxcd9o3kURfjWt76F17zmNWO//9mf/Vl85Stf2fL50WiEkfbC72ovpklMYhKTmMQkHmtx+nuuUCigUChs+dzZvk/PJ9I0xbve9S58+tOfxsGDB7c0oL/3ve89p+2edTL1l3/5lyiXy7jhhhvGfv+P//iPGAwGeMlLXnJOB/LjFhsbG0jTdItWxdzcHFZXV7d8/u1vfzv+5E/+ZMvv7aLLq5ys11bsHM/fAvPlbhGmL+Ch3PaQS+0ac7gJrArfq0zCLLnrCRgKAvJzKqK5maoYeZrxyidLM16tkuCe25xCodEBIFziib01ave48kSRZxk3Tg5aQ3SP3Tn29+a+BuafvA8AUL94LyxflMoryyZX39J1AQvl4UCxoWxV+WGxxaDLTfKAqkqQZYpR8LiylA+DMciPVpV03sN2iGQo9mv7HqbkKpz0nOTgiG1pDEZ1TONCgmT3Mmxtond0fWxf1eUmMwsdv4gkJF0gVdGjFa7ru/AaAsqZupS0d2ZYcyc8cj/a0pomi2KGaCuSsGBqK/c8VAKFBjUWa9W/FIAZ0TEoAklZNt1WFsoM52ZxskUk0rAMrh5kgx43BlOls1CvcGWq/UCHWWf+nM+CjXSfA6p6kHQ3+dqWFgUEbM8sjsEj5PfI3w16iO4TkKM1s8iVjGzQ40ZlgraTYcQCnZVtZcSBeD6ItWdYBmrL4rxMy2QItlAtbGGPwbSQyKrMsLXJ+1D+bTYLlOajUFVFJMyXOx4MS1aeUsXsC+77HleHiTWpN+GnYcR6SHRvR70BQ7Q1x0RRbnf+SjFPVXfOM0wYByEfKzEmAQUdmtWQtcusYl01oJP200C9KLOgx3MPPdN5mnJ1z2vW+F6P+xEL6JKWEoaK7Rq2Q64E0vl1D60w69ms1Mf0xqgKRRUqw1YklzzqjVn9AFuZmpYz/hrMohSO1HYqVAsozcrGdc/lMSDyQv/BPm+rNNuAMz1ekclHoRJHDgMWP6axGq6f4msc9QbciJ9rDfl075nTWiXzAocQ7Tx3Rh59d2lpaez3b3zjG/GmN71py+fP9n16PnH77bfjqquE6Oodd9wx9jfjPM75rJOpd7zjHfjIRz6y5fezs7P4L//lvzxukimK0wc/z/MzXpDXvva1uPHGG/n/u90ulpaWYBcLYzCKLXs67MYs4ItkKHOk0nOWwIjliy8eKfqpoSi3uhJzcY9IYKzGDL+wXAnzmY6tlY9VHwZPUlkGoANATNq941KkcWPID7opqbtetQBPPvDlWR+OR5R2qcbuO2zEansu/GWRrNjNeUXrly8+Q/Ody7OMX1jcxxQOxsQUSXWcWYy2yy/0dDTSaNwhYmney8ev9cUkQci9KpkGF9Dv8khNiixsqlH9xT4k+7E3YHkIW45rfc8iC48mgyEbsXLfWhgxe6y6a57FIwmyzMIBv8QGa21+AUwd2AF3UbCzeNy0SXtwcoNNlen4HL/ICZLjK+hisNbml8X0xQLybOxf5uOO+4FKnOR3LMtS0genFNRF/WjlxWk2fV54shLqrF52KbOzSIR1eP/3GB60PRflHfI+mZc+bpkSlwU08VL5Es16bYxo4l1dZQNbo1BEKseDvO1ijZ1muRYcqURPL7NkmPD9Ylom39+OZzOTcbQhkk/TtTk5zqJkjNkKCMNg6gnMohCju74FAHCpT29hH2DJ/Rd8hrEs18FwnRZB4tpZnsPHHbaHDLdSJMME7QfEuW7GGXZIeG/6MvFSKy7M8TPlVoYsoKs/Uwzjpw/AlP6fhu1ucRfQe7rS0Uh7Hnpj5w8IWJWSftMyee7hTZ0M+LkctkNmu1K07tnA5mExt+189gDFy39CHGtzXj23ZKgdhWq+6LURtcR10ntM9X7JMYNhAMXpEqoyoSzUK7zIiXoDbB4SSdCp74ltplHGx237Hi9kLK1/TIf2KIkKHhT/hq2ukpyIUgV/lh2eRyvbxbay5iOYTOVnVDo5q+8DwLFjx8bMgs9UldLjob5Pzyc+//nPP6zbozjrZOrIkSPYtWvXlt/v2LEDR48efVgO6schpqenYVnWlqx5bW3tjMqq36+8OYlJTGISk5jEYzGq1epYMvX94mzfp4/GOOtkanZ2Frfddht27tw59vvvfOc7aDabZ/7SYzBc18XVV1+Nz372s/iP//E/8u8/+9nP4hd/8Rcf8na8+VlYiVrJ2rOiIduc24nclRWpM/mzATBoRZVnzCYiuKt7aAWmK6C/YqXOVYCChKsqwZBL+6Zp8go41VbVitmV8OorT3OuSFFjpj9f56Zby7W5NK+vTGkF3D28wr+rXOQr7ZhSXZ6UoXSo0gi0OCKYLQlChgsc3+NKHkNFWYpMft8qFLjiZmvwSNhVvWv1veJBnb3+Wjg7hQ0I20sMA3Z5z4Ieso5YTUYSthqsKljMrZb4e+XFaZSeILTY+PygaeIMlKfaYE1WpuIMpaYYz1GnNwbHAkBZ08Xx55u8mjYsE4mESJk1NxyvyNHKd/OIuAZJmLAnIKCgyPK2CpoSVizvkYKuWlO5na0wxElVvfKsj6IUIDUdG7GsfFLlzatXUH6CqCLke67hpmtz0IbVW5MDI2GSiz2UCYqsNMauA42fUZDXs9ZkGJurI5st3lb/yAm2vLE9l+/FVGu01puu6V4mTSHbs1Goin0V6hWuGurwUMisUBdnEiElb8rK8hzsqqzutdvoHRW6YCXZT+I/AcC8VGO2XNXo3aizzQzpoaVxgkSrsJAQJsFmwVqAO9vi3rIMYO5yAS03rxL3ttVcQNZV1T3WhEozxPKeI5JKnmUKmusOkJEnJ4m/Wsr+x/JcrpbSvZmlyo7GME3VSlCvcIWTjjtPM2av5WmGUTfi60Dn9eDdLbktA/u2C801Y2oBZkXa28jG/bSl7tM8CrlqSBVFnX0MqHuC5rDK8hz/nKcZszM3D61x1Y+OtbGrjumD4ljc7btVc7zGIGTdu80WV6SoWpzGiWabVGAYvOy5fAxUpU5qiqV4oSPLc2TnUZo62+8+XO/THxbf/OY38b73vQ9f+cpXsLq6CsMwMDc3h6c85Sl49atfjWuuueact33WydQLXvACvPKVr0SlUsFTn/pUAMBNN92EV73qVXjBC15wzgfy4xg33ngj/tN/+k+45pprcO211+KjH/0ojh49ipe97GUPeRv2zDa4kBPL2oPofUdAAN7x+1DYL3BdY1okWLAs0eQCoc7NjCfT4j4henk7vpJDKPQ6cKSisCN9v6peCb70VIvaHYZXiGafp5nqw+gGDH/YRZtL8NRL4C80GW7L04xfYjp0QBP0cEMxiLxmTfP/Ey/G3PE4eUSWKFbOgBSTh8zuKu/ZpXzMZOThQCWZWQrTkRIDjs3QVCa9tpoHmpj/ySeIcVnev9UL0bKEKj0E/ElsOE++3HvH1tC5T6ykbM9Gbde8PK8qT5rGSSGWWKhXWJBy7MUr1apd30FJ9hDpUhQMvxaUL51tO2PCpDTOqvci4HMRkJ5MdCW0kacpJ9Jha5PFQkfdEcMfpGZtFH1gpPZFyR9FZXkWJamujSxlY2dOFqMEhaNCONJ1PZhVJQmRS5YqXeOs21Jeb+GABUcJXs2jcMxUVl2vSH2ODIur6sVDCQEAToqcksdj7Hsuf54SrKgXcL9PddcCJwKjTm8sCQPGYaPYDZnBxh6QWt9IGkacYJCvY3zifrhkTF2qKzHQWhNesys/K82FB0NORBxPyQ0QC3HYGYHsFZ9wURO7fk54yDnb9/Ix0Bjrxrp6YkTjYjkO4KvjjuR9RpBjpiWWdtFRJtFyLA3ThA6gnckPj5JBy1XHYjnm2LYBwPFd4JS4jsHagCU4nDRGbo6/xqJWi58JvceMth/1Bpz4CRFi8n4Uz5rbqPN9NDixokQ9Nwa8rbKUcZi+fDvD0UbRV/2UqfSFDAdKfb/TYQi40CAhUJf365R9nm+QpUg6ktUpr3d+mvTEhYxc/nc+3z/beDjepz8oPvnJT+JXfuVX8IxnPAOvetWrMDc3hzzPsba2hs985jO47rrr8IlPfOKck7ezTqbe+ta34siRI3jGM54B25YrgizDi1/8Yvzpn/7pOR3Ej2s8//nPR6vVwpvf/GasrKzgsssuw6c+9Sns2LHjR31ok5jEJCYxiUn82MSFfp+SWOfpjEEA+J3f+R28853vxOte97pHLplyXRcf//jH8da3vhW33norisUiLr/88sdtAvGKV7wCr3jFK859A7YDqzbN/5uGhwEAm/efQFVWWAr7JWw1NT+m38EaNJaCbKjSU96xjlN3CG2b1le/gcYBKci3XcAJVmOWhR+N4jqv2gIpgDjSxC/jYMTMJMs1GfKjpvQ4CFGSViaW5zKsRFpLpqO86rI0R9iWrLTWJhzZfMzaO7bLK00jjXlVN1pb522xrcrcsrLZkM2n2TBQ4nxxrEQi44RL88TUqSzNwaxq1h40jnrTu24FQfpTEl4qL06jf1xUnk7d10Yo4ZX67iZXNXRLEicmBtNIVRekno3l2Ihlc7TtuVzad+W/hqsqU5braTpMLcVS5O1HY021VDVkVl6U8GrX8T2UpmVFwXfY2mVMHFNWMoLVFnup+bOSCbc8x/dRutniCiTdA0kY8cq/Pr/M1T1RRZLjKatgeRwzqzPdbCn9IBlJv8/n5TabsJqiqRuajg9dO9v3mP2FLEW0STY44t4zLVOJV2rNyATpBGs9riL4i9O8rZJfHqsKAuMsL7Q2ucJYvURCvbUm4uP38RgSrOMvVtS5rYp+U7PSZasRw/XYrsh02/xZVXW0kUqtuN6D4lk7MUxwUV2M997nXAZvj4Su5RhlYTAGETPL8Ax6S2kc/0ALkzTOWBdp1I0Qk+2J3L43VRvzbiQ4LY0TpKG4jwjmy9JcI66YXL0jK5U4iOCTeOZCWcGTYZ9FUAmSNx0bAwmjjZNVxLPkNWsM+5uurapkBFMmERMVRu0+ol7I50jnS89MeXGaRYbNUoVhaBYb1p4jp1pFhaybCD7VhHKFLymxK8/g7zkK8UhFlov/zuf75xLn/T79AXHffffhl37pl77v35/73OfijW984zlv/5xVwPbt24d9+/Z9379Xq1Xceuut2C1ffJM4c+RBD0ZDQB9mrYnCNilCGcU8sQO3AhDq4DRhIMvGRCR1WjAgGFDldgcAcPLmu7knau5JAloo7LmEBfnQtFAgtXSNJpyGqrfI05ICogVT2TsZJtoE7zGswqw5z4RF22+HnHQEq6fgNY+NHbezbCEvKBXsVBNDBIDS8hJMkozIUiXgSSbEWaoo3EmkeeRp/oRyQuyfWEeD4ILtezS4YMRjzJEpgVAKxy+yEnJvpY9BS8oCFDdRleNYlC9swzT5GEbtPo8tKYkPNtoYdUUiUai6WPqp/QCAysXiZWgv7OQXSLrZ4he6YaveChYAlS9IcSwuXxu6LuGpTe0aZdw/RS8bQPV3GZog5ajTR2lWfKa+V3qfbV9iWCoNI06ge8c7cthyTB2gg3GUirxp8Uswk9fbrs/xiyldP8EJMhl6jzoqwbFLHogPpicf1G+ks0IBwJHPCl2DPNNg7F7A/TQEc4+6I36528UCL1IMy0LaEn1/DDmWqvw7y7EZ9iFIPe11mM066vQ42SIGquF6PN5pe23MxJdMxSm5MB0HBZn82Z47Zh4NAPsWK9jzbDHg009+whirDJAiliP1LFCiS2Oix5iQp2kyTGxxUpQiIWPsIOLFiiGhO7fiw2pQD1pB3f+dPoZtlaAAArIkxqTlmsxSHJ6U39mMWK6jtDDFMiRpa5WZwHxO03Oo7iQZhJiV7k99T8yBhepJ1HeLa+AvzvAYkEMCegEnylFvwD59yTBRLQ6yv9H2CgqWLfoAqdprHn00z6abLRjynjZtKS5rmZzwjdb63JfmVkpjfZ4AEA1HeKQiz3Pk59EzdT7fvVCxZ88efPKTn8Qf/MEfnPHv//RP/3Re+coFk1R9NA7mJCYxiUlMYhKT+MHxo6pMXch485vfjBe84AW46aab8LM/+7OYm5uDYRhYXV3FZz/7WXzmM5/B//yf//Oct/8I6tNP4kyRnjqJbFY08BqmxeXhZBAqOxe5avZWWlx90FekbqWE4oysbsmqjeF6KMyLhuj5Jyto0K5L7R3bVY7xtsOre6r0uJ0eQ0GGqZpTR50+LEd+hi0XXFiychUHIZfFiYmjwyBxmLBTvF1cRWmmLvabChgkba8p+AZgCIksNMxShStEeRLzCpDOBaYFaNY6ujcfH4/UuOmv9BAcFdUgZ/s6V0WooXncB+5Mzu8mN48WG96YblWw2gEAhC3JamtWVJO+bpNzBhglDmKGyaB57HHFLY6Z4QYATkPAjnZZQoPdLkMHgNbwLn813OgxXFdeqHKlJA0jdL4nKoVUYSovzvB+SzN11HaKa+PJpnOz0uCmW6da5dU0MSbDdohAsh5rwwCQBDzD9ZRopS2hJhswa2IWtrKMqzXEBB11+qjtEVUfd+9Bhlup0mLZDjJ5H2S9zpglDUGk1BytVyrDVpebjLvS127UHbFwpOW5DENng67yX6PKbpZylap62SycZVFVpMpb0lrlSqBbUWKlY5CQvOfSoM/XPg7CLfYlju9xU7VpmVyVnD4gxttyLZQkuzJPYmUzRc93FCph1HA0BvnpHooUBIV6XpUrOMyMDGPkqaraEJmCqjemYzPcbXkukxPScMRVLBKk9GdLsIuikjjcGHD1mq7BtidtQ2O/aOQv1CuKtEA+hqcF6bNVlua4Mts9Sh6WCUOOWZQgSsliS/2OGICjTh9O2ZVjPMVzHo1B5/4TfF7lJBqrYAJS4Je8PIu+mqfIXqun4NtRu6+qVO0enwM/U2c800k81Hje856HL37xi3j/+9+P9773vSzDMD8/j2uvvRY33XQTrr322nPe/iSZ+hFH/9gqalJSwmrO86SnU9ppwtTx/dHqKbTvEdCC4zvYfv0VAABf0vvNSp3ZH2apwpAJRR6FyF1v7P8Bhcsbpsk9NpbjcAk813qIStNEHVc9DGE7YFVjEq50/CIz/PoP9tGR8GBpQxm2Um/R5r2HEHe/K7bbKKOo9WLxZ0ngs6CO/0yhJy2ma/NkXWzk8rjcsT4J/jzBRkVfJVSjkBkq3GPh2vyyqS43x2Qlhi2RjBCV2lkLMLU3keNV4W3Qy8L1XVauHm2OGGLJ5GSri4Zm/Q4nlDrLj+AGJ0uZyTlY72wx9MyzXPl+eS6LKQ5bm+ifED1g9PK3PRcl+Xf6Vx8jQMFdeaWufPSImeVaYwrThlTzz4o1ZO441duMh8pPL4l47CkB8rcvcKJiVhrKA46MwPMMIJ/BJGLPQUB4VQKAOyMWG4UFxYiMg/v45U3U9IuedzWmnv4z4hya25D1lAwGKeSz0vcoVOKzlbqS+SBJE9thiQPTsRV9XlvAsLBjmilJiChheJ76DEUCJe5/f6GJyrI4H4KND3/+EE7eJhLDXT+9jgXJVmXz8CTi7dtegZO1OAh54aEH9ZNZnotUMkDp3jBdC5lMoITchrj/yGPSX2iydEkehWNyBNRzR8+k43sYyXMctkNUt4tznLtGsBBru7crplsSMcyXhwEyel6J3alBuOI4HblPKbvh2rywMSwlC0OMyWKzhqI0jjZdB/mKuPYjTVKFxHgL9bJijtqu8ubTEnmC+Uy/oiQbZEJruCo5tjwFyWeaBAadSzgah3QvdDwKi0vnHddee+15JUw/KCbJ1CQmMYlJTGISk+B4LMJ8FzouWDL1cEvAP1YjWD2FwVEBrZRMixupk1AxR4qyQlTeu1c1O1oWWxvEQQy3Jldd2wRbL3PLMAdixWUMeoiPCQFPKiOXFjpwFsVnzaKvhBHlispynTE9JF33pTgtRQWJsebY7N0XBzFXPajaZDo2W3NkaY7pJXE+Sz+1D5UDEhKRKzKvO1BNzEdP8iqYNHsKerUoy3i8uLKWqAbbPM3GPOJMh1bBYlVbnGmgtCygA6sxCxTlKlpjkRlSC8kwO4Cu6wXRQEwQmVvxuXoXByFDJcRWGrQGDGl42spXh/7oO8VgyCvfuNMR+3rwMB8Tkkit0iEERcWHJORZ9Bl+DO8+gu5xAYVQQ3WW5lxRMCxd38eG5YkxItjW8YvcxJwPA2bF5alYrRu2w3BXHqpGboJUq9sraFwsmL6mX2XRWSMawoqk+KSsRiHPgFQ2XBd92AtSOLQ+y8fK52iayKXvnJGTZ1xPeSiaFlf3qKkcEP5pAFBYWGQWoeXYfM82LxL7avzU02AsiOcjj0cwHFk9aC6MV8IgIUuCy0yTPTMprFoTBR2GlvcvXbc8jlnsNOqOs+3oPkgl6WPjnlMARPWwvqPFVSBmHs6V0JHV0GNfPsJN4zNXCrKQWWlwJdEMI772leU5rtLqcBeFEMsdjv0dAJMXigeaqCyLZ7ROUCyxKWXQvmy/iKI1Xi2NugN+Vqb2TbFmVSDh17DVVTDftkUm3OSjIUAegeRBaZosklrU9jtimxxV/aO5BgBb/pQXZ7iKRi0WgHiWCb6m+bCxfwmlJ/yU+EBlGsZIbC9pSSXvLFVVXNMCvxWJHGG7sHxVaaQ5U/cSpWubPsKVqcdb3HXXXXjOc56DBx544Jy+P2lA/xFHMgj5gXZPrSufs2CovO0qijXERsiWyYyS2p5FFC4XpcvMk8q9holMqk3bCzvh9qjvRMI/Ky2UCR5qzHCvFE2gpmNz+Tnq9Pm4bK/AitcEAQxbm/wSHbZD7kkyToOXANF3sP36ywAA1aufzBNNKicf2/dQXhRSEWGry8lU537R24T7TzBs9f1gQOr/Mh1biSk6ISdWtkxOK8tznFDmjUWk/jj8YiQjlZCGPcXm03ogCLJxsgyuZHR17j3GNHH6d9gZYbAhXkbNS22GfWi842A4BkuS4vWpu4RaNu46wsfvNaso7xJ+dYbrIZVJnkkTdEHBp8HJAKvfWYMepakimvvEuPnzU3AkFBO2NvlFSf0a3uI2IUEBwUayT2M05kmMnEyEV04ynOtK+YnqzgU2ts6GAXIpfWDofXp0vfwK8oJkFBarzADlHjbTUqrndoHFXdk/MRwo9XzXg10qyq+ZGMr+Q3pJmo7NL1wd3hpuyH6lw3eBuIBZr8NsvTzLOLlUcLMab9iO+j1Bf/UZmGldjRctXALyZFOQftQdjB0PvVCZcVl1MZT3UXByMGY4DQhY1Z8j0UwDAwlRDRfFdfGLClq1S0U4TfGsWY1ZXoSM5MIrDob8crcch58xgrZNx0Z1p3wW62W+Z+g+1KFzPTnI04zve9pmdecCC1kW6hX+LPWyjTp9/jmNYiUMapkM4UJjdRol6XEKoCC3RXNBGsda0u/Ck/MNi+baStG+OFvn6xEFEQayhYHgSXdGeajCNMf69ADALFWVh6RpKwcLWhQnMfJQnItbC3m/et8W9c5mG1th2AsVj0U23w+LKIpw5MiRc/7+WSdTX/jCF/C0pz3th37u//yf/4PFxcVzOaZJTGISk5jEJCbxI4pM/nc+33+0xY033vgD/76+vv4D//7D4qyTqWc961lYXFzEr/3ar+ElL3kJljSrBD1+8id/8rwO7PESUT/kqs+o0+OKRNgOmB1Dq31vscXNxnEw5LJ07ZonARUpeilFPbNSgwU+c7sAZ6eEy6jptq1YJHkSK50nyQwDwE2ecaAsLEoz9TH2FyC0WHor4rhH3RGvjKnxM88yXsl5DV9BW0MFaTAjq1BAcUbcll6zpsrtEmKIugOunkTdAa8wKZIwQiaPm2A9QOjNEOThcYVqnq16kvIMUskqI4Ta1Bl8SaSahEn7p1xXnoCmqeCb+BBaUtNmXVYRoixHSQorJkHIGkNWRTaNNxQckI9CruoRfLpx50lEfTEW0weavDJ3NT9MrspkKfvGhe0Q5RmxrylZjaouN/neKS0u8Go66g5Ya4qgGrPa5HvO9CuwM+U1CEiWnDZOw5YYo+CkJBnMbioINgpVBVRjYbEfpV/hbRnxkMebxpjYcYAQa1TaYkQcMMeOBVqFkoJg7jzN4FYF/Ddca7MIY23PNvGdSgO5PMZk/QQ69wooPg5CJmYQK88ul9VxF30YUl8qr0oxXtsBEpuPle4fGpdRu8cik4lWDXIrPgyPmHOiSuF4ATJJWnDKDovpkvir1ygynDtsh0oUU1aC8jhW92kSs1aXOM5xptqo0+exK2+fQaEsq950rhoj2LAdVVmlv2s/Z1GbK/BZHPMcQuQHy3OV3VLBY7JFoS7nBdcegyFJgy/Rr4dsBTBNC4CqoFITvF0Sv4s2e6qtoFlThAKyjjItvjame5SP27BMJt1UJavVrDaV/VU8RCaPm6uTtVlkRJRIExjpeHWbxo7Om6uhSczXgVndg0dOZ+qxGO9///tx5ZVXfl/j5X6/f8bfP9Q462TqwQcfxN/+7d/ir/7qr/CmN70Jz3jGM/Drv/7reO5znwvXdX/4BiYxFsNWiGhevDSKs3XlHeYX0F8RL8RTd4uJPM8yFKWUgOnYPCFZtSaygnh4MwlVjTIwHcMrlLkUTf0ntjap5lGoBA5JUTzoMstl1OkzxKR7ntGLabByitlQlmuh1JReU1I8MouTMXYNq5KT8S/GBRCZJTUMYEkWolMV2/d3enyseRSyMnr3kIBhukc3cOp7AtqgYwKA4nQJ81cKaI3MfO2ZRdUflWc4vc3PyDMg2/oSUgdtsaK33gszWGsjkGbIqSx3Fy1DGcBmGbO/xoyQe+Jc09Eqf5YSwspCmfs0bM9ltp7luVvkFdJehydgr+Fh7y9cCQDMTjNcj2HVrNti5fVCvcwQLr9QD92joJ5KXQkk8ovXYoaS7XvM5CQWo9fw0LxUJFaWljBm4QCb9wnIzy6K0npl1xLs+WUeF2NKvLBYEX8UMKsuj0KGCSnyJOYEKBv0kA6lYa82PtR/Eh5ahePLpMT3tpx3vH6SzzvuDjhxKkzVWH6EBELzkUoSzVoT5ow4h8yTL9QsgSl777KRShLpWKPegBcAhmXyNTcdW8kREFMtzVg0lyC+sTFIMxa8TMKEEyvLO/PcTAlpNgz4/tVZd6RgfibF+bHIUsWwo+Q5DMYEV+kYKvWy5hcp+5iyjOFcw3G4N456/0zLGjObpkVU/8QG2veLe7mxR4xnbe8i7BIlea56RmXfW8Gvqn65WnNcVgWy743ZzUMU6mJu0c3BadFhWBY/t/o8yqr+hqH6LrX5hMKwHYaJjSTmZ8nIUk4e6d8k3CrPcqEiz8V/5/P9R1vs27cPr371q/GiF73ojH+/9dZbcfXVV5/z9rc2tfyQmJqawitf+Up8+9vfxs0334yLLroI//W//lcsLCzgla98Jb7zne+c88FMYhKTmMQkJjGJH20Qm+98/nu0xdVXX41vfetb3/fvhmGcV6/XeTWgX3nllXjNa16DqakpvOMd78DHPvYxfOhDH8K1116Lj3zkI7j00kvPZ/OPi4j6EWvI1CA0TgCxOiT/KrJeWP/OEZQXRLWoONtQbuLZN2CfFN5eDnnvzexGVpYwg2khk4291Dybrp/ASEJIhtWDU1EQCgAMVlvYlE3fcRByw7RhmYhk2ZsaQoftkNlbru8w209nptDqyvaLStumtaEsUKalDo9f4YpDOgwUVOMrywhq3I3aHW7cpX35sxVYjiyPt0MeO7fscmne3SZ9JG0H5khWCexNhkWZfXMaK4vL8cQaKni8Gs/CDqKTYgVLUBcAzEuIbfGJ27D002LVU7z0iVx1ISZa1j6pMRI1PZ55IbJa3TnPcMNgVXngFWcbauUqK0y6H9ncE3aismeH3C5p8wzYA6/zvaNsdZKnGUMlllzND1ubzKgq1BUzj8Rf9YpE2NpkWIkaogtVl6sPWdBVgqtpxtW31h2H5b66mH+GrLaW6izmaSSywpiMGNLTq1J8XsOAq51Z0B3T/aLKKmlehe0h0lhCzLq1TJdsSBK+50v7LmJ9q7yoQQRBRxzW8fu44dnathcpPXcyjDAUxw6I8z+twun4HhMpkiDUBCOVcC6NYXG2wfc66SIBStcrSSOtgmlzxY1FfSt1VZHebDFb1I5CZsjR/dS4eAdb4tiziwqGJsFY21EaY5r1UybZdXG7zfdisHqKn1VbE/Hl6nqhwPBh0lX3r85s5PG0TK7YOX6BWwxWbxEVziQc8bXzmjVYkA3zpIFWaXB1TbdmokZxuzmvPeNFblw3HVv59MlnsbTZ4mqSWfT5ueaqZBLCkNc+Hw0U+UBvVNfmFYNg8Ew9H1QdtNyzrn1MQov3vOc9GI2+P1R6xRVXsJ3PucQ5JVNxHOOf/umf8LGPfQyf/exncc011+CDH/wgXvjCF+LUqVP4wz/8Q9xwww248847z/nAHi9huRZPhLZX4KTGa1a5z8GtSmPgdoDucTk5rfXgNUR5OL/tfvadool0z3MOYu65vyx+N7ePTXzNuuwr8CtIjouXfxyEcGRPEk2kUXfATDpSKwbGGXrUE1WaLrLqMaD6M6gXzPJc7tHx6hU4kg0UdwfYPLwiz1283JtXhbAke8z0q6yAzr0XvQ4SiW0HKyqp4GNybBSqisXV2CfOd/bqA3C37x7bVrp+AllXwEZWYxNGU7LWiNWnJVOG48CUzD2eaC2LIZu0tcrJpy46OH2gKfd/0VgSl3cFvT2V+9f90nS/PZYlGIXoHhZwxqn7NtCQ17myPAerICb7RHp3pVHCSZhb9TE4IcbYWBF9JqXt27g/pNisKQZpOOKXd6wJBtLLW1fJzlsb/DlK4von1hl6qu8Qx1/fu40Tr3wUYrguzjcNozHqPSBgYVvCnrlbVONPfXVOEWZVQrzDnmLDEWwWBkgl5BK2lP+gHvR8GJbJIo6FeoVlLQg+yqKEBT6dXZeKHkSInkQzFp8hhl826MFZEslWVqwp+QYp/WCOgvF+O10UFkBxJlVSFq1NDO8Tz3jv+CYnEdSHqHvpFRqK9ab7aBKbNmyHGMpeLJK08Cp1BdG6HhKZ7ETdgI9BbTOC5YtEO9XEYbmHruiP9fmRSGrUavE2KSGwHHsMqqREMDnDNUrDiFXFKfJMMQDzLFMJo1/kPiaCmMl1ABBJD0G0HrUSaEbhaWuFE3xTYzpyL2c6nvj2JXyfDO8X+/dcVA8eFN/XEk5aABjRUJmwDzRGMIXtqLYFbYGQhspXlM+18MjJQj4W2Xzz8/M//ENa/MM//AN+4Rd+Ab7v//AP4xySqd/+7d/GP/zDPwAAXvSiF+Fd73oXLrvsMv677/t4xzvegZ07d57tph+X4dVVv4ZbL3MvTSFW5sGFgbQJqfRZM6d7vMdNvnbR5gcu7IiHeOXr96G8eBMAwH8ikDdEY23uionHai6gNC+2NVht8YuHkpNRu8ereX++yT0CWZwgS8f1r5ySx3038RlsTGp7F7nJEwBbZ5h2B5DJVOuu4/zn5hNJ00e7+TV1crJN8ZrDMVd6QCQStBoOOwOmurfvOoKqTARIkwumpRpovdKWylQOl6sjZqn2AzHxPOjyC7m+o8YrY9LHSqMY3dtvAwAUZ49x0kCrYasxy4kAeh1uUKcepSToIpA0980jm9wL0wiGcMqyGV32s9nFgrIcsR1+MVGyF5zYQE0aFRemp5QERk9dO0tr3qewiy5XTSJJitD7a/I0Q0Wa0ZL6fWV5TvVJRSEna2mcYEjWGZqydCqNp+2irxrOSUcqCrnBNwsDXuXnp7+gAAzXOtg8JJJPXZ2bdLSaF2/na5SnGR8LkSO8ZlXZxeSZUjM3be6BoYqc4fmcGOVQ2mSm1BzK+h1O2vM44uOl7VueD9NXY2/LSuCgNWQ5DRqj2cvn+bgtz1Xm1bJHTncgsD2b5VWo4ma315W0Q6XBUglZ0EPc7Y59Nlg9heBLt4txqRYxc5VIGIt7hZFyXqkrvacs5SSL7kfDNPl62yU1z+Vppixp5BgiGK8+UXCfYZQovaUwUnIF3QBZSo4GpCNXGEukdQNvOlZevGQZ98CRFUxerKo+J810WhyHOJ6Ne2TCGNyGJXlcjShUzexyLNIw4J4q/feG9nzlmuQK3VPJcKR6SzW5mkcqHotsvrON/+f/+X/w5Cc/+SGbH5/11bnzzjvxgQ98AM973vO+b8P5tm3b8PnPf/5sNz2JSUxiEpOYxCR+xJHjPBvQH7Yj+dHF2VbXzjqZ+tznPvfDN2rbeNe73oX9+/djYWHhh37+8RylGZ+Vfe25ZV7FO7YDq6h6gwDRI8HCk55SbY76EUNx1e2iWjR7xTKLFiarR2HRClCy+czZZahU+A607xb9Bv3jBN/E8KRit5NlbFabpxmrE5PInmEqfysA3FdTPnAJAOELxn1QvQ73C+RZyj0stJpu3XWcqc5lVzH3mG5tmlwFcKsDXr3pQofU4+DVS8x8Wr3lCFde5q8VlVR35x7lk+Y3kMnKFPU4iIGSVSrL4VWjLuBILK7RqU1MHdgp9rswxz00OjzZPyIqQ+27jqA0L47Ll6ueLOghI1+5KIRNXmoyok5/jJ1Iq3DbKyh2lewHiIMhs/1M1x6DRwDg1L0PYiCvV2P/EvdJlffuVcdNxrubLaSBknTQq1eAYPDxUGkMU+r9G5NuSDNVmQojripSf9Udf/dNdP7ffwcAzC3XsONpe/kYAaGobWhQDXskEjxjVmDLSkm5O+DK1PqdG/zZpevEtmp7FrlPL09iuE3qAZMQ13CA4f3fAwAM7/8eClMSdm3OI/PHr62heVya8QAg/7VNUWVL2+vIZR9RnmVcbdRlNajfyA66cORza3s298lQxa9xYAdDwGFrcwtUCiiYz/UdlGQvlg4jZiviPvOaNbhzC3xeVC3h9oJKiatU63euYe12ARPPXSlMyWeu2g9vF3kl1rX+Kdk/lqV8z7lVn8VbDcdVTg9UDesFyENisNowZUVIr3DoVc1MVlvzM/S4JGHEjMYsTlh+gXvFRiFDb1G7A5daF+Q9n5s2YJG4pnNav5a4V1NZoTr1vVOI+qLiPHv0JKYPip7VIhmBF/0xWJUrUlRxC3pqv0nM/ZKmZZ1R9HgSj964YHXDL37xixgOhz/8g4/zmL3mAEqXi8ZkqzHL0EUKAJr5KQDEgxBhR8BwpmVwX45ddPgzVNKmkjog+nmon8GVRshY2AtzVvYmrRzisvioqzW1amVl5V4fK30p2V8StjbRO94BAJRmy6zYzonEZkslJUnMk0d2BmPVZJgo6CiJ2CKCm8KzdMwMlJK8/glxfoZpsKYVoIyELVfZprDGU3MBKMiXcxrBbAuokexCiJIPCHp7rklJACLRIBuQwuw03N0S7jZNxMfEizg5JV6SQqlZ9qP1Am7GpXO1PJd7jwr1CqyahLZkQ/WwtcmaQrOXz6K2S/YWpRk3EetaXHqSSf00dL3yNNcU2kOlTJ3EgEwOKUGwmgswLJEUJEHIlPPykjTfrjTGJv3TtYaQpSwBkIaqOTrRFLGZhODZbDMStkMc/7KwdTh1j0iKpi6aZ1kLd24BhlRDV3INDr+knGoJVWkCHKwNsHG3uD9Wvi0S4dJsA035cjc1iyKG4CyTx3PtlvtY6qE852P2KnEMBLe5cwsMGxkFX5k1k+ltv8OG1WalIZq5AaWcPQr4JWsWfe4pLFQLCNbE9aBene7hVQzXxbGErU1E3fE51rRMNC+a4eOjxnbuewtCDOR90Ln3GAoyqa7sWmKSByWOcTBUCUyUsu4dm3jfewx1eQ2Lu/cxxZ/msLg34CTVnl9muQAkMUPaBKPlWcaJW55lgPw9JVV655JunG2fQfIhDiKGRS3H5HmMCSSWxQnOqNNjIs2UvHcKl1pjmmZMnim6Y8QKQMwrRGR48JsnMFgTY7PtKRcBAKqXHGBY1bAdNjim+yHdbPEY60mb7XtKCkIeF8niPBKR5Tmy8yhNnc93f1xjYnQ8iUlMYhKTmMQkOHKcH1T3+EulJsnUjzxKl1wFe24H/z+b9EYhwyvUHJtFMSsdl2arvOo0LHMLKybqDpCnoqKQpxnDYFW5WvaKPq+MreYCQ3emXHkZlsFmt3maMaulUK8wDKfUyUOumpQ06rZuPsyRRAyXAQomIjhj2A5ZDboS9GBSg6smokc/J8MRHxdJIAw2hrxqdH2Xt5unObpHRBULX7wZALCQxHD3XyXOt1LnilkiZQOyXltVKlyPG4a5idR2UdgmxtDdfSlQqot9tVe3Vt9i1dTtVnyuelBTrenafD2d5jSv7nuHhGBr2NpEbdes/H5prMpFDeQGCx16qsG308dISm/Qat2wDLgV2Vjv2OMwBjG1iEUYhfy74o4dSrCSFJ4ta0yskVbcBKMk3U0mBIw6fa4+pGHEVVYSOAXAau2O7zBcRdWZND7B9+nUzNyYRAWHrD7YjRnU9yc8RrQPGoPNQ6tcWSrMqiZj2pZV9OGRf5xrYfNIVx7LAKVZUdEimDLPMoZHHZ3hRpINQZfvA6cxoypSBCvbDkz5/azUY4i0NF1EsCaqpNRAb3vuGKOPmXdy+/58EzWpXm9Xq8weIzbfYK3NJJMkGDLcO2x1USPpEFndLjQqTKDQZUYo3EqJyRx5lgFy7rK37RTfv1yZQufxSDV9m5aCZpO6GJc4VucSxUxy0YPub70SmlqmYgnKCk7Uj2GaYh7zF6bGzMTFmKlmea9Z46p8INnNpn8XM3fZRBziuS2TuwObg5v8/Aw2lFlzSk3jXklVTrMMOQZjx2LYLgz5s24mbTo2LMmWpmpwff+Z3UYm8eiISTL1Iw5zdoeCk8Ies36y9hq/eChsr8CMLa9ZZTgtDSMM5MNL8FEcDPklJmi24iVCSuHzgxDFS2Qi4Xr8YqHeJx2GCVZO8YvNX2hq/RdSbTpO4M/XAQjndepDMjSlZOotSrrKTNd0bHhyoiOaeu/BPjYPiSSwunMdJZmAkJKy3idiWCaPB6mujzZH3FuUDBO4ZUqsHC7RU3IRPLgGe1tHbEvrbaAXchb0OJnJ0gylWZk4yT4g069wcmEUSuOrMXqhai8IgiwK9TJfp1N3CX0wu+gwhbusMeSIQm5YFsMbju/xNTjjS8cy+bOmaTKji/qsvIbPfVJupaQx8jpKEZvU6U9LfoniP3aq1MdE7DcoppvQTZJJahgphlKacUJX3yGOb9TwmL3WXwtYZqGyIF7uteU6J/JIIoaudWuaMZsOgnUdmyFxiuJ0hVmO+ShUfWfMGk01NwIPQSK2e2JthNp9Yr+U9OjMMdOv8P1PlijpaMSmylZjVkHWNFZOEaYv+682VSLs+B7rtw02xEu4d3QN9f3CfscwFXRMCUN9/xKcWcHcNTyfFx4Ojctamxm3YWeAqC+17DYG3GdHMiaO7ynNqYsWMCtf6mR07C8vwt0rZAGM2ixymTjBJHgqgTGUC8FemyEu6L1ApG3lV+DKY4w2e1sWG1mUjPVHJVqrAfWO6hIuJIkydfGOMYssQM1FAOBUq/DnJSwrn6WkvQ6T7vMkHoPiy4tSF8vpAAAnT4CE/OSx8ALFHochebEiWw2yLOVFljO3hBL1nQ0DZHK8CB41y00Ab8cjEecrvPloFO0829ixYwecM7Cav19MOtwmMYlJTGISk5iECmknc67/PZpxvt27d6MltdD06HQ6YzIId9xxx/f1Hj5TTCpTP+LIN9eQj8TqJe11kHVks+9ANZZaLJpY4kpOYXpKNa0GPZiy0sGq6GmmaU8NGd6g1X4W34Z5WeHxlpZYu6lxYIfcf4hAsn7SVoDydqHq7C/OsCL2+ncEA9B0LcxcJVazhcXlMe+80yPqBgwzlGYb3GxLLLDyXJerYMkgZDVkqtL1jqqKnVv1uQHVa/jy+zHDEUmY8Eox82xYsjJFnmyFekXoS0Fq4sjqFzVMx90uV/IGrQCVRWkUvEtcG69ZY/ZYplVl0tYKko6oMFIFKhlGXEUAoBqD5cr/1D0nsXa7uPbTF62hedlOcVxyhRt1A1bEFwrQyrOMYGCCep1qieGw0sIU/EV57fbuE+O2/wnIZOO9GZxCfFwIEPbvvB2nviuYSf0VVe2pbK8DEPcGsZS42Xg05AqREfQ0nzMJg3guX6PUc7kZPhsqNh+xrbIogX1YMMacsoPGLtG8PPckwQp1F3dwVWFw9BjS8DBfB0DAWtzQrBElCvUK6rtPg18chxv+o82ealKW4z0mUJpm3BhftEx+hqhKVjmwH/acmHTNSoN1hbJuS+7LZk9Mw/UU5ZqO1TABR/qzFRRL0dD2RfpxaZzyfCCqe+I6cjP8th2KJQihxwWoZ7FQ31SGw60AUUDnmHPl1nLF881EEoimb5pbqCJtOjashiAHOMRwBABobFiCMjWhzHwYnFEbjO4d01GN70pQVlVr03DETfBRP+bWBKq8Tu2fxdRl0n+zOa/IBWdwGECmKpBGKoktUYI8JVPmhBmseisFVXtxWmWqJ83MT94sGI/+fBMF7fyI1cx+fFnGTM9s0IMlf2/PL6uqFlUVu1oFdhLnHIcPH0Z6hor+aDTCiRMnznm7FyyZet3rXoepqakLtfnHTGS9NuL2kH+mCT6LFKuNoB7H9xRFuzHDE1LWbvODnkb6wy1hCs9m6Cvqi231Vvpw7z4MAJiCYvCUtguIIG63Ve/SYoNZVKZX4t9TotK4aAH+TpGECbsKyfyTZep8GPDLtdCojCV8JvcuiMm4umNqzOiVkhFScu4e3UBfTlil6T6qO6b4s4Aw1iURP8MylNGra3LfCUNcC9uVNIJdADKxD+r3CVub3Ncz2BjwtiiRiboD+BrzkGCuLBxsMR/OYgVTFOplGD6J+onvl7dVMHvFsjw+ZUcSSdg37Az5vAcbA57g3Yo/Zh8DCCYnJRiGabGivLXvCeJQSw0YRMeOhgw72cUCw0Xcy+XYbMNTWl5SL2pKmIcBC23GnQ6ySBwv9cLZ5TIn6oV6H93D4utxsM73dXFGGbqS2Gfz0h1oPuVasQ1pfowsRbIhDZrjQzgl5TwI0vQXZxiKtTxXGcW6Np8PLSpMy0SWinsuTzOA/KqZ+aXgmUK9wr1cxRM9pt13DysHgcqySAILS7vUi5JMbysNTvKyXkcJxRJT1fbYVsgwlaGv3htErNTSbJV75NLugMfZbdR5XwxZJrGCLWXYxYKCgC2Dk7U0SpnunzCsVeCk3LDMsV4rQPSi0XxVHfTYeob77VwfuS2tWHzVv5WOQuRhR/wcjLNaATH36QklIK5xLBeYwVpPXUfTgDctnjvqKart3wV7VkKhXoklRyjpj3sDlTSbpmKzEmMZCSBzvSQcMQt2sN7m/WZy7kujVEvADaSx+P3J20VCWl64G4szItF1anuUibuE0w2vhFyyKLOgh2RNMIqT1aPMruT+rdFW9vOFigw5svMoL53Pdy9U/PM//zP//OlPfxq1Wo3/P01TfO5znzsvsfFzSqbuvfdefOELX8Da2toWL5s3vOENAIDXvva153xQk5jEJCYxiUlM4kcTDNedx/cfbfHc5z4XAGAYBl7ykpeM/c1xHOzcuRPvec97znn7Z51M/ff//t/x8pe/HNPT05ifn4dhGPw3wzA4mZrEQ4t8FCIbiKbvqNNne4U0jBhmoxWh16ypioOvTDPD1iZXcMiI03Isrky51SJcuaKiylTcj9FfERUNy1sB5ehOVex/1OnxqrS6a4EFDodHjvC+ajtEFaC2c2Gs2ZyNO6l6AfAK2W7MoEL+a6HyLKNqVXlxRquqmKwB0zsqqh+bRza5STlLMxSnyctQfMfxPbiy9F6ougzpmZbJn6lfJCGAmUX2LMyjIUMitFoOVlqs7xMHMTeb0srdsEz2wytAgymyFM6MsvwAgP6xk1ozuamaTiXM2WiUx2CVgbRroX8BsIhqnmboPCDuDbu4CVfCG1RB8pcXhYaWHOP+HbeK8bpFsBirV10Da6cyIacVsFOvo7Qgxra0ICp+pcUFrkYZjsvsSXrqjYLH+0KWsTApHbfXrLLJrqUx0WzP5Soq3d+257JlSenSK9V2iRkZ9BgSKdQrXC1ljbROnyFofezjIMRQNnATlGX7RXUsvsf+hlw50GAAp1pCTXoNTm8MuSpBz8/6nSeRRcKHdPG6I5i79kqxLVl5ykdD5eMXdBUrlO4Xz0dOjLRIh5Ic1HaI6llpVuy/sX+Z54gkCJWZ+FCcnxV0YZC+1TDg8aJ7OuoGbAlElWVAQFTEfKXKlc4c1BnDVMExHWVjlQddfn6oMgXDGGs2zzUtL52gAIj5Jj5t+3ok4Wjs78zWm/Mxc5WAr8t7hcirWWsqEozrKUhRsnSjbqA1+Re5GplLoc5kOOJ7Mu4OuCKWRSniPlU45TwaJmys7pZdriC2j4txP/z5Q9zCMN2ch10VzwLpWOXxSNlreT4yGrskVh6PVMGMxn1IJ3F2QYWfXbt24Zvf/Camp6d/yDfOLs46mXrrW9+Kt73tbfjDP/zDh/VAHq+RjQbMoNu8/wSXlEW/BJXdqby7ydCCpylRR70Bv5hISXy0OeKSs+O7jPFTP1KhWmDYarByikv31MvjVkvM6rHrU0ikQnP/xDqrKtPfC/Pzmqjm1olQ71HIkxiGS0y3lCEqOu9Co8yTW9hS57spJydiHwEiQWKGW0klGpYj6cWuxYwrf3EapWUBA5AHl1H0xWQGISyarApmHb2Qg9UOw6Ou7zLjkCDJYrMGb3mnGCPde7BUhSUnwlRO4OZqC2lbwHRxEMKqiwSIqOdWoYBMTvrDtTbDHtRXVC66DH3EQcjigACUkas8rrEXsl9lFiGp3ANAjUQRq1P8ebPos2o9JVg63JVHoUpsIoKlTL72ZqUOrymOi/pyNu8/wT02XlNBVIV6hRNkugemD+6Bf8WTxLZml5X45VDr+yGHgOY0s7R0pif1uJ265yT6a+Kecn2HFcRLs5Sc1Dl5tYqlcYYZMMbiMi2TzXT9uRK/SLvHxX4rC2WGm8uL08zio38HJzcwktfe8T2UZI8Ys/5KFcX+DAO+zpWlWZYroHHL4gThqhjPJBzBI2kRmQzmoYJd8yjU5EuGcoy6fG2iIFb9Xw0PxSYxhWvyGpVRaEjYdzhi+QX61/aLzKwdnNyAL/umiH1muJpBbJYqY+rNFrs66Ga+Y+Kvp0FvhqYIbns2KtvFtZ+5cj8KSyKpJnV8s1SFUZRyCJYLk5JXUiK3zDGmpz62AJAHQ8RyPhp1erx4isME2Wk0tSxKWQA3z3IUG97Y30fdETN2GwdP8DxBnp+GYSpALI65pyrX38wk6RBv7UG9UPFYZvMdOnTogmz3rJOpdruNG2644UIcyyQmMYlJTGISk/gRx2MR5tMjCALcdNNNOHr0KKIoGvvbK1/5ynPa5lknUzfccAM+85nP4GUve9k57XAS45GPQvaSMx2HV7u9B/vMUuHm0+kiAFE1GXV63KidpymLyBGjJUtzxWobJgyHNfYIiM1rVnmFGba6XJmilazRKPPqLemc4upBoV7mBm5bNjYbBU9VpGxHMVYI7jMtZicaZjDmyxWc2ODzof3rdjW0Gi3J46eVNKD8ygBg8/4HAQjxTqoiNPYvobwk4bbGLDdykr0DoKwvsl6bbVkYWnxQVX+aB5rc4EqrcYJLAAFh8Mq36PNxp9Tc7RXYy9Br1uBUxSqeGJn5SFURHL8I7+KaPF8xrsP1NnpHRZPzsBXwtS02PC5f08o66vSRZ4KhZ9oOw0IUnXuP8bX1d+9WMIKmf0TjgkKmqjamqRhGY4KsMf+sKk9lOUYRj2fUG6AkbY4My+TKqVuVVZ+dO2ARBAwgH8pKBukCmeY4U03XlwLgRsqHLWz10D7UEZ+LUmz7CVG9mH3CAbH/gqegvCxTpAkShB0oAUWCZ+m46f6avkjsq7I8y1VBr1nTmowl+9JUzdv9E+s8HnSsxZkG+2gCStDRtCyEp9kOAWDobeqS3bC3SWKIFIbMkxiGJpzKrLiBgtN0Zq9TFvefP+dz8z5dO7fqKwgsUOxigv/pX3Feyv+wIp8zuzKFXLaB5EmsxHb7mngrac5ZJiwNUsw12yEAMOOEx9ifb8JpCohG1zajMAoes1VhucrP0VF+ltzY7rk8X2Wy8hMH4ZjXJ0UWpVz5p3vXsAxuVk+jlHXBpi9S5Kv6XkHqMUsV5JYUeiVNrsxi8gGSSFXxk0hVpOj5Gj5yMN9jsQGd4pZbbsHP/dzPYTAYIAgCTE1NYWNjA6VSCbOzs49cMrV371788R//Mb72ta/h8ssv3yJqda4H8niN0XoLpnxoLMfm/pckTPjBJYiO+j0A8lQTD5fje8zCsiXTrFAd8u9qexdZaJJ7Ffp9nqDdSokncN04VRerK8qJNg0jnpgNCSdYzQWGhQBN+ZnYhkmsSuhZCssXx+I4LmxfyizcIVgs+ZE26rvF3wv1CsMMFIVqgV8mpuMgk+dTlOc9e80sSosCGjGLvlLJLvrMHGQYJokZQko3W5wwDtbES3rUHaEue2W2XXcQ7oJgCHXv+C4AYOO2+xmenHrCQU4ukUR8XERrdutl7o+y/Irqp6EkNE3h1OtbxjNtCfbacL2NkMRGTw4waA34GCmBLsqXjeEXWYAxDSN+MdD9EPUCht4K9XU2oM2jkK8T9xD5VaV2XtCMWhnuU9BfHqvrTEmV43tbGJkUdH9zL8wwYOYVoJIoSlKt5jxykhCIh9yDg/74dinYCNlVSSJBqaZp8YsrzzIlrsoCoyOtF6vHfXq17RU0LxZQDcHclufyeMF2xp4x2ibJQ+iJwlBeg4E2LrbnsiimYZoMOa/dLu6DNEoxf6VkV843YaWqD0mcS6qSYg2ipTaAPM0Y6q8slFGR/oXVXQtwyuOJSToa8bXLooQ/S5GnGUOGQkxXPotzErqeWQQKshdsFLKsRRwMeWzpWfaaNb5nAMlKhILPrcYMn1fW66getEGP/Tvp+UaxityRiZ5pwSAZEAk/2v6mghGzbAsUqieupwct5ujeBcAJlO3Z2gJYLhAWZ1SP5vwyck8mvZLliHgIAypRZZjP1JwFZN9bsvHg9z2uSTz0ePWrX42f//mfx4c//GHU63V87Wtfg+M4eNGLXoRXvepV57zds06mPvrRj6JcLuOmm27CTTfdNPY3wzAmydQkJjGJSUxiEj/G8ViG+W699Vb82Z/9GSzLgmVZGI1G2L17N971rnfhJS95CX7pl37pnLZ71snUhWreerxGMhhi0BMrk1G7xwybNEoRky6R9JorL9S05uwer7hL800uzbNlyVRNWZ3YDq8KuSqjNYrnWbaFSVPw3DEoisQzhVO9bBavi1VrOctgWBLycz21D2IVRckYQ4f1d/wq6heJzxCEtfLtFWbN1XeEvHKlf92qz+X+0sIc+4Ax/GNaCrobdJUVSpaxU70u4ser5U6HKwUEoflzPrZfL1hvpYNP5pWxt3Kcx+rwZ0WV6t5P3srNpwvX7ETjYuW3CMimclm1Kc1GcGfktdH8/qzGDJ8LQ1jyWC3PZWHSYE2V+8N2yNCwv9CRX8m4wug1qyjvEKt7qpRs3n9i7HqYJLhYacCk5nWCG7JU+RM6WjM6QRCaV2IWK200to3Rrn0cJrAkvJNnGes1MTSdxBqkZ7FfnSkZULldgJHKaucw4PuMrouuLQWo58Ytuwxjn7pDzF9pnDB5wWtWt9jzpGHEVZfB2iZ7T07t38Zwr74vjixT95f2jLHmlWMzA4+g+SzNxsQpabxsreJc3S7G5cQ3V/Dt/69gDu46dAp7/j/i91QN0u10siTmaitVDGt7FjEnG8wtz1XQdMHj79KzPur0mHVaWpjjqmQk1aPD1qayChrGGHUFvFiRHnfOzjYssmZKIn4uaVwBcOXZXdzB979ZabCnH4dhAgSHmaaqpAddGHK79CxZU6pqlBsmQ2oE89v9Dp+j7odH81oSqspylmZK+DfNmb1IMB8AlGQlsbpUQW2naCtQvo/TmjabKwRa5XEBkhVrbGU86tfxdPuhRyKyPEd2HhnR+Xz3QofjOKxCMDc3h6NHj+Liiy9GrVbD0aNHz3m75yXaSUq+ujzCJM4u7FIRWUdMBlEv5ETCLtoYMgVbTD7FhofqsurToASqvGNRMdSoB0fzdsoHXe4PSUeiXyIOhvzC1UvdzJgpFrjXANAozO2+UgTWyuFlUrwmOjtU0mSXikqI0PXUS2Y05H4cYrXVtX6gzpFNmJZIFKhPxfGLPMFnUYjkwcPiZ8kUsueWmJptOA4L9eXDQO2XXnZhwEwwMR4xjzMA1PcsoHq58B4zK3VWtuZ+o/km/ywkG8R4bx4+qRSp5TWyPJcT1t7RkzCl7AX3qWxTbEDBmlMGy4B4maleMqVoH/VjtB8Qx0UQRPNAE1NSyb60vASzSgrjoo8q6inGmOnY/JIxNRo5M+g0H7M8jjTWppzsNdab8IBUrDFACB0SIzJLc6Se2H4cJgxbF6elOKFX4pe7Wakr+rj0ejPioVoURCELYZLPmUgAxbg6fgHTB8R5udUS9xcSzX3MT89VCQ4lMoO1DvonxLYsx8LMFcJmorJrST1jZ1BRRhJzfyD1BYWtLj8zhmUyi5DgPLeiFOt154G+7CfUY/aSaeyURssL117G0DMltHFrg/cVByHDhKmWXFO/kf6SNlyPn1eHTJvn1TOMLFWil4EaQ3pmRt2IrzMdd7XXYbguj0I2W87ihJ+P4gHxfNlzy+zphyxBPhrwfgGZKNF9UCiOmY2TLIQhFeezTh2mK5Njp8TJCh2LWa7D0J57gp9p3NIoYVkZ0zIZFiXpCHFYufy7geqSuH93PvtJKF76RPEBSiIHPX6W86ALi4yf5fGJ5JsgWLVwyeNYnbu2+JzE+cdVV12Fm2++Gfv378fTn/50vOENb8DGxgb+5m/+Bpdffvk5b/ecvPn++q//GpdffjmKxSKKxSIOHjyIv/mbvznng5jEJCYxiUlMYhKPjkiz8//v0Rp/+qd/ioUFseh/y1vegmaziZe//OVYW1vDRz/60XPe7llXpt773vfij//4j/Fbv/VbuO6665DnOb785S/jZS97GTY2NvDqV7/6nA/m8RhOpYhMQlhZmiOW0IdpGSiXxSp9tClW/ivfWuXv7fnFa+FdLOxBDNdjR/aMmDyDHpfV8yxVDDuLtFoKiAl+CUJeqVOjbJ5mY6Vm+l4aJ9wIncbSdy4Y8t/LjsuVEINgGttlIUFkqfLIylKuntEqfWr/Nl7Zbh7vYuNuuUqXVgoz393A8lN3AgCmD+6FK1eo1LicZCkzwgzXY5gvG/TUudCq1vVAa3M3Slhfx3SVBhR70EUhM72oYbu6a4HPO2wPuXo2d/U+eIvboIcTRszoCltdzWvwpNxXC1NXSDbf0n6uGtD+Tb/CGmClhS5KG2RzM8TRUxLCuntDXpcUyVCKv8YJantFlYq1c9qq2pQMQjgkauj5rAFmcOUpOqOnGf0uHY3GmrapIkXXsLfS52Zdf67EIqoAWOyQRA0Ny+KKGEyTV3os/qr5uRm2C4xL+iDfbDGcVt+/pNn+BMygo2psoV7he12MidRe4mu0CbcidtDYv4TyLgHtGY6r4EUaI9PSGI9as/tpukyAsP+hKixZONE4UhC0N+r00Tki4ChPMnqX/sPlqD7xKQCk7xydO2mFVVdhrRyS53CEK1JF1o6qjHln0niblYayL9HZrlSp3GwhDVRDPSDmCJo3oiDiqjrd29mgxz6XOrFg6uBFcHdfJsZTVr/zKFSVSKcIQ1ahsp6wJ0pPnga/kNClX1GkCBrLXgc2aV55qYIH6f61Xa5mGpayYqKqpOXaCsJ1wFXLJEyQSwElEm41izZX0tdvuRdzpHu382Lxd9dDbqtKei6byHkO0kg02aDLFfaxz5D9UEE9txc6Hssw3zXXXMM/z8zM4FOf+tQZP/flL38Z11xzDQqFwhn/fnqcdTL1gQ98AB/+8Ifx4he/mH/3i7/4i7j00kvxpje9aZJMnWUYpskPLoloAgK+ofJyWUoAVBbKmLtGqPw6s+plnUehwtqpB8J2kNMLGVDCinKbNoBUluizOFEToHyw42AIS5r1pmHEitZZHHOvB4mJClPcY+K4/CKKJZqUZYnfcZAxtBYpXyrLgiUn8NK87CVIM2YQ5WmONJETnISS7aLNE3iw0lJKxrK/Kwu6/AIwSxXu86EET4+s28LguJjcesfW2ITXky+5wlRNedBpZXcqt7tZhoIct2LT55fnqNOHc+JBOd5yIh6OxvqULJ6gxViEpzYRt8UYW3OhYh4SWyvLmO1UmqmjvE28BLrHe0hbMpmSQpq4v40VKQuwvNLHssbQFMdkKWVr00Q+Et/PXY+Nn0noMNMo7dkw0PzVxFglQcgSEVF3wKbLPQlND9shyrNim7Vds2q/rU2+duz/5nowSXjRryohS90wm+5pB3w9Mu1+ImFWs1RRVPz77mOIV5du4GswjBCeEsdNqubdY12Gexv7lxREVPS5n41g3zyJVA9ZmvF9YGo9WSwA6tjsp8cedlGIVEJgo05/7LM0BxCbsHXHIZTmBExnut4YFC/GxVFyCGHESRQL8E7N8LkAQE5ecKfWVYKiPSsMO53BtDwJI3ZccH0Xs5eLfTQvFZBoHnQR3Xcbf56gbGdhp2KrSjHgZP2EaguYW4ZB7GBK5jT1ez3yUagYmvTMDLrM9jPLQ+WLSL1VlsX3mfC2lMbNp0G94ncOQ5lZmnP/FM2jXl1l9N2jLbhVIYw7TdD53LISvs0yNU9rC5RcO0e+BpUG9wqSRILhjntwTuLCxrOf/Wzceuut2L1790P6/FknUysrK3jKU56y5fdPecpTsLKycrabm8QkJjGJSUxiEo+iyPIc6WO0MvVQIz/LczgnnalPfOITeN3rXjf2+49//OPYt2/f2W7ucR95lmkCcg4M6TmVpznDI9as+Hvzkm1oXCHK4/bc8pbyNgDkssE3K3hcJs7CgdICkpUO0yvBrYoVT9QbcLVJF8ujClHY6mIoK1NxMOLGYRITHXVH6B4nn7/DmK+RLpESItQhQ64+NGZ5NUp6SlZrk6sHuq6WL9lU1e0KnumfWEcsNa/Ki2K1XqhXmJGW9doMb5qVOsOOerCY4vEN1oZh/SDNIibrd7Y0ZSf9Pl+7+t5F2GRpk2VnFFukcHyPqzHcvB0nPN7uZguGJk5J40cVB8MyNZajg7ItxinNxb81x4JlE/wYsiUPwUuN/UtKeLWhoEy9MkSRJxEgKzF5FLLGGMFlmdaELRrQpT2PvI/KsyX2cPTnp/ja9o6e5GoLVTKcnRcDRckgjYcK8iN4z3bYEzBPU4ZdKazmAmtiAUAi7ym34jOUyKy5IESebtV+IhLBqBuhPCfGojjbYL0jw3EU/CKrd/mgy83Zo3ZPkTm0ylsqq1T9E+vMsJu6WOq8Nae4Shy2NjFYE3+PT7N7AcS9wwK4K4fHPTExDoU6JQ+DVXFcXUnCnq5VhH0NIDWYJIwchZqIqbqmrHHU1fw/JVxM1WwAqO9u8v3VvldUqVe/fZSPf2rfFP996pIu3L0H5THIeSfoontEVHO95lF4u4RHI1fesnTMx9MqiudHZywCEhJthrB4DuioMdJZcRoDlJv/mYEaK3KDaSLVqo6uL6vDUkS4slBGUQrRWo6CB6lqmVUaSlMuUQQOFsrFeNWPGNj27BITL/KuJCJo1/ZCh7CTOZ9k6mE8mB+TOOtk6k/+5E/w/Oc/H1/84hdx3XXXwTAMfOlLX8LnPvc5fOITn7gQx/iYjmQwgq1h9QQtBGsDRAPx8NCkPvuEA7AX9wAQiQrBM0hihavLyccqeMi0SYR6hgyol7upG5pWx1+iWZQgDMVEGrY2MWjJiSxKmSaui9WN5AS7cdcqK7pPy/1bjVmePMxKQ/U0eWXkA0lR1pSniTqdDBMU62Jb/qz0DWsU+UXdX+mNedQBYsLT+8Lo5Z2OTsIqijHg3pBqE82n/QcAQPOpqZJUoP6zbgu5FCZFpimBE9POMlnMVDDhxNgGJ9Y5+cw0wUySdHC1saYXQbDSYlZRcXZVSSZYSk0+P0OPm2mZmKmRcrRkxzU8TWIjY8iNesIqy3PsC2fWmsq7rOgDJCYoGUaGaakXgO3CMCUMQezM1ORzzDQpAH7ZLDY4OXUrvkrQ2yE27hEv+kL1OwCAPbMzsBeEwGGeREpBXC4aDNcbE6JkhX1ib7reWAJva0r8pDAePCiuJyUEYtxMFrslqL2yrYy5a8Sz5m7boSDFYcT3ASWeGcAJvOUOxnqKACC3MiWH4DroHSUz5sMAgOZlJizZpyf6vCTkeDJQTF5yMNg7A7ssZVDKdb4/CDrPw4Dvqf6JdYQd8qkU+4/7AQxf9uUkEbNZsyiBrY2t+JK69mkYjUkHAGLRQH1lhXqFWYqpBisfu0skAmE7xMUvFAmpu/cgjKb42YzkMze3jIKEOntHT3KyXty1m4/F4GMZqIWFafJndYamS8l+vL6lFUDvCTNMi8eGpDKyKFbsZ2hyMdUCLyDPJDYatrqIZPJKTGu/1oRBMHqWKc9LfSFMiV1jBuas6G/M3BKMUF4bOXdnwQTmezTHWSdTz3ve8/D1r38d/+2//Td88pOfRJ7nuOSSS/CNb3wDV1111YU4xklMYhKTmMQkJvEIxfky8h7NbL4LFeekM3X11Vfjb//2bx/uY3lcRjIYAtqKisr5harLlQZypLea80prxFCNw1kUwqAmTG2VzroXWaZZvGy1/jAsU1mRUNk9y1jEUujJKC8qVZEi5t+IKyHBWoA8PSzORW6zVmsqLSPN4iWPhkg2BBQTt8QKdtjqMvxjWibmryQRvBl5rjGC1Q4AsdolvSVqCC02qzDlbR2stHgFWVpoqlVhSYmRcjm+vcbwCcOMrscrfziugglkU7tTqasm6TDA8KSoOASrp7i6RizF0vyUElaEEtCkKlsWJxhSY/2JdVTJR1AKGRqux8clWFQRf5/EKalZ2fZsJYQZZQy1kG5SnqaoSVipBACyH9k8gzhgnsRjAp60ytcbriksx2a2ni+rb81Ld8GZEdcw3VTVtzRK2TqJREhbt9yJOun/dAfsKejvFKv1MWjbtJTnGt2zTpEJA8gymOx/ljI06zXF/ULnQd8nmNuXVeBRV7EU0/a6qs4Vfa7qMdwXdHmM3FG4RcwzDSPWMAJURZcqKYO1NjeKe80qV++ADtLoDG8l0h9yHLZI0f9mWKKp3HJtlBdkNVJ6VDplX2NHRppYqGITUpXbLCnmn+W53LCvjxvrMTm2qgDJZ66yUEbtiLQtqhZYW8pszCGT18aQFVCz6MPRvP6IyODWpWVVY1ZV360AyVA+95bF+2UCSLvP92XUHTCU78+LebS8lPJ9kgyGWyqJhrZNy7F5nivONGAXx6t3dO+J7ykyEYkn50msRG9d1XrBxJIoVJXhxjyyknwYsxQm6U+NNALIIxSPZTbfQ42z1c98SMlUt9tFVZZIu92tjAo96HOTeGgRByPkA+XNRC9E13cZn6eJ0J5f5ofNSCMYjhSr06nZFIY5JgHAE6j8cxaFY5OIgvzEJJfGMRzZA5RW1SRnOjarFptyn3EwYmZfMkwQ9YkqL3tHij6sqXk+LhapC7rIuiRQKBKRzUNrvK3mgSaal+4aO67NwyvK0y1MWEW7e0zcl9XlDup7Fvm8glXBSOweXtHYVeIFU16cGYN/6LOlmbr4+64lZaSq9WyowVDQQx4r8cosjnkCJmag4xc5kU0GIXvnUdIlvBbJ9ytSEK4MQ0tC9XDLLsOu/DvfZZkG07G5j4kizzLufYrXT6pkqZnxNeXPanIIWRJznwx9H8CYACjdG/TicucWVG/RaMj+hJXtNRRq4poWmxISmW9yopKnGXp3neSfAaBaqowtFsg0NpMCiLnrs7K0GQUwYrXYYHkHuS3HL44lguxTqd3r7CpQa/J+Tb8Kw5NehmPK1eT1lo4laoDoK6PEKQ1HW5KtuDvQ/CZthhzdsovGbrHfOenHN31wL8PkpuczW5UZsoUie1PaXoF7sQhG3CLUSdIerS6z2jyZ+BFsBwhBSzJ8zjTjbDoXy7W1vi8p2NoawpdMzrkrF2DLhUFumCykSXNButlCJJ8F0VPoj41rttli1p7wF5TMP99jdiQlU8NWlxOoLI7H4D9AqK6TA4FdrcIOyIFCtQwQ5Feol1GShtSm7WAkWZ+BhPNMx+ZrR/cLHRcAIIn4ubUaM7wYzrQ+RIKLc6egKaNrgrDyGUxHj1zPVHqeDejn891HS1yQBvRGo4GVlRXMzs6iXq+fMWPL8xyGYSA9kyrwJCYxiUlMYhKTmMSPSfR6vR/+IS0eUjL1b//2b5iaEivNz3/+82d/VJP4vpGnmmN9pCotADC1T1ShqpccEJ9tbGO3cSMONdFAkyskbJUSj7hiYDgOl8jZeT1S2lJ5pipTOjuLStr6CtUwTWa/6KGEGX1sv040jU49QTB2rOaCsgTJEl6Vpe01hFKPiWwv8jRDfZc478b+JRYwJAsLQLEIS9MJw48kphe2NjGUK0RbY+qM0nTMa432SVWqPM3QPy6gxtad4pgaJ9YxdfFOAIBTKW1h5tmlGCCoqegzQ850bc0bryY/W0TcJ3uRzbFKBQBEQcznMur0kMgKsFULePu0gvWaVZQXJQzodLZAnbVds1wZSjSPORqL+r5lZg1B07nJR0PVXE+Qiu3y3+PuAANZvWN7FNPkhnrDNLkiR+c3PHIEhWnpraeLfmbK84zuPbde5lV8Yc8l2HaFkGDhJmt9oaZ5rmUFcY/kXkU9E1HA0F7W64x5SwLjQppZlHAFhJ6ZJEywef8JAILNx5pQcYR8JNlV1JQe6VU6C3k67k+YhhFv1ykVx4gEgIC0CML1mlWuCNd21OBLFuKUrNAaroes3+H9mYnSjKLj479pFTCGwqIQBlkE2S7vFwDb2NBxlWbriqGaZlugXdMy+f72mjXtvMSzmmpkldJ8c0zfykhVwzz9S1XLwuw0V9wSqXUXrK2p+6Tqw66K/Rqez/dnQY53sNLiZzyNM4aTLX08NJscej4IXnWqPkry+SnOzfCzkPY6rLdHY+TPT/Eclbc2uSJG27KrNbbYsqbmWUCUiC1Z0FMWSuURDFs+d1kCpOOVKN3r8UJHhvNj5D3aWqauuuqqhwzbffvb3z6nfTykZOr666/nn3ft2oWlpaUtB5bnOY4dO3ZOB/F4jjxXyVQWJ5yUeA1PQVySwZfbHsiO20hjpETVT2LkkA+enNgN09pCmwYw9juaYA3LZBhNN3qNNfNVSg50CIP6JdI45R6dbU9awvxThT8VTSJ50EUuldnzcIBUTiTR+hpPTgRt1Pf63L9VaFS4dE/QQRKMw1/UY9a8SEgjzF1zAG6jLj7bV2X7NIyQekRZl5ITnqt6gNKMpRGofyYOQj6+iqdePARx9Y48yMylyvIcnGkBx/p+lZmBOqyiBCMrYy8xABhu9DgpigMNgqWXPFSPjtes8aSdar0uXlNM6uXFaVb/BoCSNOb1doj7yKw1WQgw12jwyFL+f3q6Da/EMF0axzweveOKWUTMPa9Z4cSHkpbBagv1/RJqchxWYc+iFF5DHGNNwrJWY1YtBoYBDPJ5LEgpjVhd+9wuIHclPOKq5J5e0kas1L3zKFQLFnk/xd0Bsw/TcMQQlh7Bmnghtr57CLOSim/PL6u+LG3cOEyLrxn1fOlSFnZR3XOqZ6rP9xx9HgDmrj4wxmYDgHj1GMsdAGqhw7ASlPxDGsfsY6mSqQSAZLW6nlL99lxOiikhztKMn7t4EPK9RklNcbHBcgemY/OCKGypFX1lQS1sSEgTtqPBudLIuznP/V95FPIcQQ4BUW/A8if21AxDnYDodwSUCHGeZUhjlfhxCwNdg5LyB41aLXTuFT1mm8fFuU5fpCDDpN9HLhc2o3aPpVgo0jjh5DEJI16g8vNtu6pPKh4pgVx5b6atFVaHdwCY82LO182cKYzTWzkuYKRZjvQ8sqnz+e6FiOc+97n8cxiG+NCHPoRLLrkE1157LQDga1/7Gr773e/iFa94xTnv46wb0Hft2sWQnx6nTp3Crl27JjDfJCYxiUlMYhKTeNTEG9/4Rv75N37jN/DKV74Sb3nLW7Z85nwKQmedTFFv1OnR7/fheVsbZCfxgyMJIxhs/5CosnjT5+oC6YyYSTjWuJlrbuSKrSdXw6apWGsFb4tYHGnVUNDKlVe1UaIqU8GQm8l16CBl4cYc9Z2i7D59cC/bUeiVgTOFXfJQkjpN3IDr2gwdWH6FdXBMjTVEDLg8zbkitfRM6Ve2bRevVMMjJ9A7Jla2WZTwNkgbymtWeYwNbSWoQ4rkh2fVmmoMTbGSDFZaY9CfDmOk8jPsj5hoUE+lxKtk/fukceQvNNm3jZlqsbJ1SQYhX6eoO0QkmX2OT6KDCRJTsdbomrEtzGZLCXV6JY1dGTK7MV0/IU/K4u85fpGrF5YrIdONIUZdsd9ymMCrS70meX7+4gxXPXtHT6J9/yqf6/RBUSkrH7hEHEuhiNGhuwEAnXuPoTR/p/j7ZVeKfTZmVLOu7SromLzXohDmQFTO0NvgFX+uEQcI6rQcm6t7STBkWxSqDItzEFWdQr2sYHI9qIo2Csf8C5kVZqqqJ1erIr2SIfZlF1XTeaFRRmlhjs+XdLUIDrOKJdgl8fNwvcPaTzrTk84r6gZ8HYrac6ZXmXWtOYKGeVtZhn5HeiweXUcmCRKVxYYaQ1mJScOInzW6Hxu7G3yNizMNNR88eIgZajyumfICzXodhlipwlmcbWisziWlObXZYsFUqhibjoNSkyDxGuqyMutuF1U+o+jz/d07epK99UjPr7w8x9Cd6dpsUyPIHOKzI02UlwRZ01DZClF1zyzXmYGa9dqKPSzn9GQQIhlu8nG5xDj2/LEmddr+IxX5ebL5zrZ5+5GMf/zHf8TNN9+85fcvetGLcM011+BjH/vYOW33ISdTN954IwBBF/zjP/5jlEqqtJ6mKb7+9a/jyiuvPKeDeLyHmnwNNPcLyKO8OMMTVXz4LgCAV2sClTN4zIUDNhQlmMYs+kr40XZ48sk0CQWbJntN2Zp6YaLeYIy1Q0yz3FLeYxSOZ3O/DnCayCKANAyU0antcNJhlyoAxKRG7Jg4CPklVKrU1USmQSNkBu3PljD/ZPEiLlwszSuLik1qeQ+wqW9vpc8sQ+qvmr6oiYVrLxVju7SkvPcc5UlIL297YRd7ZSVr0ofwwTWlcr19N+w5MWlnQU/JVpAUhebfZtrKP41fhq6F8naRGNb2LLKUBEUeBvzSCFub/JIZdUfKJ4zMbBuVsf4VmoRtSmptF6AKchJzz4ZhK/mHRHqmDdfaCvIYRgyzctI/XeSX0ag74mSKaPCVHdu4V2zz0CpC+dnpn9yPykFh1E3yD2l7Xb2k4kQlbvLvZrnOCRSgaPV5LF+i8RDmoCPOe2OVe4uyKFTXSW4zdR2G/AzL5CSqf5L6CHNUtys1dZbASFNt7GTyOujxi89wPXjLsmqvJQfDdXFPDVtrDIM5kq3rzzfRuFgmCs155dU26PHChBTY88YsS3w4/gonZrofH0Fn/ZUeRlI9u7KtI6/LjNZWEPNiwV9ocn8UzQXBSkvdZ5sjZXYu76eoN4ClwaYEldb3Cghu+uAeOPKZyLOMFzn9Q8dgnhCQHyVI1swiQ8tJv8+LBYIRa9c8Cc62nWJbSczPArJUwMMAahIWbhR9JRlhmmwCzwnvSPWbWp6LqYvm5XUQz3dpocnn3bn3mDJxX1TSJhQ69JanGSdh5V3LAAB7dnHsPiCnh3SoEl6aA0zrmGL+1Zqqt5STxfEWhwsZaS7+O5/vP1qjWCziS1/60hbHli996UvnVRB6yMnULbfcAkBknLfffjtcV/V8uK6LK664Ar/3e793zgfyeA0d06/uXOBVVBpGXDUhVWj4DUXHTmJe3eWjoep1oeSjXGcarmFaqnJFSskaXTzq9Nn+hHokdKsIvZ8jGcZcpSIqcKHho/098fI99m+3YFlOMN5+6Qzv+YCcEKLWKTikFt2Y5WOkCb5z38mxviiiQNOEM2wF3Lg8fdkSipcIodi8LiZS6pkBALtYQGmBVtsOhlLFvSO1b07evoY0FttqXroJX1KgScPGLha478uozyrjaFtXq+ZBAiyZRBZ9ThhJTT3urbN2jmmZ/OKhJDKNUpYlMCxTVT1k3ipeyKLqMljrYNQdymNw4MtzpMneLnlMM0/CiCtDugm2XlWhzgzDdpSuloxg9ZSm2A1YjiX3K7Zla4m05ajeIOrlMYo+cqlsHQcxayxVdy3AWRKTGdtmnDzG9HS3UhLK44DqpTFtTqAQDbmZ1yA6eTwSZrEA8kFXVUK0Z4wiixO+r01NjXogTaMdz0Zlu7iGtd3bYUoD6LGGfVktouopANiNWdFXBVURi4bBWM9foSHGxpGyHF6zCoukFyp1pfxuWZxIwpeSKMCYXprTEQkKNdiPOj3E8npbrsl9eFQFA9Q1zNIMlvxsddcCJyWG3REfXGkhGW6l45MbQhonfL0tr4ApmRCW94j5ymrMsnE2soyTz1HnPvSOiuNekGNfWdqvKqdxwhp1RL5xtu3kHjkDwdjiMDst2TBdmw3UWdoEqmqvK7/rOlLcw7bS4p+j7pAr4W7F5zmPJDQMy9SU4UeokLUM2Q/ZDtK2GM+0vcZadJSwJsOIk9Ow04MjK2Z5FPKCLKb+yHjSQvNwxO/8zu/g5S9/Ob71rW/hJ37iJwCInqmPfexjeMMb3nDO233IyRSx+H7t134N73//+yd6UpOYxCQmMYlJPAbjsSza+ZrXvAa7d+/G+9//fvz93/89AODiiy/GX/3VX+FXfuVXznm7Z90z9b73vQ9Jkmz5/alTp2Db9iTJOsuINvuozIrKQnXXghJ1i0+NMXQACBHCTFYEs1RTQnb5e6w0rhm+5uEAmWTTKZ+nLq94wk6P6cE6O4zYeoZlAgExzZSxKK3SSvNNdI8IGGPjnlPwF4Sr6sLCdnEslTpTy53T2GN8jAQ9pLlGE6/xCrRQl0KCvssK6UopGtxLZsQjtVIdjrhHxtR6oipSVdou2ijNinFLghDdQwJ6oP3bxYLafDxUlSc6pm2LKCQklughj0d8Xqw0L6sTg7U2Gw7nacarYYIJiEkICBiPrrwpq2DRZo/Vw0edHldV3GqRz1FXgiYmWZ4qXzgWcS364/0+Ek7ItOoBrZZH7R7aD4j9Wo6F5gFxf+mQB5seZxnT+onmbrgeV4UK1QJXSgCwzAez8ZKImWpO1VfQmgbtcTUqHrIoJ/9Jq7bCtBTlHNhC68+iRPWw+R5X10zpOlDeVmaWoVlrKk/AJOKKVNxW/ou6eneusWzVYav9UzWIYvP+E1j9xj3yWFxMHRAVnuolB7jCkZMwqeXCkD87rodEVnZYUbu1OQZfkvAvuSkkw4Qru5ZrjYu0alIrFHSflaZLPEZdyXpLhgnmrxFwbuOSPapipokF8/lrshiFehmn7hXyI+17j4rt71vhMbZ9D4V5Ab05y8LwOCvVBZsZQl3cJCg06CIdiXuKnq8sSrgiTf1nADDaEHNU2OkpFqNr8zxL0GL/xDrf/8XZOlfcnGqV4TnLl4KuRZ9huNJsg4+bTeZ7HWYmpkFf+VjqzgFyLnB8xa7MhwG3S7AoabT1vXuh4rHG5js9fuVXfuW8EqczxVknUy94wQvw8z//81sohJ/4xCfwz//8z/jUpz71sB3c4yHcWhkzVwm4w1nYyb+3sxThimjoTO66HQDg9Tv8GaPgMb3YqjVVI6dmVso03CxVNFtKwEyLX3KO7yn1blJM9gqaXUymdJGiFGFbbLfQUmr41EOz/SeWMPdE0cekYAOHoQszCpW5aq/DEyG9AEzL4AknDSNOEEidvHNkE5tHZFNqw+NEwEgkRNA7xU2edG6AaggV5y6tIlybkwK34nP/CcF33o49DLPkSYxcHncqt2+4Hmx5PczGHL/o01OrnNDR5KtLSvRW+tyDRtIOXr3Ilh5hq8vHSAldEo4YXk2GMfd95anqYSNquA5p2Z4Lp14X50u9R0VfWVRkmYLDBl2Gi0hzaLDW5wTIn/VRkj02RakSn2cZT/Ju1WdZCnqx5knM515o+OiviX217zqC4uWSKj+nNJQIvtw80kZj/70AgPKshEyK2gIhyzRjaglJa8mL4XpsN4MhkPZJaV6ZzrI+lmWqJEpS+eev2oHy3r1iDOeW+fnKh4HS3QpEQjBc7ygLFdMal0qQQYkZwfiA0lbbPHwS3WNEtDAZWrM8FzUpi4KavKamhdyQL9dSHVZNPpeyFyeLE14QWY6J2g4pMyKT9SzNuNneMA2WhyBFfkAlnOJ4yKJIPT+machDMVBoSOmD7Xtgz8pzo+egtcrHlUchw+P+4gzKC2Ju46T92CG4cvHlLu9X/Ydl0UeYO0VuccgAmEUJhRb9LYrzaZxo85nqwSTZF9My4creJtv32JS8I6/HYGOIxl7xrMw/9Ylw98tWgmGA6IE7AABxpyOO1bJ4IWvFiTY3rMp/PdWfVSiM3XMAkFrRFvcJQBJWZDLFY7Q5bur+eI3Dhw/jLW95C/7t3/4Nq6ur2LZtG170ohfh9a9//Vj70Q+LKIqwtrY2ZtAOAMvLy+d0XGedTH3961/He9/73i2/f9rTnobXv/7153QQk5jEJCYxiUlM4tERj2aY7+6770aWZfizP/sz7N27F3fccQd+8zd/E0EQ4N3vfvcP/f73vvc9/Of//J/xla98Zez35+victbJ1Gg0OiPMF8cxhsNHjm3wWAlvqsrNrYbjqgbxOOaVlPJvG8KXcJ09s8j0dpgmm9QaZ2gyNjThSBaRtB3YEpnQFZppdWT7HjdZpmHEzdOWa8GfFas6gvkMy0RFMphKc9Ow5kRmT82nhmXBiFTljKAr3cdMQVUGwjYxCgM+HoK4eit9NqNd+g+XMwzADChNHdrxi1y10enpBHs5vofKLrECtrfv4UoaRT4aqqpNOFDefMT6q9RV9SMZnfGz1MgftrpKlLMfszkxGdG6FbXCdnwlKkiQatQdcMXBLjqqErI0h/KShBZINmAY8PfyLOOmcr4PbFeJcmYpjFh5rhHMRpBJb6XPTLc0SpWyMzUeu7pUhUZvl1W8qN3heydPM25+3jx8Eo3bvwYAKBH7s+ijKu+j1VvvwHc++m8AgIvk9xvX/RQTApClqmGZKpGaDxpsl5+rDABkZYoaf+2Sh8KshCrX1mHIakttu6gy1Pcv8b5MvzImvkpQenFGSmSc2MCpo0cACF+4xn4JSc9J5evGLOxtkkSSxAz72CUxRpXlGXh1BdUqmYSK8t6jnWcpN+EbOglF3m9xoIyWG/u3cyM33U/9ExtIQ2pwN7gSTXMMoKqhju9xJTIJR2PG6AAQdkcYrIiKcTVL2SuRqsR5EvG4meW6qu4likVIVRfTtZmxaMwuI3WldIvuJSgVwY00UnIYWqg5zN1COBCbUo33VKE0LFM1m0uWcG1HA9ue+TQAgLvvSj4v0zSZWBJLNuKofZi9+wCwKK3pSQcDz2e3AbPWhEksxJUTfP659vzQ2BKLGFDVVNM969f1Ocejmc33rGc9C8961rP4/3fv3o177rkHH/7whx9SMvXSl74Utm3jX/7lX7CwsHDWhsbfL8766jzxiU/ERz/6UXzgAx8Y+/1HPvIRXH311Q/LQT2eondkFX2ZSFQsi3sfRhunMFzvANBsJ+IYG7c9AAAYbAxY38cu2pi9QpTISX3c3X3pGY2OM/niTLpdjeIcbJko3WqJqfaDlRZPxrVd02heJvRaaMLqHlpBW75MNu8/gfo+McGSPpA9Pc8vcsM0lQWLafFLYFxZnaCFgmZzI/Y/f+Uc9j3/GQCAwhP+AzPsMFSQI03aVqJgwqirjFpp8hq1+0gj0d9V16EZmZil7TV+WenbpX4009P6eqIQWVecd7J2HKM1QUmnaxi2NlkWwGt4mL1CJJzVXQt8TAxBpRlDjWRaiyRmen0WJyhJm5HTISgASILumK4RQXeW7Jezir5i9pkhJ6JRu8OK0wSl6tILpekS6xVRPx3BgYDoGaEXB9PQN07xC8awTFS3i3sqSzO0vnsIejjTcwyDLV23iaP/Lu6pO//hGwCAfUGI6esE+8ZqzIz14YgLYqnzKngAJWmZSqTpHnAragyScATHFwkEw76LO7jPTz+frNdhaJlC723cPLTGSe/UAfFMFXftVolumqrrJBO7PM0Ywh11RyhUla4Q33+k7G6YMCJ5n3TWEJ+4HwBYfqK6c4HNu/Xfs1VMN0AsmX2WYypJhSDka0pJh2GZY0r9tISmxUzdb/L9C9NieA/U45ZlrHqehhEfV5YoI3BasDmLe4AFAaumJc0ihxPHSKnbR0PkA5mgaxpiBDkCGNOPo7mH+vjiYMjsylGnz3IwZDvTOLADtlwQ5pbLyWumsTZJAiHRpFxMr8RzS/uO78ntf5tZwtX9u5ldSND4YK3Dc5RvmXyMeRyzgwMxXKPOIwfzPVyVqW53/FkpFAooFApn+sp5xebmJlve/bC49dZb8a1vfQsHDhx4WI/hrJOpt73tbfjpn/5pfOc738EzniFeap/73OfwzW9+E5/5zGce1oObxCQmMYlJTGISP56xtLQ09v9vfOMb8aY3velh3cf999+PD3zgA3jPe97zkD5/ySWXYGNj42E9BuAckqnrrrsOX/3qV/Gud70Ln/jEJ1AsFnHw4EH8xV/8xRYRrEn88PCmqig0tMZauQKOg+GYAjkFN4QWbWRk7tsOcegzgg0UyLL7jmeeQmGXzLxNpVtEEfUCZq/FQcisHVpxAWr1lMYJG66W5qe4WqSz6WiFmgwjdA+L5kvL/a74juMo+NH1xprkiWVITBrXd1nw0a1VeGVNDbRJGHHVx37wPgX70Ph4PnJZOcrjCJkUcUwGIa/C+7LRdOPuFjdyb3tiC3NPko27kqmTBko80HRtOERUJUFADUpNex0kq4KZ1D9yYovhaRTEvPKdvmwJzSsuEtuVjdosQgjAbdTHvMcAAV96TQXbMryYpaqZvK/Ola6jvi2d4amb9JKYYuf+E+g8QExIMVbV7VU+7tJsmVfhpH5vug57phUPHGSolMZCjBt59ynF+bDT4/vv+OeFsWhleY4b28uLM1h8ooSgJDw6XGsjuFcopJd2htxQb+kCp2PstHHNLD2iXoDs8GHxc3eAoqzCUhXBLPpjPpYMvyeRUqSW5IlxHauYx5D0h6bDEWsvAapaxEzOelmrzLYZbtq87wTcOVF5csl4ulBC1hH3b3zifm54LixKkciZRW7Ijw7fzRUp1ihrBTyeZBgOCCICVe2oGmU5jmqUjhO+p8j8uzA7o0x89WuQiO1nvTbad4vqYu/oyTENMtpHQ/pF2rsuQ1IV92lmF2BQi0JCDNkMBqSqfxohIaX+9ho3z9N8aTk2MkeKiaYD5UHK7M3imJK5qljn8nd9fpbs2jRyWQnMBl3VTC7nCKtY4mfR9EoMz9Xl+emq6FGrBUBCwxJOP3XPKgYb4j4pTZe48b26a4G12qji5m0+ckz5LMv5/XKu3weAY8eOjTH8f1BV6k1vehP+5E/+5Adu95vf/CauueYa/v8HH3wQz3rWs3DDDTfgN37jNx7Ssb3zne/EH/zBH+BP//RPcfnll8PRdOYAnLMiwTmBsFdeeSXrM0zi/KJ51cUozGl9ILKUnIQRwwVxQIy3lC0d8jRn+xFr1mdRvmBNPJgnvngrGvKBtUveFtVyvYeod3yTJ5ymZJvoPTyWY8OUL0TLdTjBoKjuWmAX96jVwspXBeNl9RvCDmSpUoK7Wwp4+lWAWFj9Dvf2EJuvtDDFvVhxP2DoiyBHAYmI8YgO3w1LsoUoUcizTCVo3S4LcNKYAqIPSOwzQ3OfgBSqOxe22q5oJqbR6gCm05Lnq6wwmAK92WJBvsF6hxNgtuGxDPjb6zxerHBO0gq2C2+7fJFrL6Zc69Ni6C6MmBqeDwMWbKVr7FSrirlXa6r+C4JEs5R7urLNFoIHRTI1WDkFpyxeAtOXC9jYKXk4dbdQfD/xteMAhClscVokRVN7m5h9gkjareYC0/aJ4eTU66hKuQS9d8+wTIZa+ifEuPaOnuTxckoeZq8R/XDUNzdYa6N3TByr5TooyqSWX+SmxUkPskzJJGTpGP0cEOrdkQY/0guLk4fNFidmhu0qqYtRuNWA1jIZIrMcE4lc+wRSTd07sQF/WZk5F+Q94zblNdB63AAgOapYfk5VPEMNgpIas2MwIymM29sFRAavArMtnwnbUVA+CUsOE04aALBMA0la6J/V2bSzV18ER+6D+9JMk68zilXkjnxRStadWWmMyXZQkmlYbWx7iri2hUufJI5ragdiUyZxwNaeKNPk7cK01b2UZXyObIVlKRkUwzR5btF7k3TDYlpI9iUMj3uPo75PQNBWY2bMiosWC9TfBYgFCQBh60V9mXrPE4luRvFYDycAuGUHm0fEs3zi8AonVo5f5OSV5r564aEz1c43svPsmaI8rFqtPuTk5Ld+67fwghe84Ad+ZufOnfzzgw8+iKc//em49tpr8dGPfvQhH9tP//RPAwAjaxSPeAM6IMpqf/mXf4kHHngA73vf+zA7O4t//dd/xdLSEi699NJzOpBJTGISk5jEJCbx+Izp6WlMT08/pM+eOHECT3/603H11VfjL//yL8f10n5IkAD5wx1nnUzddNNNePazn43rrrsOX/ziF/HWt74Vs7OzuO222/Dnf/7n+F//639diON8zIazfS+ssmQd9TpcijYsU5WnpQZOFuaKWRWnvMI0LINtOtwyifhlDKMYlskr/liakBqmwY3eorG4DgBsTGo351mcsKQ1h+dpxgw1/VipcT6LEgzl6mrzuKiylRePYHbnxQBEBSmVVZG01+Em3JLcv1vxmcUYtja5WkSNyXa1psxfhwGidWmnMRTVE11oM4uSsZU5QaAkWjh7yTSal+0EIFZ/yuJBVbNIFyYJI9YFohXwtOsxhJaHqok/i5TlTib3ZXu2Mk91bOQDWV2Q52I159Uq3zRVA7dWBdH99qLVAf/ekmNEbB8rCGFLfSu732F/N7buyVIl1Bl0+T6rLM9yQzD5tA3XO1wNdXyHSQ/rd4kqQ3+lz03bs7svhdWQTd8SIrNqTeWRNwzGxCuJacYw4WyDbVUMT8FsyUkBGSaHVhCTX2UwRImsb0z1LzNctTA8n5l9prspvx+y92RpvskN/TQW8fpJhl4tnc2XpXyvU9ieq+xzLBOWK8a+K+//te8c54rY9JN9rjzmXOGx4Mp7x62U4FbE78POEH1JCKDvlxYDrnoYnrItorHKLQ0CNi2uylDlOo1Thm3LCzX2ozNdmxudCRI0HQd1Ei71q1z1I49KozqtqlGmvcV4Wh8ny1FtCchSNjhnr9E8gxtJra3+OoyO1M2Sc4VZ9JXOWJ7x+Zp+hZ9RNq7WGHKGZXK7QiztZrIo4UqlW/URWyTYqip+GdtvxTCJudqY5eZ6tvUaBQCbXMdKDFeeu86EDltd5bcq0QYSIAaAuctmsP0nRcWucWCnqOJDVQILzYeHdfZQ4tEsjfDggw/iaU97GpaXl/Hud78b6+vK7mp+fv4HfFPE9ddff0GO66yTqde85jV461vfihtvvBGViurBePrTn473v//9D+vBPR4ij0OkbU00USs/O6XTXwwDTbnX5J4Ht1ricj1l6Ek44r4ApJnW6yIe8sHGkCfV5iXb0LxU+mnRRB8GY55jJGeQpiNm+9DL29SUjpNwxMa3lFTpPn9GocjssSQImSLtzIg+qXw0RCIZIF6zpiAcXYFaEyClbRMLDQAzzhzf45dJ1Au4nD9zidhXcabByVrY2uTJmLZpewX48kXvLzT5713pK2ZYJhoXkwCiqWAELQGyPDFuhUaFE9Y8zVg9myZ1w/XG+n2Y8i6TrjTocWKYZ5liJHb6Y4bUgLhvaF8lx1aMw1BdB4bAkpj7mLJ6oiXdHbn9nmI57a5zMsXbyTIelyzojSVs6lhVrxedg2GZqO2WCvlEHS/6og9NfpbgWkpiR50eGwJXr36ykrLQpT8odBX6KGSPRF1FniAox/c4iaJEeajBbsVmOK5wfhrM5zVr/CxE3QF7/VFv0vqdG0g+J3q9TMdG4zLxwmTfONOCVVDPMvVvAQr+7p8QfYJ5qsRGnbKvmGT03Homy16IxI985WQyNlvleUXIn/jqZ5kQUuIWtrpofVewh/Pb7uPnauqg6PcrXHwN4MrnVlepJ4jNsnhcsjRjsc8oiPHgl24DACzI4/OWd/I9Mzh+DO17j8nzbvHx00LP33+AmZaG58NtiuTOl9sKVlt8H2OrtSAMy+R73q2UONkqzQqot7F/Sck0OA5ASv2aNySp7+dZqnoRs5QZf+zfWSiiJsfbtB7kHkp6jizHZEPtKIixevMDfJxTVwmUhyHD0RlO5gJFmudIzyMhOp/v/rD4zGc+g/vuuw/33Xcftm/fPva3/Pvs97bbbsNll10G0zRx2223/cDtHzx48JyO66yTqdtvv/2M/VIzMzNotVpn+MYkJjGJSUxiEpOYxPnHS1/6Urz0pS89q+9ceeWVWF1dxezsLK688koYhnHGxOsR7Zmq1+tYWVnBrl27xn5/yy23YHFx8ft8axLfL7LeJlJZ3g5bmyyelwQhN1pTCAiBNJhsXin681O80iJLkeF6Z6zZMWXLESkG2Q6VTcjcJjda22UJ4RU81WSZpYhWRONx9/AKr+Soadd0bK7wRN0Bw4+kR1NZnuPqVdZrc9N1cfc+LmWzNUiWstihqNbI5k8pXgizwp9Ngy6PV/s+Ub2IgghTe0Per954r+CkOh+30toacBNwf0UKZQYxaiQYuX+JKxkUvaNryp9woamqTFqFiZiatZ0LcKmxvjdglhWt3Ot+FYYracRJzNU7qlDF3QHr4ehO86lmM0ORpxkz6MSgSghWfl9v7B+3DrFR9Ik1SeQHVSm1XIttg6pL4rwWr92HmZ8WjZxWY5YFNAkiy6OQRUPzLIPTFNfArKrGeKogZUFPNeR7PlfPFNxtMhSVHL+f98WsO9tVWmCuxxWSfNDl6tZAWofoWl6AslOhKlvcVSywtFIC8X30Jnq6pw3HUX6OXoGb0YmEMNgYMlQfnFjnvxPsa3nuGYUb3arPVUc6vlG7x9Wk8uI0yqdpjJm2g1RW9Iyij9mrRRWJmqCDlRbCU+KedqolFi41XA/RyZWxMTAsk+H14kxDwdiyype2VmH5Yg7KLZfFOo2RuEZ5HMGSVTpzrFUgx9Evi/nktv99nziXgo3G7roYD9fiRmzSZjNdC51D4rwWrtnA9JWiumfNLHL12mNRzhQDaT8lxlG2UWjVXL2yS8/gwrWCJFPYsVdZYXk+Q3pGGgFSOJTnJa8AQxXm1TymWxvJOa68lDJzMBmK84+DmHW/8jTnNo1Co6wqyuS7qGneXeh4uNh8j5Y4dOgQZmZm+OcLEWedTP3qr/4q/vAP/xD/+I//CMMQ3k5f/vKX8Xu/93t48YtffCGO8TEfNEHrkMlwTVGkqU8KEH50gICyKDnQ5Qx0fzYq2yfhiCeSNJaioN0RAm27NIE39oe8TdpW1Btw0hK2NpVZrHxZWZ7LjKssTvhF68/XAUDQwlmh3WHVckD1RJCQp12pq5egLsqoM9Gk+GTw4BrLHNCkCyhBSbda4hdmdecCT5p0/EkQIiT1Yw2KJHPYwcYQJ7+zKscgRGVZPIwk0xB2Brx/wzKZBQWAYVOdEj9aFdvqn1hnPzC6LqXZhhAuhEhkOdEICYYZsXlxpjExRb8aCXRS31oK2yfj6oj7aiAn48Fam5XODdPk+6c02+AkjPrWLMdmgcUszdDYI15cs9dfCwBwLr1W9coEpxiq4chShrOsueYYhZ6hzNPFNwFkgx57S7IqtGOjd0zAuYPVlsbQE9ejvDgDb3Gb2EBjdgw2TU8ziTUdW0HA3QHfMxS2Bv0Bqm9l7PipVyYKWfrDqaj7i5TM/Tmfvf9M18aQBCNlYmi6ajGShhEnzYZpMiRH29w80kZyiBLCFP52sfDQk1eCwNz9V7FExWD1ZvH9+x9EoSGuR23vDu6ny7otpZrPx6+gP7PowzClnIBMxozj97HLgTm7gxXKk3Wh7p2cPIpQwlqGZTJTNA4TlGelhMAOAWlWFsosnHrqvhY6knE7lAuz+WqBXQNGnR76x8SzVCn6fA5GSfoQNnpjyup0fxPE1j20gs2jHQBAqVnEnGSNupoxO4usFnw2WM7zDMZIXpvTTLbFIGZqEUTzmu2oHjfX4z7B2i7R2xO2NnHqPunjGacoNuXibHFhXG7iEY4U56mA/rAdycMTO3bsOOPPD2c89BZ4GW9729uwvLyMxcVF9Pt9XHLJJXjqU5+KpzzlKfijP/qjC3GMDzl27twJwzDG/nvNa14z9pmjR4/i53/+5+H7Pqanp/HKV74SUTQ+md9+++24/vrrUSwWsbi4iDe/+c1bSoI33XQTrr76anieh927d+MjH/nIBT+/SUxiEpOYxCQmce6xbds2/Oqv/io++tGP4p577nnYtnvWlSnHcfB3f/d3ePOb34xbbrkFWZbhqquuetQIdr75zW/Gb/7mb/L/l8vKYiBNUzznOc/BzMwMvvSlL6HVauElL3kJ8jxne5xut4uf+ZmfwdOf/nR885vfxL333ouXvvSl8H0fv/u7vwtAlAl/7ud+Dr/5m7+Jv/3bv8WXv/xlvOIVr8DMzAye97znndXxmpUaLFOsVkrQhDLDEcK2KFUHa7J0nOawXJH/1islbt42XA9pIFZyXIqPE64c5VmmQX4iKUyjDKdkJcNdDVB5sCf/LkT2gpMBV8bqO2pcBasszcEuSq8qDdqjVbZhmWjsF/AgQQRWc35cNNRR/oEWNa9bEkgxTBbJy4cBCxCyMGW3heCwOMbWdw9xk/uU1Iuq7VlkAVHL18RQU+Xlxro0mt9YFqvma2oar2wro3NYrMJb32sj6kv2l9RYcnyl+xJ1BzwupdllFGan+RwByWSjil6UIFhTYp4AUN+7iZJc1RpFX+lmyQqRjXGdHCYieAWYEjqgylQapwwx5VnGVRWq9GRRwnCDo3kw6t5fxZkp/jfaFMc6bG1yczTBILlps3cZoHzyqNndrDZhT0vvQM/X4MvhloqUYTuqmpRlDPkRVOQ1a1xlEDpV4tqc/PZhAMDxr9yH2cvFtZ8+uBeO1LfJolB5GUpBWMMyueJmOvYYCxQYr1SWtm9jv0lAaHMBqhpEEBpti4JYlq6vvBS9qZqCD5nxmfBzn4QjJZ7p2mzhQn6VAFCT1Ry36iNqdwAABYLT/D1AqS4+mKsxpKqp4xcwdWCn+GytqTTVhgFD0tQ+YFdrMEmgFkAciKZwEpzsHT2JmiTMFA+EMGVliMZnuN5WXnWOzT6U5YUaV9x0Cxg6b0BpdLmy4jy1r4GZg+K47aKrbG6yVM0t5JnpevAlw9SwXdaBojGIgxFX+3srfdjS1ojurWJjFijKc3HV8ZlhF3lXEAESqW8HKJasfgws6DoYwtYgP72KCojq36AlznXUHfH9Y/pV9dwS9G0piPlCx6OZzXe+8Z73vAc33XQT3vve9+JlL3sZ5ubmcP311+NpT3sarr/+elx88cXntN1zdk7cs2cP9uzZc65fv2BRqVS+Lz3yM5/5DO68804cO3YM27YJOOA973kPXvrSl+Jtb3sbqtUq/u7v/g5hGOKv/uqvUCgUcNlll+Hee+/Fe9/7Xtx4440wDAMf+chHsLy8jPe9730AgIsvvhg333wz3v3ud599MlWswIB6iVI/RHGmoajwElPvP9hHcFJMCIPVFj+QTqUBeswcThQiTg6E0KWENPrid6HeK6MZPdJEP335dk6gHL+4RWUYUC8O/cXmVn1OopyFnfKDFk9oVqXOE1Wus7DkSzQ3TBgysTIAgJIp+W8WdBWFe2PAivDbflIwMIqXXKW8z04e5WTJdJTQH09YWq9XnmZIhhIitcgw1UZZ9n1tHu+x2CdBNoVqAWFLjEsaRgzrdA+tII0Fe4sE94iCDgiGFvWuEdxR2bXEauiG7SAnVhspX3s+7JIygFaeakNN1DXj49NlFFxi8clJ3fE9zF0jhDa97UtKeHTQY0XtZKDMVcl7rgjlQ0dwnmGYKhGGSh5NKRlh1Zpj/oXqxZdp33HVvxo0l8njopYUIfEh1bWjhKFlgo+iIEb7e4omXZO0/tLCHPxtIvmjxDAOhnztC40K9z9RcpLFCS9W9IQi22zxi5QSBT0pBxSkSHAdoF7U/kKT4XOCzrNYJVPjTNAC90zFMul2yw739nh7LuZkSR9LYpzlYX/M+BsA/MUZ7t3Lo1BBqa6HAvUJ8b1XZHZlPlIedIbGGCb5lWQ44mRMT/rpfvGayunBLimxW1oE9k+sq1aDi3dwYt87LiDN5sXbeV4xNPYwbJcTdL73ak0el6zXwWCFDKnXeSypnzNPM7QfkObxnnhmty/ugDm3U2xfEw/NbXeL9EYeBshpcai5O9C5jDo9vg+E/2Y4NkaAYPSJfy1lSu56Y96Q4u8+Hql4NLP5zjde+MIX4oUvfCEA4OTJk/j85z+Pf/mXf8Fv//ZvI8uyC9uAfuONN+Itb3kLfN/HjTfe+AM/Wy6Xcemll+KXf/mXYT2CmTTFO9/5TrzlLW/B0tISbrjhBvz+7/8+XFfc4F/96ldx2WWXcSIFAM985jMxGo3wrW99C09/+tPx1a9+Fddff/2Y7P0zn/lMvPa1r8Xhw4exa9cufPWrX8XP/uzPju33mc98Jv7iL/4CcRxvkacHgNFohNFINZSfbgA5iUlMYhKTmMSjIbIsR/oYakA/Pfr9Pr70pS/hpptuwhe+8AXccsstuPzyy89Lg+ohJVO33HILYrlCuuWWW37gZ0ejEd7//vfjf//v/42//uu/PucDO5d41atehSc84QloNBr4xje+gde+9rU4dOgQ/vzP/xwAsLq6irm5ubHvNBoNuK6LVdkcvLq6OiZZD4C/s7q6il27dp1xO3Nzc0iSBBsbG1hYGPeLA4C3v/3tZ/QdyoY9ZJmsIA0Vy0q3ciDbGMMyuEoVrPW43F5vNLjU7JKGUzhizZxRlHBZmypUlgHMFESyO3twBgtPFlYROgzCjc0aWyzPMo2JJpLG2s4F1C8W3zfLdQUBUclbNqQCwjuPG+4tGwaVwGk1YJvILdKvKo75o1HQuGRpjqGEAzZuE6ygOc9lTazBaosrBsWZBjPJLPl3O064EpBp1TtdDJUFKz2bm/fpGhSqBYYEkzBC97iozp267xRGm2LMZi4V+9z2ZJuhiTQcYfYKARvNPEX4TLkXXY1cWrEgHsFwxlfbAgIjdk+m6UGFXLWgYy1NF+GQkGF3gOxe6e9GLLClea545Um8RTcJUP6FYWtzTGiTGpKn5XF5M4vIfFlNsgssYqrYlxZXMvT9GNpl5UbuJBrzcKQGXINgPtdjwkIa9Hl7pLeWpxkq26UW0oGdKEyJqmA6VESBgAkLSnestDDFTE3dKokqU7BdVe1srXKVlvTWhNfbkMe7e1hUa9oPdAAIfa7mVQI6sJoLSFsrY2Mtms4lVDhQBArDMpF0CeIR1dDK8gzcmVn+LjV703lZ3p0oyflLwP/iWKnx2fGLY5UdHuOiv0WvyzAtRSg4A0kgzxRLeLjeQSC1sKiq5M83Ud4l7nOz2uQKUtZrMyOQwvE9rs4VZxoozYnnpikriW6twnpkephFX8FhpG3W6yBpq+tN8xVVcA3LgFeXOlNVH3kqSA3HvyZgzDz9P1h+viQcXPQkZB5V3AqwYrkglmOVBT0lvOuVuLps9qT4rRfyvZGEkVaNjOV3CrCLDh9X96gYw6lD96Ik53SqULFV0iTOK5785Cez7tTTnvY0vO51r8NP/dRPoV6vn9d2H1IypcuvPxQp9ptvvnmL7825xtmYH7761a/m3x08eBCNRgO//Mu/jHe+851oNuWkoUFaFOTJQ3H6Z6j5/Gw/o8drX/vasapet9vF0tIS8jgGHFnaLfoMXQCqh4BEMPM0x8LVItlZfuZT4OwUUI3pV9VkL79bGI3G2GX0oiVphfpCGdMHxJjMP+kihkFoQkoGISuB51nGE2Rxps5JAcEcaRzDkjIK9tyy6huQE1q62ULrNvFCLzTuROOnniaOZX6XgiRGko5tWmMJFL9cJSPMrDRQbIoJyS7a2LhHTJSFqvh3+mAES5rlGpaJNNAYi0RlpwRFqw5mGvTGatFRyj8DYJV59kT0HE5QLMdGZVn8fvaKZX7JkHSCpzEuG5fth7v/KnHedcnGcopMuzZT1QfCPUZJzFDpqNNnNmDYDjm5I3HN4myDYUW9F4ylAGxH81ezxl6i9FOxKSGsIGQWVBonnEzxuAVdgF42lsMwBcsWuB5QUC9vfiFo58OsvkglMvpLku+BUlUxZrIMJYnm63TzkewtooUG7zcdTxjzLEcGlSTSgoHO1fJUX45R8JRifJTAkosIEvLM4oS/1zt2kiVHln5K9JHOPfNnYG2XDNZRwImJR708nb7mSVjkXkcA3Ic3tV8khtNXqnsHXoW3FXxLNNKu33ECU3tFT+Hcky6BPSVaAXzp1Qjb5ZezpcFI+SjUZEjIRSFFLpmzeaSMwlngdBipPqdGhb1E8544fn++Oaa+n5GnoCY6azCkXsBAzidZnKB4qTjHAkmnjIYKGjbNsWSdxoDmm2yzxc/HmLQHCehaBo+rWymhcZF4BvtyYfad/99dnHjt+68+jF1X8jZ4vpLXbnhyHeaG6G0t7lECm3x8wFivJPXiDWWflOu76riqBax/VyRTg41/x96fF5+pXnGVHLZHTgE9Pc/K1Pl890LH9773PZRKJezevRu7d+/G3r17zzuRAs6jZwr4/gnEwYMHH7aq1NmaH+rxEz/xEwCA++67D81mE/Pz8/j6178+9pl2u404jrnSND8/z1Wq/z97fx5syXXVCaO/3DmczJNnvOeOdatuValKpbkkWTJGNlj4e4C/br4Pggfd0AZ3OIg2uMFA2w1E2NEGO9qG7rDb0AxBT34BHXSDee1o92N6T5jGmEHGIx5kyZIl1ahb9946dcY8J0+O74+919o7q4RNSWiwfVaEoq7uPUPmzp25116/YVHs70vH66/0GsdxOGm7Omq12pftmL2MZSxjGctYxoshvpaTqStXruCzn/0sPvzhD+NDH/oQfu7nfg5CCNx///141atehTe84Q3P6HOfUTL1X//rf8W73/1uPPbYYwCAU6dO4ad/+qfx2te+FgDgeR6+67u+6xkd0NVxPc0Prw6CJAl2u++++/Cud70Lu7u7/LsHHngAtVoN99xzD7/mrW99K5IkYa7VAw88gEOHDnHSdt999+H3fu/3Kt/1wAMP4N57731avtSXC1FvwmnJnX2RxPBVRSIeTngnSCoty7aYdF675R6UPaUwymLdQsKAgtgvJvDYn4qIl61jW6x6E35dK0UM9Rj3tDJgPukppXyHiGg7nmH+iLTor02GRllaQVVG5WO2P0TzgqxS2c0OoCpOVLEoxleYFAvH410ywVK23UNNVeH8TsDVGPKgceo+V7FqnSYfo2WLa2GMq4wEr448yVnBl8UZKykpnMBhSKa+3kHjiIJIHQ+56o3H16DR4Oqde/gEikBWGkpXE1q5VUUWc/9CqjiWccSVwLg/YjL8YrSApwjYpJZqG55ak3N7fAzc/ids8RhZrgthtDUpVPsal8w304zVRn4n0EpJardh27BIfRlPkZ57VI6XqhLYYbNSneAeckWu5wWR7F1XqzajMaAqGWal0mwlREFqRDesYbo7UT8PEKp+e7X1VSZd09y1/SustgvWO9r4VAkphKerd5aw2YSxSDPte0VeRMWERRHhZg/H/p8augUg4dvcgMtUpY2heei2QmWhWz/ZvsdjxCaQwma1nKiFcA5JHzPqoXfpU+fw1MelIaRwHWx+o9zAWQrOE0HIZPsyz1mUYF4PNolMYqOH46QCgQISjiSVoTku1I9ydGaXoVYI26iyJpW2QvQv/Ty9eADvsDxHZ1W1C2mu8v1RiTwHpspjSz038vmsUokkOoJDcLXncPstN9TeT4e+YaEOVWhfvlEfTqK8pfIMxegyjw2geu8piNZt1bVXnBpj4TqV5ww900nFCwAN5VvX2GpyVbPMS01WZ4L9tX0nl/HM4vTp0zh9+jR+4id+Ap/85Cfxq7/6q/it3/ot/I//8T+ev2Tqve99L972trfhjW98I17xilegLEv85V/+Jd7whjfg8uXLFajt+YwHH3wQH/3oR/GqV70K7XYbH//4x/GmN70J3/md34mdHZl0fPu3fztuvfVWvPa1r8W73/1uXLlyBT/1Uz+F17/+9WgpGfVrXvMavOMd78DrXvc6vPWtb8Vjjz2Gn//5n8fP/uzPcgXuDW94A371V38Vb37zm/H6178eDz74IN73vvfht3/7t6/7uEWzA6F6HFpJzIun13xKP7TVv7PLczzx/30IAFDr/D663/Jq+b5mB5l6wBKHYnrxgB9YXjNkOXSgDMssz9e8hSwxTDVJjWJDKNlzOSn44QLoRZmalZqQSBlHrERjrk2Rs6qnmMwQXdhV5/64dllXUeY5l+vT8RhuQ8FoxMWpBWyoF271UF/VcBcAjB6/iI6hqOHeYGnGvd4ILlgMJ7yICs9m92GKbK4TKGG7DKcRFybaj9A9rh7AhjLQsgVmqqkyqc9ax7cQquNOzz3KCadQi0XpBRDKEDAf7CNXijF2FJ/PKq7llPwJW7BVA/Hd3FbdUJol3K+RVVbJVZAONwoWnABTEroYTpAqBWj7+Dr3QeNmugDKmUxAskvnkF6W/BPubxgncClBmk2MBMVITA2Xe4JHyizlvoQFOT8byXC+WPB30Hm5oQ9hy6RmfGEEJ5T3QtcWGrIjHmLos12BcB3kistCEfRa2uwUekEzj53Gyly402jOiaQzlP+KZkcfu+fDVpAbO8OnCQQZ4IZNiI7mBpGK1SJVa54j25VSfkHzGdpk1fUdTFWiPT7XR+u4XPzJD78Y9fnamS70QJW7BsgEiu6ZbDqt8DlpLMloM49TA072eAyZm5fE/Flxf8Q9SGks3TDg5Da6dAWjT30SANBW4+YePlGx4OBmysmcFaikXMyimBORrLIR1MgAfZfte2wDopW/LrrUWL23yfdlMb7CY18YY0/zMLp4gBYlrT41DNd8OkAn8/We6o8Y6GdOMomZ/7d2+2F0TyueHfHasuev2pMXz666dBWq/qKKT3/60/jwhz+MD3/4w/jzP/9zTCYT3HnnnfjJn/xJvOpVr3rGn3vdydSv/Mqv4Nd//dcrbuff9V3fhdtuuw1vf/vbX7Bkqlar4f3vfz/e8Y53YLFY4OjRo3j961+Pn/mZn+HX2LaNP/iDP8CP/uiP4hWveAWCIMBrXvMavOc97+HXtNtt/PEf/zF+7Md+DPfeey+63S7e/OY3V/hOx48fxx/+4R/iTW96E37t134Nhw4dwi//8i9fty3CMpaxjGUsYxkvtvhahvle+tKX4u6778b999+P17/+9XjlK1/JxZRnE9edTO3u7uLlL3/5Nb9/+ctfjt3d3ad5x/MTL3nJS/DRj370K75uZ2cHv//7v/9lX3PHHXfgIx/5yJd9zf33349PfepT13WMTxtenbuSW9A7/lq3yd40bkMTpWeX5S5nfGYXLaUKsgKtkKNS/PjMLu++tr7pNGqn7pKvNTyFLKNtC5FDTeUWw0OuA0sYSiy1m6QSvhWEyIayEjO7dA6OL6sTZFwpgpDhybg/4h3g/MknUFPfS1UASwiG9pJxxL3Umqoy4PS0h1iw1kHnuHwfwTv9h87yzrmxvcaEaacesEcMwQFuGCBQJX7H97RCjqoqgVMpu5NH15QhtoTFAWkUG1WPgNuymARbJub3LyF+8lF1XBIedbaOo1RKoGLUr1SkAFkNKI32PeG62vkGrm5dc1wbS5LirMwLpKo6Rqom2/fgbj5NRaLIUYyVJ48icGfzFM3D8jqv3HyUoSmqnOX9S7wLL4sCdqAgNyLdphm3HxHTSHsVGdAHV/Q8v2JMSMo9MsUkfyYKUsDRnLdsm3f2owtjXPniJf6u9jEJTxIJ37JFRWVIlTjyCgvWutpwNRozydlrayEBXU+7VmPzydmjA1z5vKxerKnqo7Oxo9uuBGGFnAzIipxjtBwxlXNaeCE/q1zEXIHJ+5fYHHJ8Rp7rZHeqqxunj6G+vcVjA2gITw5cgjJz9feq4N6X/V32j8vjhKs9uVHBqalqz2IwYc83quq0b79Vej6p42aD0DTjSjfNgjSaG8+eHP2Hqv3TOrYNh33rHICI4PNIQ+ELOj7DJLPuV8xo6VxozjlBjUU3JP7ZeOmtcI/JqpBodlAqBV8RRxqqLDR0TmM7749RvyKrke6qUns7LhvCeka/zFpHX2PdPshC96R8TvZOn2AoncZQLF5sTVq+OuPKlSt/p+Tpt3/7t/Gd3/mdCMO/m7/XdSdTJ0+exO/+7u/irW99a+X373//+180LuhfVeG4KMmksiy08Zzns1ybHo61Vo0X9/3P7aK+KfttdZOYeRi04Lihzy7DeZywPQH1rwIMqMXzYRFkYTzwmO9jKgzjhe4LR01lGx3YC1KaXcR4KJO8hnpINI8egttVrsqNBhsjTi8eYHJOJl4hNSHe2uDFxmuFLCWm17WEYCjSCWpYPS05Cq3jcmEdPHyOHbHTaI61u6WKqmKApx5+Tt1H3eiJNlcLByVTxP0ApLEe8c6Io+T4Djo3yAdd69gWL9TJOOIFnuBNt1nXPCXPh1BJ0vBRKccuHnoS9U3tOk5miXaNYBStnLJsG73bjwEAOrec5IcuwZdFNK4kDRPVy63/RSmkGJ/ZxaFvUjL0U7fzYlKM+tw/kBLS1s66hmjTjJM8Cpn41q/6f80BAoA8J7Xdgu0EAKP/n+K0CDfRnJJxpBdtk3Ni4AfcLYBd7FNe0L3Q43tlcu4Abl2eg+m4bW4cqPk1u38bSXsZRwzp5YuF4T6vuE9ByI7b04sHrOyjxd3y6xq+TGJ2Tqd/IWxD3q85U1bYqijuAEhISyns8sWCeyxOL6okeG+GKJPj2vrsGYRbcn4SPEvfx99LkLhhg0AJQ2r05CzSzDCcVJCi0Sha2AJ1NQatW6XK2Nk6zvOhmEew1bMlNFzJ6T4xkyk3DDC5KOfsxb94WJ5rmmHlpXITZPe29MZkMuQNQDrVsC9BuJV5eFVDcPpeCpPflTzxefmj2fvP9TQXSv3rhgl/12I44eSTVJQibMEznjdk4suQe1Hwe4A9HuPxmV10VRJFMB/1wHw+4mu5MvV3rUL9yI/8CF72spfhhhtu+Du9/rqvzjve8Q583/d9Hz7ykUVprIYAAMkmSURBVI/gFa94BSzLwl/8xV/gT/7kT/C7v/u71/txy1jGMpaxjGUs40UUX+umnX+XuLof71eK606mvud7vgcf+9jH8N73vhcf/OAHUZYlbr31VnzsYx/D3Xfffb0f93UfVjIHqDO87Rn+P0KXkpVhH1VGAEm4vvxZWQp3Qx/1LVlWDjZUi5kw4PJxMo6QzZ8AoI0bnc6KVlnVAr1bpXYiUaxJrWGgvWVivTNn4nDNZ3jSEgLTXVXhUbssrxkiONqRf/d8wKhMjc7K1zaV4d/6vQWfi1P3ESjPKG6fMovhdlSV4chxBOp7aZcf98fY/4L8LCfoY/W0OlbHY9LoYl/+PU9T7vtW5Dnvwkm9Nh/E7DNlCQtOoEirqvrR2Gqic6OENIKtDSb0p7t9hidZkRknWLlVvs9e24Z3SAoB2mpcR1+6iNHjsno4u3RF98szer0RwdzbOqwJ+cLm/oUEi5VJrH3Bei0Uqlo525djHQ9iHHxawowbrgN3XXYEKCZDrs4RJAgAHVXN8XorFcIyIGEogv7KIkdJBHNPKfHEUPeFTFNkRtsVs60PICETqh7MDoaYnDvgsQeA+nqb5y9wrXcUoInFtZbHf59dnsN6VCrcVm6RUGjnlhNwNpWhpK8NK7kX5DxiOG1x6RKGdG12r3B1rL4uqwyt41s8j2qGnxhVQ63Ohq6kPPUlJGdk2xKqrLm9VV0RngwZunPXD7EBrqUMXUWaoqB2LlHM7VxIFJEWBRK1kA2eGGJF/X1VwZOiu86VDhE2NexXFAYBXRv/mm1yqAJjjjs9Y4TncBWMRCWi2eHztvKcz0WELZ6rwlNVuiStkMXJy22ovJ/2PvElvrbNU1rIUERjZGPtAQbIZxwJV+C4fF+aakTyCBNByFXHhfKLmvdHBoQ852dffbPHClH6XZkXlXs07o/Vawc8FhZVtuot2E9jfso9JPMCe5+Q5sO7n/oUVj9/BgBw/P9SasXDz6xn3DKen7iuZCpNU/zwD/8w3va2t+G3fuu3nqtj+rqK7NIZFAvFGwqbDNVYtUBzSdRi4jZcfpDHw5gfoEHvPJfcPeVz5dR1MrUYTrncTf2xLM/XtgOOB4seqsSdyguGZByjWTQw4p/Y/NLzjfK38WAZzNWxTuAfKfg9VFqP9iI+B+Ieea2AFyQ7bMBXtl20ADgbOwwvFvPomqazRZpqmwTf0VL6LOHFghR2Js8pj5Nr4D3b0xycoOuzCzVdl87JbQQq8RNhS8NsaYY8VgacHrlkG/3EipyTT+pf2PV8zPfIdXzMjt2UkDq+x1CS02houwDH0wuWAdsSDBGsdeEQxKXGdX4w4IWr/9CTaChYCtBGrLSIxoMYkwtfkOd7bg+rp6XTfe2QskaANnq1HFdL+el3WQpbJQd5kvKCBwC2srWg+WW5rgEte2wJMnlqysfSPqpguDBgF2kK4bqs2HLCALWWmmf7E0T78rwah+W/zvphiKO3qQPxYCXy9/ZEJdpZqo1T84IXcsu2EF+O+XgACdUQJ9DvtRAqWMC78S45Fl4dYiYX17x/iWEdbtrsh/q7ilxzwPqXOCFzqNGyscnK4gWbS5KFh21ZaJMJsC0YAqX55vQ2NeQtbG2NsNBwF3G2zKSp1mkwREXH13/oCYzOyvMKN0KdoBC/y/aATCf4lEAhS/ScVc8gNwxY4VfmBd9rpFo9+MJlzC5Lq5vNlxywRYffa/P8cdcM3pmKMonhqmdHjZJIQ6VZTAasHg4UZzE4bjOcPfzik+g/JE1QB48doL4qz5H6ltq+xxuAMteO8HQuDq5ymecvVtc7TdkR32vq/oTZPOM5S+728Ay+3nMcefksYb4XcW++5yrEV36JDtd18T//5/98ro5lGctYxjKWsYxlvMBBnKln89/XW1w3zPfd3/3d+OAHP/gVGx4v4+8W5SJGekaRLBcLJhyXhikhEXCFsBhiypOCqznxINJd5w2iLEEP3ZuPStKm+b2xVsGIbsg9pYjMCRgE27Cpd5UwoCeDvErhhj4baUZ72n+luaOUZM2OYVyXcIuWzlFZ6q51mrzTc9dbcG97mfxgn7y4IvbSyg8uYrEvd20MqyUZw6FuWOMqmDPq826RwrIFf1dm9EL01fuD1bpBZK2xRwyZ/AVrXd1FXtjsz7MYTtiTqqWIzbVOkytqEDZEQ/5eqN203e5BhOfkz975ym6Xvp9+nu8dICBjx+66JjezMWTK3+VAQxIm5MgQ2O4Vbr3h+J72NlPX2A21v9bo7AC2LwnztLf32k0my5stYHiMHZfntLBjZFR5FaIyv3hc5pH+u5rrpXowT3an/Lv6uq6aaOIy4Dfb6mefqwQAEO1JAcO5D0uj4SJJcejVsgrrnTzNHkbsg+XX+RrVVlNWiCWTiOc13X/u7ojFHm6rrgnml5+Sp9VeIL0kr2188Sm+LwleFWGT71tnbRuWgr7S4ZAhQSazB7qKZariwg1ZMfEaLmxVmVq/YwNrd0tREEH65nhZtgvL1eIS66p+ecJ1eK7Xt7c0TLcnzyUZzzG+oGCt1YDhXsuXlaLCrUGQ6s7wDTN9zuhfp9GAp+a82QaLoXXXZqPa/KNnMXpSVhCbhztoK8NSUrNa9aY2dTV7WpJXWJawGMTurnOlip6HRRxxFdvxPfbNml2eo/+YhALpWLzQ5epzvRdy+yi6f8qiYDVeUe/CStUzaK7GItJV4WBtBc1teSyjsyN+NhKakPha6PFcx9cyAf25imek5vvX//pf46/+6q9wzz33XCMb/Imf+Im/t4P7egh7dQtiJEva0/OPMLwDGG7P9FrPBpRzbn01wMpJeeMdvv9O+Mekqo1K9EUSszrFOXQcoi5vyExJ2uOL2hQ0uEHLbwk+ckIfdqjgFz8EaJGzBauv+KEeR/yz49f4gUJqqnl/isHDslRe35zww9L1HU6i1k4fAwCs3H0buwiL7gYrWKyEDC0PtG1ANGGOD0u40wxBT87JoNfWHJyrerUBkl/DyUpeQJCNgoJMbddhJZvXrDPsSVyyPE4gQu0WTcewGETM+airZEq4jnaEr/mwWhImoCaqwnYBtUhl8YLVZSu3S9sDu9nR7uFZyo7x+WC/2qeMQv0swiZDKTXDroD6vxV5wX3C4oE2DfSUK7PtOQhWlUVHXVs+EFSaJ6lO/ArNH+GehYaaygzhOTy/KCmH4cLtBB4vJgRzZ3HG/dPc0GXDSJpni/GCoU4n8J6WU9VXHL354BF2xt6E5vnQElAmsb7/hNAJUD3gZJuizAuG1LN4wVBphzg8W4f5vpPXVt63lHzYvS1tw2CoJYt4xhCPpThsBLXJcRFo7ayr8dDmmaz0fMlL9CbKSC4YIrY0MGEZ/RopiQw2UsBI2ikSxS1MooTHonPqCEORRU05w7sBylwpMj0fBSU1aQoIeTzMwRM2PGUX4E0iWJeqoIkbugz9ZXHGiazwJmjuKChTKZUtoxekBeiefiqZykd9WJTECKGd3xnyjPn+smzBmyjH11YplFAP44w5rd3jHYZux4myCXpyF13F1fTvuI9tcBga9+uwKUlyPIRbMgG3xFlE+5rzCgDihucP5lsGcPTo0evqaHLdydR/+S//BZ1OB5/85CfxyU9+svI3y7KWydR1Rpks9MLnOcyRmVwYsSKCeAPzQcx8npUbu9h8mZQgBydv5gU1VwRIYTot+/XKrgyQ5OvpGbm7m/dHaCkfHnq4OStr/FBFkRs7tRp77dBn5oMD7fWSF7yQNg/Lh1gynmH0pFxMphc1L6DW1rtiInzOzp1HoD7L7m1W+A2AfBDmAynxj/sjXrho3Cwh2Jm91mloDsN8xlUmOj7LFnDVgpfFCz4u25D3s3O2sJGoDvZzlZhFFy+juSPH0wl9RIpEX+QFL3LEcwLAlhBWcMCLHHOMhjpJrG9vwSOfG5JFJzGfd2HsZss04bHnMJMqw+HcUdUTr5lwRcN2HW76ms0T/tkkUtPDPIsXnEyRf5fwHObQzPYHmO2rc7ykmr/2WpXmyPRzbaWtvcUokZjFum0KtFs0WVHEwxiLsar+jRNOIGgxm+5FfH9Ytq3bHuUF8+jWT0qLACdwmCMXfekxBJTEEO8sS3nBy+OEK1PCc5h4Tt9fGo17k3iGuK+vDwA0DWK132szT45FBF4AKEdvy3VhUZLV7MAScq5Nzu/xv+w/F/o8P2nOt45vwT8h546zunlNpbASRaZJ54uYK6v0/U4tYC6VWVkiD7IyL9E5KseiubPBXKmCnMotgZKq12ELgpomZ2nFSwuQjuE0D4I4wVw9x+aXFRF8nnFV0hIWu/73bjnMCfRTf/QnAOSzhIjivTtvgrsj7VHI6wtFob26Rn0+R3NTYlrEsFdc4HDVj/h8rpFgzfpztsUg7mgaxWzH4Ry6xEm72Wi8NIQj7OHXrjEnb67uqWB8Bc9XZEUJ+1lUl7IXcWXqQx/6EL71W7/1af/2H//jf8SP/MiPAAA+//nPX9fnXncy9eSTT37lFy1jGctYxjKWsYyvyvhahvm+4zu+A2984xvxC7/wC9x/9+DgAD/0Qz+Ev/zLv+Rk6nrjWbmAkQ8D9axbxvVH3n8KidoVTy9eRjLRvJ7FiFRnqgKU5vCVLcDKqUNonJTKKqvm6352A1lStn2PK0fFqK9/5t5/IcJNXTki80hWydx0F+80s0vnuIJSW19jvgHv3qIxu1Rn8YLNRtnMrj7F6IzcWQ+eGHK53m/V+GeCyGzXYTjNN/uG0fFPhvxdaRQzXEXf5ffarKySYyrHJZkYlamuPC8rCHlXWisK3ZOMFFC2NgiFEAz5UQwev4TxOVktCre0KWLj8CrbGJCqbnH5CkZnZOk/jOZok7JIKc7ywT5XoZyNnarJKGT1hhoSF6M+9yMz5d6mRFs3yU4ZliW1VW11hRv/ZrO40uOOqnb02nQyw5WxVoVeDd/Z3XU4XQXxhj7DUlQpNE02vU6DK3J2u8dVIKrIlYu57ik4N3qqueQi73CVNou1YpKizEvEqkoQ90cMpwW9Nsv29WsLvp6257LTfMY93XSl0hJVbh070avqQ55krI40Iag8zXmsGoflnGRoE+CuAwKaZ4SwC5tgp3nEfJnZwZDPS5tn6h6NdTX/ZGNdXZnkyhOZ8mYJw15lluixjyNdIVf8KrvZQUHQ8mSom1CTW3zgcAXINBe1lElrKWzNRQtasLvq94s5V9DpuITj8Zz3ALSv6kaQJ3mlOXC0J6/X5KkvcMWKIOoyL9hyJU8zbKr7ilR9lhCaojAZIFXWCmbPQTI/XgymWAx05ZcqYsIja4QSruKIplGKJ/7kicqxbL1kS0OzWap7LZKBrxAoqEqXad5m0PUhFLxN1fX8yh6W8ezjIx/5CF772tfiQx/6EP77f//vOHPmDH7oh34It956Kz7zmc884899RsnU+973PvziL/4iHntMkjlvvPFG/It/8S/wz/7ZP3vGB/L1Gsn+HqCI0YvBhMvHtmczvEH/Hv6mU1i9/5Xy7+0ee+Lke+eYiM2ePUHINy43ioWW53obWwz7OP6Iy9JMijUfjjWfu9Nbnl/xMwKq3C7hOiht1XHdgDeI95InOSeHi7EmQtPDJ9zswSe7AYM0a5kcoLG2byDJOrWF8XttLR2fLziBCnpt/lzmkQjBC4RsxDqUv6dkymjGm43HmB8onypVyl+MF5zw2p7Nbuz1Td1Alj5/tj/A9IKEAW3XQZM4aEa536Jm0UnMCy1DD0VeESVQu5jZpSva60fBk36vxeOyMBr4dm+R3lbO2jbzSuxRH7Z/iceTrj9xZOz+LoTyWIr2IrihXKSYxOz5muwubDQoQVJj6LTaOoFa2wYUn8bKE7a1YK5KEmsuVpzwImIuljnDeBYnK4VKKJzA4QVIuA5z9xrba3BammsE6OsCyPlN5H32xIrmPDctW+j2J0IgI/fqnOZ5ylBPnuRIlU1BNlecqeYB+4Y5dR/FjPg6NKdb2t3asmDV5Gvtdg+1bclDaqsERgihvcD2Iv5ethK4+ag+x9Swd2D7DFsTsoucxz46d4G5jJR41o4cZ3GACEIUk6q7fXNnTc+pjR0+bmr1gmzB8CWEqLi8z/YUJK7Oq3Ek15ytdg/+tnJLp64E0QK2p8+VEqvFaMHzg8jq4/NjthVoHW5qSJHGAtCiiWYXjoLNk4lMVhb7U6QzcmifM8G85tkMIxdGUk9jb3s2WiqxahyS49bYXnvapt7EVyuLVD9HE23VUl9vwQ3l7+leji/r5srPdXwtm3a+7GUvw6c//Wm84Q1vwD333IOiKPDOd74TP/3TP/2sCkPXnUy97W1vwy/+4i/ix3/8x3HfffcBAB588EG86U1vwpkzZ/DOd77zGR/MMpaxjGUsYxnLeGEjL8tn5RX1YveZ+uIXv4iPf/zjOHz4MJ566ik88sgjmM1mf+c+fE8X151M/fqv/zr+83/+z/gn/+Sf8O++8zu/E6dPn8aP//iPL5Op64zoqctIVQUnj1PeZQHg3RftxhfDCRu8yUqK2qlkKfzD0ombIThD3muFLSajM1Q0m/Cu1G2lulcUwWnRuKI24l2dQXbmPoJ+HTbt0pOUYQiCTJJJxNUoYQsuiwtbYNafVc51dGYPzR25Q/QdT7s1q+MvxldQXpCQpO05TLwlWCoZTnHlkTPy++cJV4vCu16qFVsGPMlR5LqvnOo1Z7kuVzCmFw+w/2lZwicTyTwt0D4sd6ArtxxF44Su3lFVkNys01nMY5BMIhSKTF7ZtaooswRQhROuYhS5AdWklR53BImll9UOexwxHJcbjvVsgdCLuJpk+SE3KkZRcEWS5dzziHfGSZQi2pffQXCc3Z7AUuMJYbOiiz7H7q5rqKcsgFTCmkU04XMjYnM2iw24bHGNGs/2bK4CuL4mA6vWlvBCl2Gn5s6GbrTd7GojSuOeIIWrVfO19YBNJGfBFchkPOMqazrTFSuqVqVxxvBikRT692N5vS5/4aAifvDCvPpdjovS3BFbRm8+dT/6NJ/S1FAOZlzR7ajmwu7ahq6yKZK1HAT1mX6oqzLCBrpkNtpnqH+s4Oi1+QKN2+/iMaIqKVWuhOuwk79o91jFByKgFxks1STYKjJdzTRgU+q5mUYx223YPU2cp/s7mcwgPFmlyuYpw5umXQwp7EZnx3Ab8hzbJ7Z5TnLlLE8rSk2qvtU3tElrfIW6BURwAvlZXrPOlUuqVjm+xzCe16xzhZ/Or9Zpakd4w7KBrk0xHWqoNU25D2p9s1cxsAWAiaraLuPZxb/5N/8GP/dzP4cf/uEfxrvf/W48/vjj+MEf/EGcPn0av/Vbv8VFouuN606m8jzHvffee83v77nnHmRZ9jTvWMaXi3yR6Id2lPBDwrItfihzw9aLA7QuKt7Njq2ddcMWc3O4nN/u6RYvnn9NAlHmuqxuh03kqtRdqr8TBANIaEB3S9dJBwj3T2J+eCSTmcE7UUliknFZHEClLUtdJS7ERVg9fVwvgo0Od4ovHQWHzSbctLV2aLtiFwAAYhZjti/PYboX8YO/MdfJZeW81M8mVMnnJ2xkM7n4zy71mQtDPlardxzG2l3Sx8dZ29bwSRzx4kx8pDxe8HkL19VNWQsJoWUzreRxu90K/Ef/cuJV5NqeIdWLFPkx5XGKBPLzJTyiFIMEYRmKOavma58d47h1op5ou4PQ5cWb+EaW5+tkaDzSdhoqWSvjCHA0X4c/P454LhJsnEZznjt5nHArH3PumJAO2TeQlUV9rYO60dKE1azCZm8y4hQCgKuodbbraY8kglUd7Ww9vXhZW28kOfu+UWIHaC+40i6Rx0Xl7+FGnflbbqtVaXgNqLlHEK4lUFIy5QWsQGNfJNfVUNBqgMa2PN/2DYflcTQ6ev6a1iqmwpPmSxJrzpJfR7Amj/HSJ+Smof87H8XKjV8EAGzddztzDflj0uwalTAAbWcCALZaEwpjbXA8VnWaqtBKo2V1vKQcrq91uC1SmU95rtM9BQB1W86DzZccxqFXfwsAwL35G1DSM0IldkgXxvNwwvOPlKSWLVgx6a+0GaIF9DNNGC1mCELOowm392HF8uYmw9wibOrnzEJzxngMi5zf5zXrzHWk30V9DfM/1/G1TED/9//+3+ODH/wg/sE/+AcAgNtuuw0f+9jH8Na3vhXf8i3fgsXimSWt1+WADgA/+IM/iF//9V+/5vf/6T/9J/zAD/zAMzqIZSxjGctYxjKW8eKIr2UH9M997nOcSFG4rot3v/vdeOCBB57x5z5jAvoDDzyAb/zGbwQAfPSjH8X58+fxT//pP604o7/3ve99xgf29RK06wCkMoTgrmSaMCy0cqPcMR579T3wNuQuJ7tywG7RbtiC6EpyNZfay0I2UQZQxlNdkaLqjEFmtjwftG+lykHev8QwjOX5ejfturoHnfp7Nh4xcVjYonJOgNrBGpAN7+KNigNBf26o4QQRhBryUKadluNyg9pyHiHdk9AEwQXTc3tMdl+9aU1DXF96BAH5Lan3w3E1dDYbIxvL6gP3RHQ8rhrafg3Hvu12AEDnFqmiFK0ejwGpKSmookUEcNuvYeMeWcVqHN3mqmF2hfrx6Z6HZVFUGrXyWChTQtHowA11hSWb05xRLtpByR5ITuCyVw/tmuubvQrsyzv3ImcHfBYvTIZcoWkcajJs6u3Ic7GbHeTUdLbfx+ATD6nzleKU7s3HYBP0F4S6+rCIK14+gCQjE+m8yAu+juQjZdkWm6H6nTrqCtKj6qPbCDW82O5xtQkwDDIVZDK71Gd3/Fq3Dzs0+uRBznlTvUmeP3mSczXEbHZLrv+Frx+prFrtBjzn6bPNfwEFgQKyKkVVpLzQvfOMaiK5rXdOhFi5TULLrvIlszxf+0UJWxtYkioV0H34DFUboJ39uyfl3Dj4/C7OfkTeX8OzIxx++cnKeWdxgh4ZWq5tw6JjFIaHFFViikxTBLJEGwqTorJW09XMLAVAn0W9LQOGros0g0ten67D5qvr994GAPBe/n+jqFO1dQIxV6KJWN6LxWTInm35YJ9NSMlLzBICXUXkF2FLQ/1nL7L5r/k8ayqH/3SsTVYpws2e7qtITv/QCAKyRHv/LRZMyBe2rZ9D1JWAzFaX8axidXX1b/3b/fff/4w/97qTqc9//vN4yUteAgB4/PHHAQBra2tYW1urmFwt7RL+blEkGQTzjXIkU3KTLqUSBcDGvfIh5p+4hSXIZTTG8DHpmN0RNhwyAFTtIaxkjnKuoLs01S1fjIcqtyFJjRI9JVOLBT8cbeMhUExThoASQylGjZbdMGA4iiCuJEo1/yvNK3L5eFiV0HdOjhEeM8aHuAUGd4jsCkqh4UXq1m77HrbUAlPrNjnJuvSxL6ChHnS9e+4AIJMSeqimw6GG0dQzq8wShmfCw1v6Ya/GKH7yUT7HNIoZoioME0fiG9XXOmgcUdcoCPkBqsv6VeIjQw7EsSgKyXGBWuhVc1fpzC54bAH1oFcu8LVOkxtO739uj79zm9RtGzuVpqu0EFObi9lun+0nNu65GeFdLwUAnm9llkKo99e2tuEqXhbxb6YXD9A6fgGA5DE5KomDsCttUeTxZ9fwpADNTwkCB35HQi7tE9tonlJO+WQuK2xWUVp+XSclRa6T0pDaFiU8d+b7A6RRFZ6pr3c58fJ7LTRU4pUZ8KNWFgoAZDOi4dzGupa/LwbyXmke141vdcNhIwHLE4ajcqMJL8Hvli20fcnhI3BvkAk+qyTTOcNWlm1rDqVt3Pf0g9F2SIQtBGtVq4kizViRmM0zthkxzVBp/teSGI6yRAA9TsqC26YUi1hzEntb2pjUUAZrB/I58ki5rBu2HFlcvWfkVxSs2uTjPvM5HmMIm9XM/CyZDNj4tiwKbUSr7n8RhOymjiLXbbc8hxtp0+Zntj/kpCcZz5hTSLEYTuCxavXa52wRz/TPhkGoZWxKmaOXVa/PcxlfyzDfcxXXnUz96Z/+6XNxHMtYxjKWsYxlLONFEHlZIC+u3dhcz/u/3uJZmXYu49nH5MIBnKn2lure0AEABKtNJoRSdWP+6EOobarqRthihdDgkTPoEmHz5Gn196ZuRAygpE2N6ollOV4V8qOqh9rZ20bloMxzlGp3NT+4gplqFUI7snCrB7cjjxtZyrvJItW7WtrF54kmWQrbQuuw3AG2VVuKcLPHKqtiHgGkuFPHZzc7XGXAPOJj6Co1U219jf2pyiRGqMrm4yd3ce7DkkxLu8qNb7hVN+E1DC+p8iWanYpBKRvuqd2829E75Lg/5jYb0V7EPiukOPMaLiI1bq1jm1zJ0+ogp3IMvBtVx59MBsiflNUev9eGUyd1WB21rjxGakjs+g4rjJzQ5/Mlo8N5f4qkL4+1Vm9VoB5uQk3E+TRDT1X6/Jvu4hYo+g2GX1O9xURoivn+gKGP6OIBH1dzZ4PPgcJ2Ha56lHnOrW2oYlgWBUN7rVtvhqN6OJIqrsxzbVhpVGCvhrQBwO2twlEVWS+J+RhJyTZ6/CIrA/1ei9Vyi+EUwy/J/mmzy3P+3OYhWR3Zuf9mrhxpAvsBX9siiZkML0htJ4TRZHfGMFw6HDIUSZVL/9gJuIeOyfc1egzREkyIPKmYdnL/ParSXS1ZN6qdbJqpCLi2X+M2PLan2/PEQ93ihdpAlYsY5UI1KBaKwJsluvk2DG8vx+V7HAQRG43Xiyy5puIsYVlVsUtzFiXYruB7hKJtVJOsIGQonypT5TxidaPd7OjKPFXG0hSIr2rRBNVKS6mGBVWxPIeh/OnFA1b6UnUyGc80nA08jQhG6GtoKHvdhlZdZspXL75SrXo9l/G17DP1XMUymXqBo3vqCLpGmZqdow3Ig9yPrzxyFuGmhGq6txzlB/T4zC5Gj8sH/OFXyZs5uPUluhdVlqIwenDJL8iriwwlKGY3d3IEn0fMFRif2dVGe8rl2+t2GF4pJkPDfVupx0wX7NDj5qiNrSY6J6VsuHWr7DPobBzR/epmE83/YO6H5mwhS+B0pLLPVUmPCEJ+OJZJbBgMbmB0To7jUx+XsJNlC6yelhCqU/crSRT9y/wWw8SUeVL9XV7ssli7F/tdn9VGxPsBpAEgoPsQAnrBFZ5TaWJLY0ZS68VgyiorYVtYu1NyOvxei5NuX/FQGofX4LZkkpoMhohCmShQot7cWecHN6v2AOTzGSdeBKnU17vMj7L8+jXcuzKJK6oxGrvWMTm3vGadF8TR40/h4Aty/jY2LmLl5iN8DoC8HtwL0fiZFX5pxs7y7s4poKGgHJVIiHReUUbpsdQNlJmnZPwdAKsAibM1ePgcLn9eJq/t46ucIHnNOvJUfh/xqHo393DkVXfJc9k5xp9pqebGbuizIeb4yV3UlOEquZsLz9eQZ5ZWbAPGqqclRev4LlZOD3gMGM5ydJ/Lyj1MyRQlUWbFwFT4wTBPNSDq+qp8hvi9JivcFmM5j+OxbupczsYo5x153kajYYbWook25QybRmcBfaxmlwbTvBWQ85HUtGVecLKSA5xk8XPG4BaVqWGKqRKs+d4Bf64bBnyPZXOt4nICOZ627/HzLk9Sw+JCqSyF4PlNhp6Anhujx59CWz3j3I0jsAw7Dn3eMrku0ozP2xICwksrYyCc5XL9Yo7l1VnGMpaxjGUsYxkceVFCLDlT1xXLZOoFjt4rvxmhUqotnrrIVYs0mlfL9ZA7RVKXDR4+y0qYcLOHmWp1cu5DnwQAtB49r1s9rKzpCotZgap4z6hdlWGsRx3fy2LClQqvGXIlgSAXCIFcwYBxf8RkW7PHHe1wG1tN7p0nPIcNJ6ePfQkA4F85qKhXSAlmEkq5hF8LmJTNHk+LOYpY7ZbnEffxK/OC/aHG5+UYXvrkRd5tr5y+if2WzDGi7y1rDVi52jkrCCAdDDDbldBdFs0Zjq11mryDpephmRe6+7zvsd8MVUKSyYyrko7v8XHRe4o0w/iC3AFPLkWsFDv6rXeje5ckIRMRWwQhX4/y8hWu5lDly/Y9bajav6IroPsDnl/0/VThAmSVgdvvmBUgqvo4rvYuU+MWeD775cwPBoj2ZKXl4OE+w2Rb9x5T31XXVRFfw3Q0hu0T2/BvlwricuWwrkgtyLPL8Gsy5rZl2yhFFe4qk5ihzmy+4EoEQXtZFGP+GSnwuPywrg75vTbqitxf3ii/v7mtyeqW4zJULpQZ42x/iPE52T7F7wTc048qU1agjVOdIOT5nc0XTPqmXnOXv/gQBo/KSsbhV15G/cab5Hip9j9WEOr569QqbWrkQRvz23XZHNZsYUSmoPIYQz5vgvnIxFL21tQQLHvcqfeWC+1jZXm+hmPjGUqhjV75tZmuxKRGNRKQc8BW/fCSSFeA6r2QXzN8VFacy7zAyt2qytzq6aqfqlBls5ifUYvhlK8dzb10FldaCdF5277HMB9duyyKjZ5+FsO9eVLw+DF853haRasI+NneOURnzspjGUx1BfTwDXxNfYK5hyPgXf8vPB+RFYD1LBKi7OuPMrVMpl4UYUAOrCAy+CMUaRRzsrUYThiSKXKtHiOlUf/hi/xQ7Jw6gvCGG+Tnk5IobDKfQfKBiO9AnBMXpSrR53HCTsRer8c8InLune/uMW9Ami0qmwS1CHZu6KF1TD4kgvUul80XwwnmCiYYcd+7KS9oRZ4zf4PHp92r9KjjIBVallYgExNiJN6WYMm6X1ECERxAUJWztq3NQoucF2+CKGzfq6hvKAFpbK/xdcwNR28KU41ECVgeJwyZCFs7RFM/wCuPPsWcJ9sR6JyU3KXw9rvgbJ+sDEUxuqzPxXP4uDRvp6qao3kyu9Tnhal7SiWxa9uswirnUcXcVI6FC6sm+V+W518DoxWzCXNR5DjIzz9YZAhUchiuS0Vlfb3NCZ/fabIxKSVjteM3wWrLBaa8yvqDvvMas1PI60rXzORXcX/DgyHfa8FaR/673kG4IZOtpz72FKI9qVzeuGMdfk+OZ9DTCkxeUIOQ7zHT+DZVKl0vdJn/5G5ImNPurrO6DUWOXMj3BRtr6J5SzuxqQZ3tTxk6nu0P4LbO63GGTB54wW64nETRxgiWQFmqZr3CgaVUbUU05ucJQZISapVJZpFmIGZS3eBy0iZr8dRF49pf6y4Oo5H4VwrLFqxQpfvDDX2G8yZPTbn/Ybje5OOhZupXHjnPz6vA8/k5Ndvt8/kRtGf7Hl97uj9q3QaPwfxgwJ0D3NBHob6LrndZFHyv1zoNtnuxe3LOto5tceIkwiaslpTlkzFrMepjvi+Pz++1UDuu6A6HbkBJ0C0lqYvnT823jOuPZTK1jGUsYxnLWMYyOJYw3/XHMpl6oUPYvKPzuh1dPTA9R6jNSBiwwikZzxiSyaMFe/E0tuTO3txVppHRx0/1iULY1X4z48tcmSLFmmw1oUianY5uswG9454fSIhrdukKE7Edv8YmiqGC89yNI6yuKqZDWOpYap0mQ4FztSvuP3yBS/zNnXX+TmpZUoZN7ZllVkLo2OaRPodc7xqF53DpnbvAtzScJoIQ6WW5s52dOQMAqB87BveIIl/XAt12gnxnwhZ6dygjw5o2Ni2zlGE2Oj9S7wGySsXmfGqH3Nhe0/Cm6/D7CI4YnR0xtHfi1Tdg8//xSjneh27Q7Udyqs4lFWUQKfOEqo55zZAh4jIvAAPWoV1+cFRBxJs7/Fn5qM/+PLRbFmGLqw+WH2rPJKN9CFUS5/0pRhN5DCueje7xjvwOBRvRbh+Q87e4ioTs7Z3TXkUE+wIaZvRDlK4c59LxYKljsISjK1WGSovb8Bh+SdwPLfR1lax7BecfljDdYpxg+xtklTXc7PDn0PxHUVSOBwDq6x1ECg72WnX4R1QfvePSZLL0Al29iwa6EhGEDKWTmKNIM/ZsWwwnXF2z1T1jD6/AVfeKs7HDPRZLWz1XgnbF14ojSyuwPP0rckNhpuYMwcaWLfj702gOV/UNfTqiueW61aohVS7pnipyhh/toA6/R9dOQXuTmVYOFiXmY+X1NpzxPewow9Q8yfl6+HHEFTG6B2vdZkUhSj8zVCts1DoL9ZkeJuflc0FWqwbq3Hs8JqUa+8VwiiRSPfnUvZoZc9o0IS4OJIQ8P6vpGo0Tx7mqiLKAtZjyMQJVP8DnOpbJ1PXHMpl6gUO4PkSglTg2ueHGCfKEmgNryIIgAqfus6IkGc90uV0lWEWSo7EtHx5+p6l7j5lS6kw1Z41nnGzRYlkksdFjT0NUZm8w7vWWF9ygs3vLUfg33SVfu3pIvinXyQWMh6ZIYv4MimgvYlVMrdPgBY0euhgc6MXb8bTJpCEt5wd0mrFCJ4tieKr5aeeosmM4vglvS0r5nY0dXgTHT0re2fjMR9G7TT5Ia0dP6gXAgETZKqBiNaH77Jl2BzyGBsRG4+aE/tM2PaYI10McfvkxAMD2d30HnKPS8bpw9dyh5EFCKoZjtlpEPAVpWp7P55CMI+atua2QDQx5HkwGsHvyOtrddYZwKk2iWZnl6MRO/anMUuat5UmO3pqcv81DDYQb8mfqPTm7PGDZfZkXuok19UYTNkM2lufDXpFjX/jKSsMNdF+4IgNy4nUVsBxanFWiY9u8eHrNOtKZbsoNyPuIEqug66NRk597cTCH/TdyTmzeJT8+3OxUkmVWzJKdh++xI32w1uU5Q8eNsoBQDaDzaFJpJk7WHTQWZV5oF+6iQDbTvQwBYPb4RdiuhP66txzAVfYRzrpqtgugdOv8vWA+j8sGtZToR5f6PAbhZu8aflY+2Mds92/Ua6/wXG9sqdNvdoFA3mul42n+FgArUzA0danOUp2oo7qBpHPlpN5QzRV5qTeV9NxoBZqP5odwOvJ4vRs0LEvPu3zU14lshWenv58SWrceIFWdDUaPS95aPIjZksQLXXihp96nEkrbcLQXNjAbytO9+Dh/T/eel6jju03TCvIEZXFt38NlvHhjmUwtYxnLWMYylrEMjmVl6vpjmUy9wJEdnEe5qsrmfsiKMjGLkfSrxnFO3ecqVZFm3ILF77U0AV2Vt+PBnHfZTujDPXJKfsiahBgK24OVKKKpH+kSvNr5LwYTJpVnUczEZNMYkYib9a0VNG+/U/7uxJ0oarICUijYyUoXsJWFkiVs5Oo7AN0VnvpuAZd5p2eSpKnqk/d3tXmm4yLZk9ACmS2WecFqQ0CTafM0Q/sYqdrk34P1rv7cwT5XzAjGuPzZL6H/0JMAgJWiYGPSpH9FfXbEO+Da1jZfu9LzeTdapAf82tJQStputc9WHieVXlwm3AQA63fusDrT7q6hVBWp0vEZ3qNKTJklXEWzfY8VecLwyqLzTiYGXBwnmpStqh+tC7to3ibVgs7atu6tF18Lz5jB1cHJgM9r7fQxhqGj/QnGF1Rvx7nux8c/pxlXjqgFjb22DbEuxyBvriH11JwhL6U81WORLfT8Xkx1ZZMqho0O6hua3E2ViFhVgxeDiH2N4kHMogVPWHyMRARvHd9ifynZxoZgMps/n+ZJc2dDK0RJ0FAW1xD7Oag3nVKRhdDQcDrWClAa43QcYf9JOT8n5/ax8Q1yjOvHhnzeFY8jNQ/s7jr358yVqagpVLBswcdYGB5j3EsxTZ9WnFAoeLG0Pb5OlgEB05wtZhOuFqXj8TU+a8J1kMe62krKXNd3mJjuK+Xh2t2nEJy6XZ3X2rVUgMmQ2/SMvnSWFXr1w7ICa3k+X0MXGv4r17tM0h8n1H5owca8APiZnLM3VabNj+eRrtCrqN92l+7dZwkgVhXhxZypF/Se9Er1vc9lLE07rz+WydQLHGVRVGArCmcygLiKx1EWBVJVzo8uXUGu4LfmzgbDf1SqF57D5Wnv8A2AWoSKUHNNLPVws8M5m+vRg9b23AqfKZmoxXeacg+41VskXLF26mVwj90qP9929MNSfX7puLBybTfAiirDnoElx60aK74WwwlDjZRUCDNRmUfsOk6u1GY0tteMJE0vOGYjY4buxn2WcTP/BZpvNL1wgDYt7upY0miOmVL6lHmB2rpanH3de4+dzNOswp+4WkHkBDUjIY75GLRKM+E+g+7GRThK1Qbb00aMCjIRfojS6FdXgRkACbUakAYlzaajN5kiplHMCWn35mOckFVMO1VYxs9soZDEcFRjXr/XYt5LNh9wH8paW0HEx1c0zy70+XyFusbdu22IzePGeStj1FzB0GnMcJm1iICpsj4YHDDfhBse97b03FssGC4j2FV4M57n0/0IA8VT6noO1u+QY98+vqnOq11pqsz8Q+Vk7oYB6kolaNkCuTLz5CtgGOSa1gpWUWiIR81TJ/QRUuLUrPN4mnyzxUiOx+jsiBf3bXXP+VuJtiNIE+ZCWlcZh9I1qHXlxqi2uclJM/UJLOYRQ4Kz/THDcOGOVGeWq5sQlOgmc4aAYQl+RhBsm106h4ly+E+j+BoLgiLNeJPld300t+Rx2b7L9zg14a4dvxmitaLPS6ni6PtFU28ssuiLbLpJ3+U2OroPpm3Dpt7xec73Y62jNppxwhy2IsnZrJOa1Nueg+aOTG4tP+T7hRK8Mk2RnnlY/pzEmm9nJIC8cTGh9WW86GKZTC1jGctYxjKWsQyOvCiflc/UEuZbxvMfRmnccl1WK4kgZEWLWZmKxqr/2+4Vbmvh99pciibiY63TQHhYMkGdQ8dReNXu8VaRcT+vMol1JUF5+wjXYQ+mLE6MEnvKMMfeZyQcsBj+PlZPy91V85Zb4Gwdk5/RXOFzK1NVPTA9ooyWNqRSrK8GvLszYQNBxHnX5R3/5PGzGD8py+2Nw9K/pXfbcTgra/z52mTSUIqRgalt8/kW8Yx9nswqBR1DMpmxTw3tYB2/xtWmybk9ViTW17vcd45gCjcMtClgFLO/lqmcor8nkwizfbkLJVKt7dlciQw3n4RNqszVI7JKA6D0FCQTtmAp36Fy1EceyV00V+SMXa9jeGVlcQbblT+TMWWt0+Sqx+iJCwh6Sj1mmmqSieqorz2nqIpRFMgXWpVHFYf1O3eugXIa22sIblDqySDE/JHPAgB2H/y8/P7HL2LrolRBBbfeDXddQdZE5BYOQNByniA3SPRcEVCVGBE2tZ9Yqw1HVSDZY0kIuEod5oUuQJBfXrBii8/fgPZKU8yhqi7Cc7hinMcJ4i99QX7vpXN8LDwnawG3Q7E836hwKoVfkXOlz2k04PeqfmSL4YRbGS1GCSa78tpTBdf2PTgN5a1W5Ij3pUoxixdM9mZ12fEjcNalQEM0Oly9zpVqL4+mmvh+ec5zdW0s7wNPDqT8rmxRMQSmIMgwHY/ZoLTMC54nFMl4xvOlsREiWFVVpHrARpfu5hE9bux1ZWtI3NZeW/oZILj6TH5StuHBl0fTq7zqUn4fIO8pYasqG3R/TIKIASDclufVabXZWJd9xbIUi3PStNM0Yu7ccoKJ/lxJfBaNh683yrLkefRM3//1Fstk6gUOy3EY3ivznKEmALDDRuW1ZRJXFj6S+hdJxhwcVvs1GnAOy7J32VpHruC9DIoLYFkMD5WL+BrYxlTZOYYaKY0zhuEoqTr4wmVcfkQ+rDfvOo/tb5Uu1bVb7pXn6FfPA6YbtaF4AmQySJ9vCWEkkioJS1NkU7VA7GoOATU69nZu5AUoH/X5YW0JoWFUdlqeMUxRpBlycmsmvkSrrpVkRpBCsCwKNhcUrsOfFfdH8NTPtumerN5v2QILStLUgzyNYk5Yh2dHDLmRo3LvpjXuwVekGUNFbqPDyQSppYRb02OcpcyJovPyWhnsoK5+Dnnhsuwxzy+Sm9e3Vvi8sji5Bn6kcQIAOwhZik+LVRFNgCtyMVkMp3wsXjPksSF+1vTiAdbUYhWeulk3c1bHl0xmzOny9s5xskIcJHv1kDY6tIROcLJUN7ulxM+v84IrGh0EG9U+aHFfW1HUV+tYV/faYrzga05qWhGEWuU4jzRfTM0z4fkM5ZdZiviihKRHj8vG27bvsZ2I1+vxgmv2q0uHQx53anZud9f5u3z1/fP9IdxQPgvchssJIV3D+cGAX+v1evA6Csp86IAVau0Tql/mHUdYql+mKX8XbVCyKNZzy7bQ2jFoBYBsxEy8MQAgk9UkZuVe9pTkJE7O7fGcau5scK9E2uCk0Ry1lry2buhzH8r6ehf+YTI/1e7iDKPZnoYXySojidjktMwLhgkJ4pWv1bYZNOeLNGOOGjv1ew5zprJ5xqadizGZepZoqyStdSziJuz8NdGYk7joUp/h/3Crp6FjgoC/jNr37zuKonxWvKevR87U83d1lrGMZSxjGctYxjK+BmNZmXqBQ3TWKhBBaZgKXt2br4TeYQKGoqVV18onVcK3u2twNiTpPG1uIC7kLrtQ5VdXCF2ZyhKtajPan7CJnxC6wuLOJewBCcnJv1uY9eXubdaPeBddI6K4F0jjRMgdqkWmhKafDpkx+jUUudw1LoZTxGrnS+VvqygY0iiLgpV3pLSDcS64qp0MQybFtURvUx1ptrIwYTg6RoKlikTvVM1+XtIjjMw65XGbu17hOty2xIRSqUKTfbHP5Gci2rZPbOs+aHmh50mesgljyYT/mobyHLdiUEhBcLLbCCskfaoKkkrL8WvIjR0xQUFcIZ0vGIJ1NnYguvJ6UBWgzFJ+bRrNMe9P+f30+8V4rv6eMqE6zBJZ8YFWesb9CaJLkswbrHfhqPmVGp5B7qFj8vv9UBtG+qGGl9UcKKIJiy1Es8teWcFcfv/0ou4RabsC4YasQq3dtor1u2XlpXFEnmuZxMgHknQNYTOUaJPRrelf5Lh8L5EyLNqfoKV+7p7K4CufJsvXffqoIic8Bz5BVH4dFrWEYghZiwga6yEah2RFjL4zmydcDXU7HR5jCXfpewGQUCt7iC0M7zQFj9qzOd8zrq+hTFYrmipPS8AiuA2aTD15XEJcyTjiiljj+A5Xv0jg4fg1NE/L8Rauw3PZbdVh1UmtKr8ffpMrYgCYzkAV6SKaMInea9W5V6i/rXzxhA1QKyOjj2Y8i1msQRW5bJ4y2TweL9gzjb3TrsxRa0lYtLmzgZaC5+n8kt0LbAoKaKNjb00bFlOYatznOsqyfFZQ3RLmW8bzHnZrRd/kkwFDF6Y82FyM6CYO15v88PF7bb1QkjN1u8fQXu74yFXnSZvcFI1eczAaxFIytRhoPkRhLMK1VsCQH0Uep2isy4dy59Rh+CekoWTZkJyp0gsBSz6oRRbrEnoSM5fJbAJMpp2DvYh5PgT1CNvmRCVY6zI8wotCLdCKmCRGOdMLhMnzoaCFI43iitoOkMkUJ6m+pxcTddsIz+FkKY/1IpUDsNRnUVPbzDhHSwjuN0eJQh4nXO4HjEQ51L3RrJwWd2OREjbDe6VS85VlweOBotDO0Wo+ec1Qj1HNNxq9lsz1IH6WZQtt+tkK4XTUNVWLQZFcqR7LVaadV0djW16v7qkjzD8hC4/uqTY6d0hVqGh2WRJOiWeRZDwX5/sDBKjGYv8y85XcnVM8Bk5vE4X6mfh2lm1rA1vHg3WV+jKZzDA+LxfcNErRUHBr+/g6X/NELax2nMAh+4kgBCjZoSTWgLWKxEjgqcH05Tkse6DGZw21nBK/lOFtM4mlRMRyXA2T10iFqOdGnuZ8L2kTSl+7/je7WimWZAxr0t+rTcV9OIel2z/9riwKhFsyURidG+LyZyVk1z75EADA76xpRW88BS2v5SJmmJo4am4Y6O9V3w1IBSmgOEZqLMaPPMZKz/rmDCsqQaHrWbg17fJeFrBSBfUrpWc26vPnN08c1UkYHd9szM9kcwNS5AXfF5QspdOEeVJplDK8N13I37WbNazfKXlnrTvvZh5Uev5RABJ2Jfi+c+MRBFvaJofmj6VMR127avHwXEZZPEvO1BLmW8YylrGMZSxjGctYxvXEsjL1Akd28BTSVO5w4909jJT55OjJfe407zZU24vQZVho9fRJ+GoXkw4GDAOwiixsIVdl9aIs4aldpwtV7ZpNYeUKMjR63JmtYqgKlkYLbRDaDVFXLV6oolCkGcNt3dO3wNmUJnSa+GlWwXJNJgfY7+hqDyhAmiVe/oIkLxM522sFlYqd2dIGALxexDBLmaaVapTFqhitWKTxypMMIIhTVQ7SvGBIz2uGPPZUVRKuw1UiN/QZgk0mEQpFeOZO9EZlyzxe8tGa90eY7Uuox/EdbrVCu/UiL5ATpBjFqCkCbpmlhs+UqlAVLp9rkcRc8aJKo3OVoouh3XlWhUVV0GtFu8dQQ0Gw1uUrSKdyHtijPhxVASpUBSjvX0KkVFpeK+Rqqh02GOJhf6ItTb62PJ8rDaSeFLaNgtSmts3HTccsx1CeazuewTt2s3ytH7JCDspvqlzMNUm/KLgiTNBbGiUM38wHMZO6F4MJk4RpbvmdJoSn2vP0r3CFksL2PTbbzdOUoWFT5EGmoG4YVFs/kfkq+8v1WfUWrHVQP3ZMvla9R1Z21dyam9UmeQ2DjTUWCYggRKauYzKJmDxN7aOKyVC336np61EaxqetYxKT7D98AQcPSWVgc0dWprZ3TvF8Mdu2FNEY6VhW1+qbK9ccl6k2tYwqLPUEzeYJ+l+UYxAPInRuVM+b7BS/1uxXyRUpVQ1DkbM4RxjeT1QJLXP9jDIJ6JlRvSbxTRKllfY29HuKw994CIf+z/8DAOAcvx3lFfl8n52TnlqWEOjepQxGjX6Tll/X1WWK/hU8X7EkoF9/LJOpFzjK+QS5amiZTCK9kE+1GZytGvN6W22s3HIMAKTjMrkjOx68bcmPooeX5biwlHrGM4wdrYVqeptMYanefKUQ3JTVTGaINzMfxMylcQIXHiUztAhu9tBRajrLD5k/QqwFy28ClgJ+hC2NNwGUfiiNCQHYlOB4Dqt2Wod12X+6r7gjj2lLiMZ6HV1DTQdUJd7CdaoGnSoKQ6pPZXzH97RykKCecYSM7BLmyTVSfs91+Gen7jP8uBhOEO1P+H30HoaHxjNOomiM4/6IIYLuDR0eT1q4pXlmpF47YehuMwhRu12eb07Ja6kTIjOBmylHfeHt8XFbQrAqMk9zTuKYu9HrsQLJfNiX6ho6oc9JNx5/GB6Zv1KDWuVQD0gIixSqSf8Kfy/DiL0VbWDr+QyJcAPc5oTNN8skZgsLWvyTyQyTc8rZ+vGnsHa3TKyat9zC85vk/eU80hwUx+M5S4mOJSwEihPYOtzEyk1ys9A6vsX8N4bOGiHzr/I4YTf+/c/JxTtPcrSOyGRn9bYdVgHSv0E3RtBTCavnaOhtESMZybEl2435/oCTMNv3UKOG2oaSlPh2rrH5oh6X9to2j3ExGWK2JxMg4TpoKRNSuh7FqK+h7bBZ6fcIyGTM7UlLksZWG32l6KVrkO0+CbtQiU401slKEjPH0T/a42tA503WC/QdAGDVWwzHhVs91FryvsjTApmC8j2CJIMWw4tWlnKiTOFs7gB1+f1WkSHvK8NfNkgteIyzKOZm4/IeVb0+iVuY5MyxhK05qYH6XbDa1CasZYFcnSPdv/P9gb427Z5udAwDSqdxmY7wfEVZVB4jz+j9z0csFgu87GUvw2c+8xl8+tOfxl133fX8fPHTxBLmW8YylrGMZSxjGV918TM/8zM4dOjQC30YAJaVqRc+bI8huunFA1Y72Z6NrqoSEITm91qsakORc/d5u7uuFV0zuXspJkOuDJWq8gVoEmYZRyjI0NKA3UxfJCbQ5gXDfPPLM35tqNrVdG85CnfjCP+eyvEMUfQA1FTJWji8UxNFrpVOalcY9NqwT0u1VBrFrNyjsv6sr/1m2ke7rMShSCOtqnP8mjbNbNi6VU4h359FMe/oy8KE9Mh3SfC1KdKMO8YTvJS7LsNORZppEn0YoFSVqeGTBLGlCNY76nvnmO5KmIMI35ZtYfUmeS4b33ArE5rnu3t8rGwgGiW4/Oey6/x8f4jjapxrt98nz8X2Ku1TiOQuLg3l+8czbqFR5gXmqmJVa9Wwfqe8ju1Tsm2L6KzralHN1z5oqtLHBqmQO/e4/4h8rVERM+cUKT3HT+7y7p+uobN+WMPNrqdbnfhKfGASuadDlJOLfD50LslUHt/4Qp/H9lCcoK6UZuQR5oYBXDUfilGflZTcpzAtsHJSzu+Ne29mLyOqcAFGm495xCaPbiPkNk62mrOPP3QAPCYhmjvyAkdedRoAGCIDAKHgrGSsRRdlXnDVjfyW8jhh6Dfc7HG10FLEe9uvwVfiBSEs3R6H2ug0O1xhygf7XInzWiFfhwo0rkxYTUViJYxnB7UgKhRcmA4GDNsW8YyFJ3a797R+ZNxaZqqfV7RA2X7Iz6k0mnO1vrHd4+oYQ4LG3LOKjGFJRxHVi3pXe7LNRzwe9G82nTKFYTGY8jNo1o8wu0y+VymfKx0LwaQAYDtabMJzdnKFyfs8fAbUa/l1nkfUkggAj6Fd/C3X4DmIrwY13x/90R/hgQcewAc+8AH80R/90XP+fV8plsnUCxyW42rVXJLBDRU/qql5A8TjSMYRP/w6zU61f5OC9NhYL0sBdRMLYWtVDZlyzqNKDzF6kNBnBr02y4Drq7ofH6Dl/uw8vH1CQ0BFrg3xyChxMoAgtRQMN2fHM3gBEtLx/RCeeqhGF3ZZNmw6Cq/eJHkWnVNH+GFkGniywq8VGrYAuZbKq3/dLGWjzjxOdLmeEjAY45sXfN602BR5zlCT6dAMSN4ToPvdTXanPIbZPMN0T0Fu6js3X3IYW/e/VH7+xo42pFQ8iXQ2x/wyGQ2WvGANnhii9WnpqL1KUG27pxVX84iPt77e4nOhOTXdHTHPY+veY1i99zb5vT15ba2rlINWTXNoAMCKXa0kcx1O0igpEa4hmXddzbMrCoY3aINQpol2ri5yTthojpSuXuRNA1uCTBhuVDG+oBLGP3+ELQKIs0WqKUBee5pHpvKRlJiL4QReeyiPtd2DUFJ8gqOyvV0+L0AvkARFra8ESKcaInMCOV6OOn+vFXIzaru7xolLPtg3kjsN7VGjbqfVYgjU7M23clImF+H2Gto3SCUZbbzguCjV/YnCmNOuw9eBkg4RhBB1reyjMJuOT5+ULu6z/TFvcprbXT4+voY+AJUUW4G2raBnUDHcZx5VNl8wL9HsEEFQbHTpCsLNDgBg42V3wDspk1OEqtG4bcwTtwZL9bGs2CUYTvnciFhtLhdDbcGxGEy4L2k8iBmKN7lRbImSFJxEkdmuZdu8ucyFYJiZItxeg7elXOZDfT0RhNxrk85HPI/J1N8XZ2o8rvYTrNVqqNVqT/eW64q9vT28/vWvxwc/+EHU69caK78QsUymXuCwXBf+upbm0sM87o+Yd0Py5vbxVbRPSm6Us7GjGwYnMVci2NXZdF12fOYsUXNjUeTIaMc0m1zzfsDwSNpZ193hk5STldqWIhN31yqNXqnyxJ8JA/+fTSoNOy3Ti0adCz1U4/6YK2H08GpuNbjBbK3TZDJu3NdOzHR8Tt3XD+0sYW8Zc2EgAvnTuQsXaaa71tuCKwKuqlwVaaarVGnGsml6PaD5bkVeVBLCtdtkFWDrPkk+9Y+fqvjI0LiYVYpoXyUN4wUTlltHmsyLYc5JliJTruPz/QFX38gdX46TPL7WsS3mRzlr28xLYZn5bIL8QFaA8v4lzWMymidTxaBINYGdifedJgKVNLhN7Sjv99p8XDSGyYUn4KqF2lnbvkYwUPneItfu9cpiYTFecMLqd32eM+MLExZxcPWltyUl8JA8JZahC33dtCVJjOFjMmnoCBuuIrZT1UZ4Dp+DJQRfj/ZxOVa1Vo2ry7177tCJjQrP8bj6hixlovRi/zL6D0m7gdFZ1apoNeDkFEXBCzXdBwDQvVk+I8KTN+o5Rd5qu2f4Pek0qmwAuGWToys8zJNazHWl0OAf0oZrPoiZ7E6cK2QpiuE+ronZ5Jr7HjDEMwbXkZ5hELasbkEmOFRttXubQFP5WhlJFEUpHOZlWqqllbWIjGqUYYei5lncH2N6QXLJFuPEELxY3G6pSJRvX14yfyqZpsw53HqJhJ5qnQbme/La+MZ30fNh3h8j+tJjAIBmswNn6wZ1Lq72HySbh7+tOvgijiNHjlT+/+d+7ufw9re//Vl9ZlmWeN3rXoc3vOENuPfee3HmzJln9Xl/X7FMppaxjGUsYxnLWAbH35fP1Pnz59Fq6Y32l6tKvf3tb8c73vGOL/u5H//4x/FXf/VXGI/HeMtb3vKMj++5iGUy9QKHVatznzTLHrH0Nk8y7qtlKVm2ZduYnpVVggbAzW7tZkfDLlSNyjUfqXRc3QyXVH2WgG30AaSqBu2K4+GkIv0mGCMZz9hkTqgqhWh09K6wLGBRP1Fj98k73CTmHSBxCcwoklj3vssLCFXZobJ563CT5dROq4WAeqn1RurrC11l8HyGiIpogmQwlOdoVJAo3DCA2yDjTwU7LWJWO8X9Mav1qKhs+17F1JMqJHmccIWEduvINaciXK8z34yrK2MNU1o1/xpH+jSKtZJonqF9VFZ7ercdRXhonc+XguaU3yu4z5nT1VUZ7l1m7paDUHOCqBokbK4kxufOQOxekOO1pswFhTAUkTW0TyqHZ0MRSeactWZXu2Mv5lpZp6qW6TRCui+VVZbjwnaUGSNVYE3JepZqPlGkK34ENZV5gcxX12u1jpVTslLgHZJVG7vZQU4KUmfI76fKVXNngxWyycWzuPzZLwEApmcvok0mkeSg7vnMKSyTjCtxrWOyAuU162gcprHfZJiQ+2EWubwvIGEvqhzFw4l20lYVWtsVGo4uclb7UUXbsrUhbBlHyOlzFeybjCYV13+6V2rdpuYx0bPE8Sr8Iw5jbtD890KXe4XSs2LwyJkK9MpO4722rvgSHy4IYas5aaNqlkljpTsMpLiyK59TnRNfQOuQ5PdZgV60S1svbVauqlCKT2r2P0WR89iQxUcyibjaVOaFVm162oqWKs55kiMexvy77g0dAJJHCsjKLFe2hM1V+2BNmyMTNB5OhsCaejYJxzDjVc9u99nDY3/neJbJFNR7W61WJZn6cvHGN74R3//93/9lX3Ps2DG8853vxEc/+tFrErN7770XP/ADP4Df/M3ffGbH/CxjmUy9wGF5NX54OX6t0i2dYCO6GRfDCeb7QwBycV+9Sy3YNR8Oy7zVBEvmzDEQYcx8Ano4WkVWgU+YfKkWJmELTpps3+OFq7G9htrxm+RXqXY1pVtjGMHKs8rDlqNQC55JOhfimsbKJvfDCX34HQkZkOeWlCIrb6ogRG1VNUclb5w0q7RHobBqPsNz7KWVZEwgT8YRWw/Q3wG9UMf9EYsDqCFsY3tNN7t1HSb7FqnmvtG/ZV6wzYHfa/N3kC+S8Bx4xOmKI+2Erxa+WqeBjTsVdNZtorEteTH1jdVr2kykl/eYUF3khXaPJxjHDwGVIJVJrCHaUEvKpY+7hKHp84XrsOzfVaTccHuNEyR34whfz/lZ6SF15ZGzfFxbQQ0BJXTddYYU2fdrMmT/qnzU1zAaNf4tcs3zm0cMMdHC29pZZYgtunjAG5P1e25C88575Ge1Vvi86Viz2Zy9rJo3S68iZ22b+YeL4YTnpe17RrKhxrPmV2wviIdHcJcb+tj/hCTm5w9+nonn7LnV7mkXbiEY2vI7TZ7/nppHli104mbcv0JQA/SFbhfTrPPYkJCiLAqGq516oMUg9abefBHfDhFznqwkrkDmdD04cdzpYXJxwGMgx6rGjuzCSMqE58AmCxeVvFuer5PmxVxzqcjuwNbJlO27yFP5+9n+AKHirjlbytLBb6J0Az7Gkvz06PyySHdhyBKGD2lj49YD+F1132OuG8rnJYSQCRWR7S3bgpvSva79wvhcXQcF1Pc7LnPQXHXtOqcAt6s4Zmvb1Wcm3Yt03OL5W66LsoT1LEjkxTN47+rqKlZXV7/i6375l38Z73znO/n/n3rqKbz61a/G+9//frzsZS+77u/9+4plMrWMZSxjGctYxjK+KmJnZ6fy/w1lKnzixAkcPnz4hTgkAMtk6kURtDtzW3Xe1QJArkiYRP62bIHCVWZy8QLT87LU3QxCNsIUHbnzt7wAgNwpphceZ7iLdkaFsctHphUtFF4zZHl+Ych0/a0NdjgvPLX7swQs2n1ZQu+uCJIpimppnVyVbZv7dXFPwOGEd7Z5mmmVlZIiW7bQMJ3jsckd1aKy6ZShB8u2NbwobK6g2F19fFydGI8M1aQ+X6og+b02k2IjZTGw/5lz3EOvsb2qIQ9o53ITBmQnb9fh6gH36NvY0hWYLOGKAUF0wnMqcBZDmUHIcCtVFIo0w4wrmCOGF+tbsiqz/hJUnKnZykIIJphXQl0vp9HgKhdVfdLxjOdekSUasjMa7prkbkGKw+4G77Qtaorc7iGjCsvBRWRPPaleq2FMIo0vLl/h8SBV4MrNR3m8F8MpH6MbBjzvuXm4sHkMao7LFRx2+U5iJt7H/TGTvuvHjmmFm6GAZeNF19UmomMySdWKxr1PncH+5z4DADj0Ujnuh775bl2hcT2GYGsrba781Foj9a/HVTDL8+GqQ6l15YKS72dcsfN7bR4PLWwZM/xYO3Kcr3dZ5FrCT2rceaR7ZzpexVCVgu4Jx68xOZvuGSF0M2vLFgzt5XGCPK4S04XrwGnJc4XjcQ9FblrueJX+gnTf0WcCQKHsVyrWB4spoKokNDelYEdBf3F0jV2BE/pwZ/LzF+NFpWcnqXRrDRKmWGgo0rklLITqHjOr1Gyyqs4D0M98p6Gfi8VMN9+2fABXNbq3TLL8cxxl+Sw5U8tGx8t43iPL+OFkNzuoGe7idBPSv4vBFPO5fKjmkxkGj8qWBNGlK1i5RT6cglvvBiCbuzJfaNRnGTe7Czse8xXgeNpl2tewFD3IFoOJdhKv64ajFiliHFeXoF0AuXqtkh8j08kJhF1tF0HtQVxD+cfciIXBXZA3p+0J7UDtuKwwooXRDbQdwjXql6dTwxjtbEz3d0CNu3rWuaHPPCeCEZ/668ex9znVjiNK0DlJKsMG+xrVtnf4+Ohhnh9cRJFqjhcA1Ipc20SIJj90KbxEKwfn/THDsV4rZIdyc/zYfsIWzFkihZLXPIfOTYrzESec+NTDFlsiwFcLZ55AqM+yu2tokNfPVC9ApL40YVPaAHjNuvZJO3krrBX5+ZyIA0CmlKaOy21RrMEBZspjC4q3Vus0DTuECLa6XpQkumsbPDcd32Nbisuf/RK2lBeRs7Gjv4vmobB5LvMYLub8WY3tNXjUSqi3yfCjmajTveRCJxPEF1rsT/nnMi9giadpA008wnnEnmtFlnKy0Dyskqpuk+e/6dRNc9cNfeP+SdiDKejJe3D46HlO8vxeuwIvkg0GnUuRJVhclhYB8XDCSRzB/5bn8/w1eYiUWIbbq2wDUSQZbxQXgwknKHT8bujDN86F5jdvRlr6vLxWyPdg57abYO/IxupZU9ldCJv99KzFBOVAOdGrZ5/0vFIbvTRBPtd8M/n5dU4+hW1xAiVsC8GqHJuu6lBQ6zQZqido3RwPyxbMARXuFJZLG5eqxQggNzakgLZqRosvmqdzvZl6ruOrqdHxsWPHXhTJ29IBfRnLWMYylrGMZSzjWcSyMvUCR3LmYQRt3YOODBDdsNANaNXfzJL2Yrzgndro3BDRrtxB7qiqTHC7q6G9ZlfDWQPtR6PhF/ta9UxRaOffXd1g0w3ParisVqcXa5Kk7QCeqm4VaqdrGeTTIkdJrzUMIW11fMLod2cXNb0r9ORn5EnBaiF/OrzGr0Y0tLIRRa7hxSy5xukYBixlGjfSuKZRzA2LAb3jJtNEISxMLsljcXwHnZPydc2dDW6yS5WecjFHvpA75CJL9c6cPaAua0Kz52tolSotrRZCUkC5DpsKDh4+i446XlLY2b7H1QvaYcvzkecSXTzgypnbrOs+fZ6v4d6naa5l1QKuHNlqDNPxjHfhwnW0OEDt8hvba2jeIisH9uFTKOpUCbG5NyQKw3CWoDPXZQ8w2vnH/XHFd4tMJglSFX69AkkTGTiNYiQHSoyhIDrR7mm/pKJAoQjNpGoti4LP1a/52pk6GnNfQnMewahsmQIGQFYpxhdkJXJ8YWIoMaWnkGh2uG9dOhwaJpAp/xwP5Rhd+VKfe991Tmwx4Z7Ca9Y1BBvN4SmhAVV4ap0G9j4j4cvp7p/h0MtltaZzx626ybSqvFlFAdtXVAHDNZ/mbK3b5KpLY3sNq6flDUAmlJYfcpWtzNIKlYAgxeiC/P7FcMrE+sb2GmqrK+q7CIYf6ypup8H3onfqbuRUkaJ+fOkcQlXwrekVZNS/0FCPFtR0OckqLuTyYwTD2fX1FiwhjzVYbWLr5XcCABylIMwH+9w3scwL7q1K/fxkRY56dk5hq+oVueQ7K2s8RnKOKjK94ZFHsZhW4cjnMooCsJ6Vaeff48F8lcQymXqBY/Dw45hncuaFmyvMrRCeoxMco4ROv0unCVIDAouVISSZ99WODitwGjsRG5J4XgziiA0tCQIo0ow5KYvhRCvg0gyFal3BKizPBygRsG3mA5CiphSONoE0eEplmvCDxHoauM02XMddX8mWo4TdzuubPeZZWEpuLoJQ816yVKt24PF36L/rRMxaXDvGZa6NISV0ppMsQLYcqTXluLaOtNBWKi136xgvTMT9KGYTPm/huCwTZ/jU03YIzBNRx0DjSvCL10p4YYsu9bnNTfuEUnGFAZtjOpOITV9JgSQ8pwJDEMxnj2f83eSCXTmuNNGmlqTw8+sggbJl28ijCX8uANQ2N+HdIF3V88YqCl/BeEUGKMm6UJypIp5VDF3Z4DPXZorEByrSFG5dqbcoCc5S5r9kccK2FLbn8Dl6ig8k2j1tgZEl2vCUmvEWBasfiyzldi7F7h6CLfkaUkEW84hhzzSaV+wsKCixCzdCrN8pocbg6FEe4/yyhDQn5/YwV8ljbpig0r9B10djWy7E7RPbzGtkU06jFYolhOHQrxfi5pbiV6UFxk/Kxdt2Hc3PM86bP8sW8NT8o8Qsmy/482udpnbypm4IWYoi1hsYyzAFpXQzWNdjRNd2/OQuW2w4yuC0jCNkY5m0eK0QtRO3ymNcOcJJlIjl3LEWE1hj1Wz50jlke9JwNTU2FhQEgQOoNEina+jWAzTulPdq69abteEqJf2OyzC27Tq8eckNGNM0PCbOHiWOYV7weKbRnDeuli34GUEQcxpde/zPVXw1tJN5scUS5lvGMpaxjGUsYxnLeBaxrEy9wNE4vI7ZZ2XT2mj3Cnq3HwMg23xQewXtMzVFNqfWGdoYst4LmKBKvkcocl2VKXKuKHB7BiOKaIL5gdwR0U4T0Dt+2/d491U7tK19WZTayTKUUYCurHCDzrVtwDUgFVV9KKLxNeaUV7ckccirR7UDsT2bvWsAaHUMVZuKHKX6rDLV0ILleqyOMZVCVElJxtq3yCQLMwE29HkXS1UK2xXYvEuOy6H7bkZwXMI2VhDyeXE1TOiKne24EHRtDFPFwngPVf1oXMqi0FUso2VJMokw21cKt4GsIgTrHYYpap2mfp86f7/X0mqjJOMq1/jJS6g9cgYAsPmNss2Ne/ikrjoGIVdzWPkVjRkOLhLd7JlhjK1jKBqSBF0EbeS2/F47iyEISiRTxatUpVSJq1H3FKN9j/QFq+7UO4aXUZnnFbiNzVF57k24siSCEIWqbFrksRTPGAqSY6dI5f0RjxdDpa06319FkmGu/m76xBFxuXdLF727JexpqjBZ9SYEw3TxIOb3UXPk8NTNurmx4/KcIUWmnSVwDNiKKlJ0zF4rZIgsi2Ke38F6F7Z6NlAFaHrxABG1axpEcAJVsVKf74Q+f+7g0fNoqorxyt2yEuls7LARpzTd1FVWbpStjrMutLBk3h9xxSw04PBY3ZfdO2+HOCq/o3A8IFX3jSKdi3iCXPm0FbOJNpUlFaQh7snihW4Jpf4VnsME9+bJY1z1thxXV9B7qorX6OgK/26fx9v0y2Pagl9jvy16hoyimO9lyxYo1LHGBwN+Dq6oZ7q3rvtJPtdRFk+L9F/X+7/eYplMvcBR2zoMTyUwB595gh9eQa8Nryd5A7ZPZeKMG23maY7WYfnwW719h0vC3DcunsGa6V50xP9go8QkRrYv3ayTwZC5LvSgld9LJpMt5qVYQlzTgDYbj5DNlFImzTgZofeHxyZwto7x51ICkfSvMNzEfdrSDE7g8ft5ce4p+bEtECjOUoWbQmqoydBIZIR29BZCN15W3Imkrx9+yXjGx02LtON7cJVpouN7XMKnY1694zA6ZLzoe5g++kX12hr8HXm+pB4Toc/918okZlNOPlbX1VwvYbMMmtVSUYyMXmtrybnXDPl4I9U8eTFeoHm4A0BeT+6VpsLxPXiKp5cvtMnj6MIY9r6ybPBlv7DGwYAXObdZ1w7magGZXerjstoMLMYLdhpvnJCcErvdQ66MZAunhlzxMOyyAJTaU8OIhqLO8SB8DR0DgHCrjvmk9JxevMzjYnKIqIOA32ujcUTCM2yzYNs6cTNk/ww7u56h+Ephc382wRYaqbpvw82VilFsqsaTemvans3Q3Mrtx9lahBbmIks5GfNadYa2J7tTxE/IRNVryo1LfecIoOxAIGyG7aE2M2USw1LHNdsfsCqOeH71zR4f//xgwAmGu7rBYwMhv0tc6iNWCfro7JhpBfVV+Vzp3bTOUKvXrPN9S7w0si0BgHxwwAlfCf3ssAgSdDx4ii+UxQu+pnT8tW6DE5AnfucP4f3hnwIAVk+fRO2QvAcLGosi1wkONFRo9g8lqkLlehqwbEo9C/cPUNtU86+7rvtQGqa3JrRM9yvBeMIWEIr759a1uSu9LhnP+Lnihj5ctYGO+yPM1CYl2O/IYz1S5cc9l1EU5bPkTH39wXzLZGoZy1jGMpaxjGVwfDVZI7xYYplMvQiCfFv8bsgl/sVwwtUD2p3N+yPejTe3GujdIgmf3ZuPajKs2jEtnroIV+2+ZOuODgBUerLR7rC2rv2XSN2WjCaVUjV3lzchPdrNOx6SPbmrjHb7vGNnqGl4RZsSOi7v5BbDCe8GqTIFaOKxIwRsVSJn2CjwKl5YusM9GXEWfI4iCCvnS4aPSV/1PuuPuN+eCS+abV+YKO45fG2oetfc2YC7Kf1myjjiNjPjJy+hc0qOfe8b5fE5h45zJQJFwaactoI/y9RQGxoEdMuArohEnV+lPtIwHhkkWrBVNclUdxGMmUYxckW4XwwnbEJaX61j/W4JVZJZ5OTcHlfsWse20FLqRG4hc+mS4QFmc6WD1Z1FoaHWIoelaJpWWcAqNdFfjouG+CzPr/hAAYATaB8fOTaWGg8iqI94jOL+hPs6hps97mPJpPM0RU7KVqNqyZ/t60qTZcCPtuFFRjBeFicV9eTorLz2k1053p2jba4M0bgBujpSDPYZXrdswfOrFSeYPjXh8wGA+OJTqCtfMdsg0Qsa70WM7Nx59Z4xf2/juHKNdjwUSlFmGaaaZZZqRSJVX/KCVZmWbSGN5Dwaz7XwJVyX92qw2oTXVPc4+aU5NZSksHNcJvkX0RilqpATodtu9/he9tMMk3OSkD9V5rN5mnHVsdYN0f+iVGee+8gZFGr+1VryXmpshKivy9d6rZDfR1QFd/0Qzy134wjcjSN6DADMn3wClz72BT7HI9+qKuVr21xd4x6SRnXc9hxNpyCDUeP7vWadTXpN4nth0Bo8Nb+8Zp3vS6rS1RrVCvMyXlyxTKZe4CjGVww4ra3VdHmBxRXlyK0UNbVuEz3DHoFu5HQyA7GITCdxUr01DsfwjypOkSEH13wjQ4KrfnaLnJOLwuCflHGEgnhAZCrnuNpmwYBaiFMiXIcN88qi4D5h2TzhhZ77brkOJzNOUGPTPzOBMnvoURJpQgpmMLQXjRlaIzm3OYa271UgTkBKsCmxK5KMj4tdnzsrDA+VRtIz3Y/gtRR/hBIjYVcSP+JOcK85Q9lo8qfMJJOVnOMZcyvMIMWYF3qor3cAyDnFSjZ1LvWNVV7w5vsDtp9obK+hffKo+jB5fE5/hMk5uXBFl66geVJBx9xQWzejrm+tIFSKMJoP5TyCCNU5JhFspeYrbRelo+YPSfFdjxc0y9GwJ5lJuq0Wal15T0iui1qQVI4qlYlq4zGIUV9V6izP0eaulCT5QEGL+2SoYVd1DUSzy3PK8nxOrvzZXFsEqGvgGfYSyThiiGPrHpl4bn7DrQz7irDFXEbmHpqQlF9jKIigdQDMlZyc20NtXXLQ7GYHcNT5kMXHYN9wQG+hfYNqr0F99aIxQ5LdUztapRuN2TAyj+T7c0MR6QQOzxMK2xXMoxKuqzsP0AbGNZKpwIBBjecV8SpFs6M3GEH9GtVbmecGl9JF67BKEtdDhh9J0TzZnbJha/voAqFqjO6uKtVdd726CSO+m4L/LVvoe2Wzh9pxaXPirB9Brp59488/BADoP/SkTvI6TT5u04qCnoPEgQUAYXBEi1w/A821gJKpK1+UlirB03i9PlexrExdfyyTqWUsYxnLWMYylsHxQjQ6/mqPZTL1Asfs0gGaxyRpN9zsVXY5jmrgSD4jTl2rZ1JDdZdGc6MfmNztJpMZV4AufeIJTHb/BIAm5W7es421u07J3/VW9U4t08oWMqOL+6OKEowgIK/bke8RgndUzZ0N2IHc1ZHfTJnEWDwlIbDZ/kBDd+tdXV1T1ZMizbjyI1wHdlglXRbxTJJwIcndROpm9Y76F1C7Xe4Un1YqAPT5Tl0pbTyXj2GuoIXxmV2GGxy/xlWq9iFJ1OVeeurzqco2eGKITEEhm/dJKMnNEiavlvOIqyLcTy+e6Z+TWKv4rvIZAoB0NucKjBv6TPyttaiK51bgy2BN7syFATElu1J8MDsYVsbbrMwA8hr1P38GAPDo/+ch9L8g4Y1j/+ddAGQFqq1I+I3tNd79U3WiiCM4czlnhXBY5lPaHkpFTLdqum8kQ37QBG1u+dPuIViTVZNsnmgVFqtOazyf8jTH+IKc/40nd+GtKeK5mi8iCGEbrTwIHicyshsnmkjd2+IKaJnECBTsSYowv9dmmC7uT+CF8l5au+tGOYa3nGZFJLJUmpPCuPZJ1U+qMKq0dUUBoCpYOptjdlEZO27u8DnkA9XWqH+FK1vh4a1rKrYFAI+gzlx7vhVphmwo4SS67xfDCfKE4E0bdaUs9FVfvPbx9QrhXysSNW3AyhUkmBrqNtfRBHRDdMGE/yzheeB3lapuZ4PnaTKZMeRoCQu+EomE6/J6pVHMEGu0P8PsYCg/46r7H5BVTw0zX3uvlXmhjz03+qaqa7/3uQMUiawcbX/jYYYSWTiz3uW5B2Gznx8T1dOMifUptFDADX34HTnewzPyek8/d+Ga41/GiyeWydQLHP5qh5uNBu2e7tnkuNxwNBkMAQDzg6EBcdkVPg0lUdQfKh5EyFPlpJzmbNyYq7K9ZSRAlufr71WfZyrp8jjBYqwTjWkoF0HiMYVbPVYR2kGdF23iVpXRuFL2poa/drvH51AjRZfhTlzmRcXRmo6bIh/1AVIIGckJ8YFEf1fzbrK0YjMASJM+z3CfN3kMAC3Y8ndeK+MHJZ2f5XqVhqkFWSdMU4zOKsdrJfH2bhgyxFSYjVYJrityzVVJMob3MkNeTwlUNk8Y9nF8j7kqpKwSnsMLqhP6rOQkCC0f9dncdbZ7BYlamOrrXV7kiNtTc1z0bpfcnoMvXMalv5GLdq39MACgd9tR/i47bOgkSs1dqyhQcBPfgN3wS6cGSy1OxJ0qslTzxYoctKQx3Of5cNQ5lkVhQMQlj4WtFvdgf4zhGXkNokt9dIbS+oObFBvcOsvz9fmq+bYYTCB2z/D3sx2BH14DB4uwBUsdi2VbRk9AqXL0WiG8Qwo+Nfpg0v3hCMHQWmYoyoqi4DnFv0syNnYMlTWJOd5us64hxWanMj8BBZ+SqrTQ/TeteaStUAwpvxuq5NrgBgUKQg43VzRMaNhiVPiLuZ7n3NB9zWg6Ts+INOWNUHTxgO+LljLCbRzfYRsT++JlhhyTKEWs3OXZKLblcSPkIi/1fdmXyaJo9XSS6XjAQsG2xGHLc1bgmWObj/rI1JgTlOqFLkp1LF4rZJibID27t1V5DuaGKa0cY68CEdPnms/fzjE534puiOcrljDf9ccymVrGMpaxjGUsYxkcZfksk6klzLeM5zuC+74DXl015MgWleoBFCGS4Kcs1tBGkResJkpnMROa9e4sQBrJv4/Pj5lIeuSbTwAANl/5Uq1YMtRK9P2mQWIWJ0aVq+BKBlWr0lnMfku19VCTjxUptsxSbvvirh/S7WZmY27fQTCJ2bYlHk64BE4qscb2GgRt0LJEexSRIWAQwlY74/neAeL+eR4XIpBTlczrdjQUGUcQttzhssme0dLH77WZ+MvHn+e848/GI8z2VSUky9FQ483VsEUMqPcJz7+mP2EphK7ELBZ8zWmnmqcZ9/2Kh3OuNPpdXSkwvY7oHO1mRxtKqp3/5Nwe+5mlcQYv9HiMCIKyCI7IUlZlrt6sYcLFSM6tuD/iSoblekwmL6limCYoicgNwFJkWytPAOp3F6sWMfOIhQp5nHCrFFbACZvhMuE6rGwlKCqLEyYOB70G/95r1nVPP+P+4iqn0ZvSUccqHJcFIPEn/5q9umhcAehWRp5fMb+kylQyIehvBGdFzmPR8JgMT2EZ6s0iz7kK5Pge+x0R/ChcB/UtCdtafsiVJ4KcnY0dXR2cDnl+skFpo6MroLOJFk74uqLs9eS1DwYD3Z9zf8h9Km2jP2Jp+G9Rlckkm5dCQchhE3YiP7+Ixlwd42OdR4jPnQEgDUCp2kn+YNTjEpBQWMZKyiF77xUGPOc15Dyp93S1iEUsSVxRzDLkruaG7bloHZPfWz92DO72CX0+6r6ge7F30yrW75Z0ieDoUd3WSgk0RLOrqRNZymPjGMrV3DAmpfFMJjM2LD7xzXfL3914D/Dr/wPLeHHGV00y9a53vQt/8Ad/gL/5m7+B53kYDofXvObcuXP4sR/7Mfzv//2/EQQBXvOa1+A973kPPE8/vD73uc/hjW98Iz72sY9hZWUFP/IjP4K3ve1tsCwtlfizP/szvPnNb8ZDDz2EQ4cO4Wd+5mfwhje8ofJdH/jAB/C2t70Njz/+OE6cOIF3vetd+O7v/u7rPzEhUHhK8loL2axRzCNk7BisZLZ1nxOoeH/MC5rb8NjUkhuAtuqs5nMujFFrK2hOLbymAq8UdsWJG5A3OC1AtU4DZS5L3Wmsy/mk5AGqPAv6XO515TnagTrP2SA0T9OKWg0wYC+g0iSUTBPdbpdl7uVCm1/O9pRxoxAsP04mM14M8iRjVU3ruHwwi2aHYa08iTlhI95CFmu1oe17muehEqAimlQSlNFZ5XxdgmEGYUjp6UFqOa5e0Ig/43iaGxSNKxYZdPyUHM8uzwzJuuBxdhskSXe1Qk4I3VT2qX31mVNeWFZOtXWiURRs7+C1lK2G6/LDPug1UF9VSZ5awOL+RI9no6M5SYZVByv0yqIKay6q3CHLtnmMk+EUaST5aj456iseFyATDYJ6KGkq0hTZPOFxb2zJe0Em4Mro1TB2ZAg5SzTMTbYa3XX46lgWly4xd24xnDAE1NiWyXXjxHGG6runYk7aKQkND60zvGi5rubmEF8pGvN1LpJMJ8K+tgGhxXu6O4aroOP61gYcOq+QTHVtnRws5gwxUTJiOa42z8xzDckJG7jKPDWPE+beLYYTXHlMNzwHgJUbVxBu6kRl+JA0rS0/KyFgyxbajsA07TXgXPNfNqJthXy+k7OSo9cKW3xt/F5b92jMB5pj5pGFhgOvqXhj22sIlb0JqZaLUZ/vP2FSK0ixuXNM96bsbQO0NkQDTubJesSyhbZy2djRmzNH8/GsTM3funaBZ7sPDOAodXGFBxgv4K/I+ctmqnY1CX8uoyzKZ2W8+fUI833V9OZLkgT/6B/9I/zzf/7Pn/bveZ7jO77jOxBFEf7iL/4Cv/M7v4MPfOAD+Jf/8l/ya8bjMb7t274Nhw4dwsc//nH8yq/8Ct7znvfgve99L7/mySefxD/8h/8Q3/zN34xPf/rTeOtb34qf+ImfwAc+8AF+zYMPPojv+77vw2tf+1p85jOfwWtf+1r843/8j/HXf/3Xz90ALGMZy1jGMpbxPAQ1On42/329xVdNZeod73gHAOA3fuM3nvbvDzzwAL7whS/g/PnzOHRIquP+3b/7d3jd616Hd73rXWi1Wvhv/+2/IY5j/MZv/AZqtRpuv/12PProo3jve9+LN7/5zbAsC//hP/wH7Ozs4Jd+6ZcAALfccgs+8YlP4D3veQ++53u+BwDwS7/0S/i2b/s2vOUtbwEAvOUtb8Gf/dmf4Zd+6Zfw27/929d3YlkKqFI4LAGU2gOJTTWV30yRZIgV9LAYLVitRD4/gK66hNtr3COszEu0dzry7zdLhRG1OQGu2im25M4p6CWobcrPX1y6xITl+f6Aq0W08/aadf45m8Vc3aB2Go7voHFY7uI7J7Z1j6woxsIwBgXUbtwgf5JSrXlCEnjdI6d4d5jPI2QzMmlUKscoZhiiKIqKqo2Om00uHa3ksRyXYRuK+f5QG3h2mhreI++qyQCzXVmxGJ/ZxawvKx0rrRq27pEwQeeUVB7a7R7gK28m24aVKpK8KkoWAFclAV36z43KHUGt2TyrEIKJRO8cOs6/o4pXMeojHeu+bICslHCPvXnEooXpxcsscGCoKQy071cYsDEita4ZXRijfUJWCeqD/YrxJh+LqoQU9SZEU0JUKAsUqkciV1LShKsPtu9hpqpBdG3DrZkWOvgeHxfBfYBW2AnP5SptfaunTWPJJDXPYQk15wFNCjdajhAE5u/43Npp+PDjGD4qVVUZ+3eF8I9KKMg/fgq1bXVvUaUxCLliB2hvMTYzFTbP+TSKdTXU8JQz4cXdj0vo+uDzu+ylRe1qmjvrqG8rY9XuOoseuAptexAdVakJQobiizgyWunIY6mttFFT1RE39DFQrW2+8DfyumxfmODkP1Ato7bXMFXXa/dTspoU7UWs/Nu6Zwu92+T8DNa7cAp5f7DHnbBZ9Vbvj3DlYfmc2/+0JPHnScaq0bIo+F7O5hmcQKmDldqw3gtZHNO5cUdXsqkP6GCfK8qWHzIkR9Uo0V5FESjSt1PThq15ytVRmnv9J/cBSIPPLc+Hd1L2UBStFb5efJ1rPkSmniEsCPC4ki48R/cHdF2uVk4e+rx8LfRzfhkvvviqSaa+Ujz44IO4/fbbOZECgFe/+tVYLBb45Cc/iVe96lV48MEHcf/996NWq1Ve85a3vAVnzpzB8ePH8eCDD+Lbv/3bK5/96le/Gu973/uQpilc18WDDz6IN73pTde8hhKw64nS1cdiLSJgqhaeOOKHMVsNeLo3WVGUSCK5qCcHM9iufFj2blElZcflPk9ZnOHyF2Qy1D0lH06d3qZWKBkcBz6uNIE1lmV9bxEjUIoY2/euketbttCck7rPZXVaFMYXJpj1yZV5hOYRVfoPfU4WmFs0mBqNQT3mThAkk+2dYwPCYjJgQ1P6riyaoyRzTc/lpKBINdfDhN548TcbEasFxjTyrK2u8EJMMvp0OGRlVTyY84LVPtrA+j03ybFTD1ers1651rDV2BUqEchShuPSiVYwUgJkOi3Hg5gXqfV7bkbtjvvka3ypZCuTOSyVwIiwCe9UR/2s5f3ZU0/K7xoMKj3JaLwygy9HPCQJoco5GahFvL6qe8lZts3Gh5TMJcMpkslZ+Z7dC6gdl+PirG7qsWD1V7WnGiVGkUr2FsMJw0YAmFNS98g1OtQQtK3njjBg1Yr1AiUa9ZaGcKlhdpZyQ2wUOf+9ubPB0LHp3k+wqqg3Wf3F7xeCk4YySyqNtoGqaae5YTIhP4pgtQ5XWS/Yns2LOiXBk3P7PA/rtUAnh7baoFgC5VyZ5l6+pFWwlfNVUKwBF9c3c3SOynuh/RD1QrR4o9fc2bhm7jS3NG9tfGEMQM65VVsgVPAjzRM5TnIe1DpN7jwQM31giun5PXUKghV6QddnSJ14oW4r5E2lvbatXe9Juej5fC+b0LIVkAGvw9AcykJuciGNZln1Sa7moaeVf0XOGwMyArVcDd//bcHWJLbgjaYDPf+5Kbnz/MJ8SzXf9cVXDcz3leLSpUvY2Kh21e52u/A8D5cuXfpbX0P//5Vek2UZLl++/GVfQ5/xdLFYLDAejyv/LWMZy1jGMpbxYotCcaaezX9fb/GCVqbe/va3M3z3t8XHP/5x3HvvvX+nzzNJ5BRlWVZ+f/VrCNv9+3jN030/xS/8wi887blaWQorUTvV0T4KVQ0qF3MDepA7Jr8XM+RRa42YgDuaLCAU+Xn8pEzoGttruiVCL8De52Rl6pH/98cBAMf6Y6zeexsAwFk/rE0FzXNSu3gRNhFsybw7WNPml6z2my94F2X286OqTpmXmO7LHdvgiQEWYwlxNbbaTOSkKlceL6oGlYp0PVetImxPoHm4q46ly99bGJUzqua4oc879zTSBHPTyBNCE6JZ6aV8qrxWnfsmOpsaFiWIYDGYMNyQJwW3c2lshKgflhVSIiajLGTlkT9EHbeqIOWjPvvc5EnKx0qVGK/b4erKTs2HrWBaZ+MoCmV6yZ9f5BDr8u9F0AY/1mbq8/uXkO7JSiFBCYDqHUZVOyK+p5khHiiY2Lu1IysHje1VhDuyZYltQMfYOyfffzBgr62n/uqL6JyU1YnNV76U4ReYZorqHPM44bGl+bIYL9g8ttZp8LUt3ad/jHE7pCyFoAqkAblYjlGNunr+G9B3Njjgao9dqzExeH5ZjtHozC78LbW5EloRyUo6gFswmfOMILZ0PGP1pmULrnQsBhFmffkZZATqtepcDSrznMeDxyIvMDmvhQbtE/KaO+qYRBCygraYDHQVCmDDVrqnLFtAGOpeqsa0VzS5mqpQwnH5XmmMqbJ6wC1eXM9mA9JgrVvpfUjjQmPstZtoUitBdR+k4xnTFmzX4Xvca4U8h6lSGPRacNfl/SfClr4ehpDBUf34rNYqV45Mng/B8Jj02bSzLAq+R1k13Q2Z4gCjAoqnafdU5jmPsXnedO2F6zA8adkCMyUg4lZeTwOhP1dRFvmz+r7n81hfLPGCJlNvfOMb8f3f//1f9jXHjh37O33W5ubmNQTwwWCANE25irS5uXlN9Wh/Xz54vtJrHMdBr9f7sq+5ulplxlve8ha8+c1v5v8fj8c4cuQIrGwBK5GLcJmlWvrt+VwqJo6FnaXwe7LsXWvVdGPPseZZzS7L1877I14YG4eacBuq555KwGYHAwwflpBftxbohwurnQqW7xcAbG4YnLKUW3jqX3fGZoMZNM9H971zuRS/GC1Y1m/CS7rvlgPLl9+bRXNOosjRGNBKslprAL8rYQhaYGqdBieRgJZLu6GvzRYdXZY3LSEIviPIxO+14R67RZ5Du4e8L6859c0ri4Ll4iZvxw093Z+MlVUxv88y1JNsDXHloOKoHd4gGw6zkgdA8oTsBzZ65Aw6p+TnOr1NQKlBi5GsnGZ75zT3qKfhtFQdf7Z3ji0nAL0QA9oWgr9zEvGCWes00dyRx0NGoWVRMIfMEjabIbJMvt5iQ9n9z+2h/9gj/Nmb36SS9Za2XKDI4oVOkF1yNS944XRDny0hTI4dSebTSKvDhJko0fVexJzMQNi6YbBvJlikpIvZ0DVYW2FV6EBxp4ZfuoTGtvy52VmvKEQBCVFbRhNhWtyJ75dMIh6jMi/4vq11QxQqYaOkpMxLtkbwmnWeM3x6RYHJOcVvHMRsgXHolfLv7uGTfHzVxG5eceWWgwjkSNR4zjlxo7540V6E8Tk555o7l/n+IjVsMok4AVs9fRK1oyfl2NZ83Vj6KksWQNIOPFLYqWsY5QWSiR4j3Tkh5qQ2WJXPgKuTtfKqbgOSJ6XUpl4AcuWna2TlCUqVTJk9Pcss5YSvcaM8F8evsZI5HQ61jQfzK5OKepPtYmI9B8jE2Olt8n27OPslPl+2PPk6TFC+muIFTaZWV1exurr69/JZ9913H971rndhd3cXW1sSL3/ggQdQq9Vwzz338Gve+ta3IkkStkt44IEHcOjQIU7a7rvvPvze7/1e5bMfeOAB3HvvvXDVQ/u+++7DH//xH1d4Uw888ABe/vKX/63HV6vVKlytZSxjGctYxjJejLGsTF1/fNUQ0M+dO4crV67g3LlzyPMcf/M3fwMAOHnyJBqNBr79278dt956K1772tfi3e9+N65cuYKf+qmfwutf/3q0lPnfa17zGrzjHe/A6173Orz1rW/FY489hp//+Z/Hz/7szzJE94Y3vAG/+qu/ije/+c14/etfjwcffBDve9/7Kiq9n/zJn8QrX/lK/Nt/+2/xXd/1Xfhf/+t/4UMf+hD+4i/+4rrPq0xjlJlBUKSy+mJc9eQBKv2tAE0WpqqPGel4BtFVZfkT20zGpWrQ9NwekzuzKwcQZKJHvjWOy5UxEYQoE1UKf5ryNaB3kJYtdEXAaP1SqJYfli3452yeVuAJAFhEU24PUhimgAxzhC5X2bJ5hnggd/es3FrvsuJLNLu6fYiwUc4UcfyyJLJG53Q7DsevoVCwphPIpNfdOKJhuizhigJVdeb9MVcUvNBF/Ta5MVi5WZv3UXXDEjYTFIsk5irY7MwZAFKxxq0oNnZ4h8v9/JKYd8WL4QRj1a+rdmoIyw34cwG566XddDEdauhMEdzzOOEKlGdUoiyhhQQZqeb6HveBDDdXUN9Y5fEEgGw65e8tojFXpqy6UoEdOobOTbL65v/1l7CrvIoOPn8Rq6elAq5mGDKWgwMeD5qrvduPAQDaJ48yTBL3R3ysJjmffg56bdRWlbllzdcVGPo3TVjUUOYF94AkPyYRNivKQoaSphqqJZ+1PDXMK13XMBlVFbXBgVY0ZtpbjcQTaRTz5wvX4Sqr7XtGWyENtVLlygk8VOtSCuZWUOx0L2KYnMfHr2syfJ4DM90rjr6LYCfTlLMsCr5Xm1sNPhaqMi8GU/Y7o2ge2UDzlLzG7pFTrBIs06f3meKfFzHPe+1Zp59xeZzweGXzBKGq1JFxsLd1mKtv5dPA9xj1ucpsrzlsLEqGssX4SkVIQc+NMk35msKYe0RtiHb7rEhkTzRTKZ0mhjhBwZ+9VYa7hecjVS2MFsMJnzP1QM2+ApH97zPKoniWydTTrxNfy/FVk0z97M/+LH7zN3+T///uu6Ur7J/+6Z/iW77lW2DbNv7gD/4AP/qjP4pXvOIVFdNOina7jT/+4z/Gj/3Yj+Hee+9Ft9vFm9/85gr8dvz4cfzhH/4h3vSmN+HXfu3XcOjQIfzyL/8y2yIAwMtf/nL8zu/8Dv7Vv/pXeNvb3oYTJ07g/e9/P172spdd93kV0xFKV8FpScyKmqsb3wISbiDO1PzyjHlI2Txjx9801iZ7BAc01rp8wy8GGi6jsn3cHyGPHwOg+9N5rZB5B5YfauXRZFBpjgpUH7oAKoaSgJR4E1RTJJZOpuKsAvUBstcWcWQoqQJ0MlVr1xD05MO8vtljThHZGohGp2LuSElLORtXoAQAiC5dwehJ1WuuVcPKzdJ+gbleWcqO3EU0weK85PvM9hUPxfdYru0Pp/oBHydaZk4PXwNqEo57TcNTN/QR3CBtK9yjNzP0QL3AilGfLQxm+7rxdD7qs3Ejf36jw4lCPurztSdlmNtq8cJWfaNWNPqkCJsOsdiXCU6ZF9rgkJycAYMnkuuHqKUTHEqAqg1kS9iqUksJWD4ZstXEbH+Azkk5tu3Td8j3JDGGX5TXoP/QWf6s+ro8f68Z8nzwj53gBbWYR5WefxSUPMT9EbJYfm/Qk7CVf+QIbzDsWk0nsoOJTuLIOqETMNfFWdtGUe/InwPdBzDje3nOSRQ3JR/rBK3WaTKMWOQ5J7L2sNqj8up4usQyNe4lUoi68Qzwqps0QCaBZi9O+X6dwEsul1wuCF4t8oJVW+ks5s0Z9aWr33gM7hE5p9kSA1LBSjAXz4h5xNBfOo14TOj5UOba8DWLE+aV9U5sMyROkLbd7FQUv2Y/TwDI5zPY6v4TzSnPaXpW5KM+J1PlItabkcWCj4vsDNxmHav33i4/q9XTmy8VxXTIUH5pKBfJ3NM2oL1iNuE5F+5sI1MipWyquiCUe1jGize+apKp3/iN3/hbPaYodnZ28Pu///tf9jV33HEHPvKRj3zZ19x///341Kc+9WVf873f+7343u/93i/7mmUsYxnLWMYyvtqizPOKjcgzef/XW3zVJFNfq5Ge/xLyQpK/4Xi8+yoX80pFCpDld9qppXHG8F54U4jWYVlNIY+n5s4GnJU1/qy58mghDxu/10bvTun5Y/c2eSdGndUBVPpXlQaZ9ulawBBElscJk75pJ+uEAVzyk0oLFHP9frP6JP+/4N8l08SocqkWMdMUs8uyUjI6O+C2Eiu3yKqSB+hdZZoin+sdPVVC6Li8Zp0VeEWSMxGUSOeW42q4bDJANtcqP/mvJrkmkxlDHnmcaDiJKwa6EmSOKxuyGkTicnFtFUKS3eVr3LDGxF6TRE+qz7LIWSRgh004qtUQew45boUIy+1ePF8TyNvUR23C8OD+Jx6BUPAiGTA6HcOc0PG0OSSfS8wVtSRKsXFDBwBw7Ntuh3uDVJOyGeqlc4ZBZw/d+14hP1a1IkkvPM7Vk+lehKkSJTS25I6/e0OXyc9+kevWMEKwAWeF6MwqqYK9o6htTGN/gLaqjJkEdppvgDaULfOiev1cOT9y1VLE2UgZoi+SM5WKGCDnDlVDG4fX4CmhSzGPtGKW+jIOIvbdyuJE+2r5Rn9FdSzJNMVUmauS6a7Xu8CVW0sIruAgS7Xfkfo3M5S5ju/x77lv3uFVhhwlfC/nerAh55B75EaploOcDwSjVYjYRnWMKphpNOdxpjHKk0zDXi2toGNRCYBiIKvM5SLWcLOjxSB0/MlwCltVfCHsSnsooFp9L4uiUtmie56erbbp1+f5yNUxZEotSxVoOleu3LKicqg9qWybr4cIW3CVxxcpCFP13Hs+oiyfJWeqXCZTy3ieY/Dw4yifkg/w+noXruJ35fOZ5jRxv6aEe/OtnFzVsvlmyIsAqXcsW6BFD8VZzPAeG0ue2Ia7Ixt0Wn5d94pKr33gQdhs02A3OxDE3VIPhnw+Q0bmeobpJpsmGrycPDZhvIJNIF3VbNf3Ak6mMiPpshUUGnR9uKFMimqdJkMO1JdOGGqqMokh1IOomAzZ0oEWszIvYAnVkDjNeQzdxqPys5od3fg5nnFPQfrX/CzH91DrkmN9g8dL9z/UY1BEE82dyMnVfIFc8YXs3hY7KNtNxZmaR6ygq3WbCNQiUmkqa+4GTa4WQQpKYQdhM6SRTYdI9mSCJFxHK70UXCHCJjf/tezH0P/CU+q85bhsfMOt7KZv1XwDTlNzY9TnhbF5qIHV0zIJ637zt/AilCmeyPSRL7BZY/OV/wDFitxklLMhnxbNKdd3MFUKt2Qqj8Vv1XQCUOR8DQCgRLWZbbmIjU1KzD39ZvvyWJNJzAsfHZN87ZwTHK1WrWnH+lEfIlDmqCqZKr1QO84nGWYH8nwmFwf8ue0TMjmubW1rJWiuE/y68Z2kXkujPtujUI884Tp8/9ieYFdw+ruzfrjizk1zrhjsI6F+d+QibyQRtU6DOVGkmLSEQF0Jd9ytYzzPTIiXLECQpxVOVGH8LF+Xs2WJmbzkzONa6I1Vp8lJjR02dSNvMr3dvQinLuFgZ21bQ9OkzowXmD8mrTsasznctQ0+BkA+N6jxunAdTqbtwNP3kpGs0b2EyVAbg5L5KzRXq8wL5qM9nTLR/Fnauuj+fwCQjLSNyTJefLFMpl7gsCyhuTCX+uzVUl/v8s1E1ShLCObo1Dd7GmuPZ1pCvK/9gWjBdUIfNUVGdxJNqmXPkxjM8eHjEjYv1MJohQFha0df8qUZZ+wBsxhMmEhNu0ZLCN7B5vGCuV7zgZav+x1FgLcF3FAueHXoVjnEufJ7TXRPycW7tr56jZ9LGUcoVbJTpon2CprNq5wmSF5Zqlzk0zhDoBJCaprsjCb88JvvDzE70IsfIBcoSuZqnQZXi+qbvad1lbcMSwaqABJ/xhKCd8iW61aSL0AmAcR5qq91mLc1/aP/3zUVgyxOeE4J18HKLccAgDlZVtjS3k5ZwudYJBmcjtxZ04Jr2fp6+70Wai1JIKdEoPboeayoSodd85GrSh43cp5N+Li9pq/9xPqXmAQcPfGEfL/rovlNsvtAvnULrERV6FRXgLy/y5sC0xRwriqC80HM4gDpIUaLqDGOauFbXBnxGEa7fcyVnxN3FYhS2K48vjIveIyLVDectn0lijCc18t4Bms+Vt+rCM/ZotI8OFW8G9pU1Fo1rrSIZldXKqZD7b2kqqFZFGNWyM+f7kXw1Cak1lHtiTyHncC7N3SwfrfkE9VvulUe89o2z8MiGmuLjoUmqhPnSbgOP4PcVl3atQDwVQXUXtvWZHvoRNVSTv+l7TH3D+lCt65JYp5/pSGaoEqIGwbXEJjj/qjSWql2SD4H3e0T/DuqCqXjMYaPyspQ7WCA+lbVssayBSf4WRSjo37vbUm/NCFsuI66L12XK6cibGmrEcWLg2VB5GTzoLlgxJEs4wiZQgPi4YSfg+azmRLxuD/i+T3fH0AoXhZXoZ/HWKr5rj+WydQylrGMZSxjGcvgWCZT1x/LZOoFDq8VoMEmd7NKLyrarVYVOnInF108QKBUP7K0L3dyZHJp2YIrDmaPOeJj2IYcvZgMWP3FPauaXQ35CKHL8UgrxoeAVCMRp0PYgndSBFkCgEd8n3rAxqHpNNWVCnJdzoUB/dW42Sv1YQt6LXZFlsfrVo4lH+wbu0NPNzI2xrAw+gGS+tELXeabkaM3HA+O4jaYx0hGhdHeOTS2Buq4NHcjjWI0yZldVWrs3iZzlqyar/sPquN3DaPR9KkzsISEIUrD8M/tSf6J02hgcVn1BBxOeGc7Uby4wWMHXGFZu3WdK0MMcU2GXFUsF7FR/QivbQicJjyeprs9QbBXHjnPx7hy+40Mf1BYQrA6bTGc8vwefu4LhjmlrHSE974S+dbN8nttF2KhKon7kt8y391jzp8QFuotWQFZTBREd3nO1cMyTbRiUfjASM4psjaYnNtj7lG0F7ERLPF+bM/mCmqRX4LfJSPOq80IZLDb+jxi9ZZpgEvjnadphYsESMiS1GEQotLL7WoVbjqb89iXeclNfgmCq3UaPL8te6CtDdg8dq6/OEu5SuVuHoGnjpeUouViXrGUYHWxgtPgHPDfRb3JffwI5rOKDKXq7mA2Fy4TrZAjiMy0unDDgLmEBG17zTqiS3LOO4EH0ejI7212KvAcoJ5xFyR8OXj4LPPwCK51wwDhpqy8plHMz0mXIDo/5GtnOa5WrvY2kbdkZapUXQeQZxCpcq9fRIBTNSMFNM3Ba9b19VRVclPJWeQFCjUGidGfk6kAxnNvGS++WCZTL3AIx9GS9aLgZCnujzDfH17zeq8lH1idU0fYDqBcxOzCe1E1IQ08G60dufjWN3tMmGTfJYChB9PZl7rbW7WAE5EyMmwFilyTaQ0yLz38AKORMD3kipx5FnlqdnkP+Gcibxd5yv499fUuw2gMNzTrLD8WzQ6fQzFUJf5+H4Uq4Tuhz02i7aCO+qZT+axkMmMSf329xYs+840clyFOr5WAiu1Eci7zgh+Os/0BJhdGejyUdJ+4YOFmjwn/zuYOd6h3uqodR7un/X8MiwzmIGWJ5kQVuZ4zBkww3VWJytkxu+MH612+9szFMTx9stmcF/LaIc2jg+L9iMXU4F8JvjYUeVqg/7B0/06jWAsBeuS1ZPOxBr2WTgoMH7TatuJcrWwB5PmTRBCKK5WOFYF9MmNuk+3Z7HdU78lxaWyE3ERbhK1KUkLnG6kWHeNz+4j25YI1uzxjnlGtpY11FyMNfRFPzw19TvDNoPldxhHKRN4LdD1R5CyKiPtjJouvnJT3p9cMdTIWTTTnL9f3DVkkpFHM1iK1Vg2NrarruHAd3jjU17ro3q7sNm6Q8n0ELb4vLQA0QkWsrQnMdjh0r+fRlEnslKy1T8bwaMOVpZoHle3zuDC0Nx3qdklGMkmJTNwfG2T6GkRdkeGJ8F0PDD5RoBNlS3CHWXp2iUaHYdHxmV3MFZxLHNPa9g68DQXn7u1ygh9flHxA/8gRTtasms9QZt7aRNFQhHqap9kCJUGZZQGhOGKcSDtepVk13Wt0XReDKSdOebyoJNpMuFeb6tJ7Pn2mlpWp641lMrWMZSxjGctYxjI4lqad1x/LZOoFDicMUCx0KZ/gsjzJkacKcnBJwl0ywdz297m0XySaFNtsK6Vbq6bVdGFLk05nWhGiDSU9DUFR9aLIATIQNYiqAJ6mVD1jCKzMC8yVWslsmEoViTLP2XSTXg8Ai7GGH6jK5fdaXEWi3Z0IW7K0D9lHrSiUKo4M/6I5myFawwlXm9xWi3f8jjour1lHfT3l7+TvMNzgaVxEEEK4EkajnW6axHz8TuChcUjZHCQ5w0Vz1Svx4KED7H5CKoyOfesdaByXSrXFvqwkFvkTqO/I34lWTz+MiORvyORNt+oiyRgqiJQMPh7ECDfkOQRrHa5GMnR3lXkpOcbb3TVAwRelrXbeqLpQa/iFqo4Fq8uufPESV1M7pyRUGvTabJtBVSUADGcAhvLJIN1befa0D2Sa0343Y6J1oKwfuqeOMFRrmfYPSYxMkd2JmJ+nBeqr8v7Jkxyjs8pwUlVKw26oDS+nKc9lx68BfrUtlO172uiyf1lDpaoylY/6bHxa6zSwcjsZWXbkWERjJmRLuwLVn7PZhd9T6kJy3d8f6GNcb7Jghe0QxjMWNRRJhrkyQXUPy/O2HVdDd/MIBcF/qZ4TrI4zXOIBMCzL4oZzDrqKkC0aHVbjUZRJbMDJczYONaGtzJjTZDVhqkqpQlR6MQJ1r9rNDlenTZI7wYxW2OJnY5mXmkJA1XejIbEl9LOp//kzAAD/0XNYPS1779WOngQ2pQK1qHcRW6rKpPQPNTdg41HLEqxepOO3HLeiTmTY1XCWp+fo+IK2UWjvdNgIlpW7Fp63KAzLlWf8/q+zWCZTL3BYtuAHSjLRXeLTacKKJbIFKPMCs75MOqK9iJvsuvWAeUa3/8BLAQC9+75B+w7NI+1foiTalmF3AMc1eBKkrkmuWXSBaisH4iIkk6jykKCEkJvS1gPNGzC8mSwhrnHntmy7okrjZCrQJXxR19wjix6KquyfxwmX7Ys046SjuSPgKA6XKT+m73dDn60D2IfH81nxKAA4anGvpeSZlfH7hevCpX6kbsbn63cVJyzJcfAFmTgtRp/A0W+RY0cu9W4YaPWZ62rvG+KWjEcVNSLbOxjQcK6g0pUbuzj2bRLWadx6By/a1DBbQrXaB4sXQWMxtEr9sKff275XuTYUtZZy3R8nGDwxBAAkkfx75+Qmc+iKNNPqRVuwaswyHNxJwWelc60wpe93nYqfEynVuqeVL5jna1+w2YTnfDkba3dutci2jwcMn6zf7bAale1I5prP53d9hi8Do5sAnUs2TzBTSWS020dL/b6+rXmJjtEaxDl0TJ6WShRQFFpZCyPZzRJt36Bgvlqngc4pOT9NDg4lDF5LNz8ePr6LKw/JBJ68nywjmSoMDyQRthgmY4Ws4wGqA8Bi/zJfc3IfL/NC8xOF0Oej1G3FZIicXL+LgrsrmPcNzWPh6TY63sZWhdMJyE4AdH+62ye0ms62gUJmGaQiNC0xLNuqNPIGqjA3oCFSokrsfeYiBl+Sye+xV8/RPXqz+i6ji4GZ2NB943hshyEMBSCNkUgz9qrLjPPX9igZcx3NFmE0d0RRdXJfxosrlsnUMpaxjGUsYxnL4Fhypq4/lsnUCxwmiXnenzLckExT7rdX78ndtBM4aB1WkI0tsBhU+1cBWgWSXjoP77DcuYt2z2i+qipQWapL8HleIaMDquxv9u4iErKd8c6XK1SDiA31bN/ln7mhax7B9slos8FlaxMeyQ0fHoI00vFMK75Uf13L9bQfk+Nq1Y1PRFWf4aHp7gjz/pTHq1OX40gmfJYteNcXbq/phqOqoldEEybNFrMJk3GpiuZ3mnyuV6u8WF2p1GVpnLFnVq1dY/UeqSwldEEigWqvPQBw4ggWVaYiDS8C0mAS0M1wm4caDG+SWSSACqmdyMJEAAYAexHDKqjipQ0UaWy9VsjzS++sU670eQ0XsVKTji9oOLm1owwlPReJgnPTOGOyOJs1JnNY1NMwnXPllWBK0/y1c+oIVlQvTPL+yXbPaMf7+Qy20QuNGjRT9SMZR2y+6m9toNNSJGPlVRSdu8jz3BRwlIs5ksmuGjujb1yuYU/6PUFkwoB6nrYnIsDVoDKJmQBeTIYMkdbXOvJcfU/D+6m+Fx1bO6DzR+Ylw83cjDqO9HfFkX4eBCEsdu0nBazN0Jn0r1LXmWBhz2H4EuIRff/UtRM/q1HNylteaHhPHV+t24DXU95m9dY1i7GzcUQ7+ActWZGCgobtasWmzFKGEoP1rm6AvC2ri2Zng2QS8Xm1jstqWBotMFHu+vODITpzOZetdI6ap+A7IppnC+2lVRqwNBmXGs8o4RrKPYLpi4LJ8vXVBd/Ds8vaHJZpB89jfrJMpq4/lsnUCxzCtRlzX4wWmDwlb2Kv4WLlpFwQV26RaievVeeHcjKZGY1vx6w8opvRa9bRVe1TyiTWEA+VwDPd4kIeyFVKEfNmMGCIMi/4AU0PxCzOGGYUnj4fE5KhRay5s8EqRDgeaGkh2fXi8hVOTPI40e7vapEU80irdoTN8CQ9aP1eGzVymL4wwPAMKezOcrmfoMYyLzixczeOVBzC1RfoxWAesazebMJqumEz58oWvKBS8lDmJQ7dIxf9rftu4SQqY0PWMYRa0MssYfm5afNACYEbBvwwnu0PWCpPbtiNrTa8Dbkw2N11Q4ZO/DINHxVJBpj+orQgFDo5oITMabXhKChkriAbs72K7dpwqeH2ZWUjcWHCdh32VWqk/U9/ib8DANq338rwjuW4fB0IdvWaIY9b69jWNU1lLcfllkHpNNKNlNUiDwDlnrScyOMEmfpeJxzB68jP8k6elmO8c4rvGdMeooROzOjffLFgHp1sKyTPffQlaelQ6zbYbsPubVUtEyCvd2lwi+i70mnE40tJh9kuJosXulmySnIXwwniAfEuC6SufC5QZwR365geNyE0LDrqA0a7IfqXEiOvl/AxkNlpMp7x908vHsBrPg5AbxCcRoMNSO12D6Ha0ImzZ/l4abPk99q84bPbPYamOSkxHNQRDTjBh+NrMpEyS80PLvK9uP6Sm+EcOl45r2LUx0JZbIwev8jXy1XPBTesIejqZxfdN1YawyIVHyVTaVxJouj3/P+Oa6iDPU7g2T3fdbQFjhB8ryTTRJs1k12NWMJ8L+ZYJlPLWMYylrGMZSxDR56jFM+iurRsdLyMFyKo+jIfxOxzc+xVx3Hom++WL1A7qmw8vsqjRfcmax+Vu/e1u6VPkH/4iCZS+/VrSMal4VtUzsa6IS/tfoRtGPYlvBs2q020q7Q9m0nyju+x0Z5pVldXLWaE0QfQrD5QJcQJfXikzLM1QZ12/iaMgaLQvlhUSg9bTHh2fIcVkfNBzIT5nJVZHvztQ/J97V7FTwmQihyqThQTl3ewPO6TGfeoc8Og0myWCM0Uh19+AqsvkURpu7fJ1QdLXGXwCFlJzFUFZah6iAGowKM0tkWaMfG8sSHHvXfbDXCPSMUYwq6EIgCIQLUaylKuLhRpxuavJiTITWkNeMbyfK2SUvNlsjvl7/dbNZ6/9G86TTA8K8did09XsVYbHmaqbxy19JlePNC9+U4chbMpK7Km0ixQcJeztn1Ng9oyiSt90IjYbrd7utWJo8nIVFUp8gJNbgcT8blSRUA0O7BIPWZWDcnkMYnRUAKJ+d4Bk76vfEle2+ZWA4fVPVGpkrEvk/GZszHDfGk05woiR6tuiDX0/UEE9SLJkSekkF0wbYDGuHFkA+5h2YJFhE1k3Boq1XAqVYVsF8VQeUvNJkwgp2OaG0ablhB8j1I1rb65wpWY2f5jTAsAtMnoimqYXbv1G6TPGCR0V1LlJ9HQNJmhFqO+rlI5nlaD0njOI1bGOlvHuGqdG82FybB1ujti1aYQul1U87CugHJ7nySSij0zykIrA8tC9yJUYTZatoIQtj+t/F24Dj+vbM+Bp4jv0d6Mx4uq9vCaeL6iLJ+dmm/Z6HgZz3ukkzk/hOqrdZz8zrsAACv3vZwXt+wp+XCeHwzYOG9+eYJSqf3W79ypGEICypGY7A4cl80QqSRdpgvdjDaJUSpuECuJTMPDouAHaBbrhqOkjHJT3dG9vtnTdgSq+XClT52wNQcgCHVypx6ITpFzwpZGsQElagl1PddQFD/4SYEkbK0ANGClMi9ZfcVwXLPOiqZ8cKDNEkNl3umF2tRwMkCeSq4Mm/z1DZsJ22YYJI1iVjSSWq+5s8HX0wpCbe+goA2To1aMxgwpzoyHfvOwPK7ebTewnYFwHfhK+dPakQt+/cabYLXV4u94sHKdjADSbJW5T9GcE5SK4J9gvtx4qAqbDVnpXONBzIuR6zvo3iQXRIIu5gcDdhfPL00xUsntSl6irfh/nZMb/F0Hn5F9+vqfP4PG9mplDAFUkjnqA1gY/5pwmOn2zdCwGne/N+U5ZRppNtT1sPywCoMb5tM0T0hpWc7GyKZykczjhGFwsm7wWgG719tto6cmmWNOk4ojPUPHBqxDSjNAQ+Zuq8WKSPpd0GuxsnD05D4num5IPENP33NuAHtL9bazLBQ1uahnnuJJLSJgfEUd15yb/7IBb5xyBwGzaTkdi+253Dz8/J8/xkq1ztEW1k4f4/GgMS0U7wuGxQApA/PJUEKRkEkRqy5nMY83he06bJFRJjFK2qioZ1s6HrN56+zyrNJQHZDPYeJPeVuHdTKUJbDI4ZygxbJk5SuKTP+swnLdauN16nyg/s2TjI08hW2z2W6e5myVED0leXzFyrXq6mW8eGKZTC1jGctYxjKWsQyOsiieXWVqadq5jOc7ot3LXMk5/KqXILjjGwHIHTQpiyjSKMbkgqog5SVXJNJojvmerFiFSokm6s0qYfGq8jOg/VhMSCOLdNdyViuZBovGZ7LSrtNkr5b2DYd1Z3XaAScxwydFNEZ2RR6rXatVq1aQu3WqLggD0qNKT5To3VnDdSpVEwAoozEr1CxbsF+L4zusKGwcVj26GiGymVKXnXkc5UzuBN3jt8n3r2wBDbVzVpApoCtSk90pk77dcM7wRp5m/F1U8UijOWrKw8tyXIYeSgU7FbMx8r7aLZ87j+ii9KRiMn5SYLavvKk2RxW4s31cjjdXJw+f1L3DygJQMB9V4cq8gCAhw3jO3xXesI9SwVl8nbNUtwQxxpbbn+QlQ3rrd+6gd1pWOlilGSdsMmlbwFpNXqdD92xi/e7j6hBVP7JxhPq6hFcWwynOfvhRNZ7y7xt3rKGnYCHgST5/ni9GKxXhOVr9ZfpnqSqD02igvq7UppMZho+er3xW8+ZTXEEtF3OjstW9pq9cMY+44hCsd7l6THOvdWwLzoZqmRM0mVRt1VQFK54xxAzHhfCUijG2+XxIsRkP52x42j62VWlVcnXUWjVWUm7dL/3nane8AnmolL22y+asEA6Kq5RqiCcMnRXxrCIMASQ8KlT1rYDgKhjBU9Gux9XgoOujd5Oszq3cchSN42o8FJG8mEew1PfDshiarlQdDW8oquYshlNWzBJsC2govut4VXNUSAL9dFce43R3yhQFmsf11QChMsy0u+u6smSMTWlW+k01Hz0rLU2XYJhQCE0hUM9OSwjdfssFaqpdmLAthmgvf1YS+23VDuf5iPJZmnYu1XzLeN5DOA7WFZfGu+G2yo2fK9dmcjGO+yPNSek0+KE2evIyZvvyxltRC3q4dRHemlwY7e667slnGNpVJjzxmIg7UhS8KEx3J2zT0Nju6QRBJSKLQcTNf8//2cMsjydoYf2OLebCJOMZ83VsT5fjfQUNFLmG+Qpj0WcILYm1SWWcQDSpxK4W5NEEM6XmA8Bl81qrpo0Xb5aKLcvxIJQpYXzhPAafl4t3qJKa+u33wl6VnCqT00TQhgkvLMZz/n+vFXJySeclPIehIGvvPCecxGUzYb64P8b4nEykSZ1Za3ncbLfMC4YpFsMJQsVHYz5O0EJJC3au+TiUnC+GE178hWdj8LicZ074WayoRZ3glyIa8/vmu3uYnJc/T3flwhR0fWy8RC6Mq/feppPymXydZQtO+lcCFyN1PvF4YVgPSBgvWOswr21yUfNXCA5sbK/x/CTzQwAVRSUrybprOqmHdv7nBbnIjR52HUTq2tGcz+KEoWtAQ1e1I8fZLoDGJZvFDLflccLJITn9N45sauNUL+C5agnF78o0zIeiMJp/p8zvo3586TTRtIC1DjzFt+G+dnUfrWPyvJs769xI21J2G6VwNBSVLTSc63uGQk1tRtIYRaYhR/oOTlhtwc39HN/iZIrugzxODNjV4nGRjdnzynWxaj6EYc3A/CdqsG5wPC1hM8ztxQuMz8h7mOw4Vk72GKazar52v6e+jE/u8jMqTwpOpmiedk4dQe243JjY3TVt1lmWT2+D8DRRmsmUEXS/m+bFzH9MMqZO1Fo1jM+rzgKPyevtl+WX/c5lvLCxTKaWsYxlLGMZy1gGh4T5njlUt4T5lvG8R/fOW+DdIGElCBvZgfSmKSZD3vnSzrvWaXK/Jsf3mEQszSfljoaIjdFuH+Mn5Y6tdXwL/lEJv1wNq8n325pkafaRIh+cvGCSZhbNGd6jthJuWNO70STnHVVKO1ETrpsnDFn4nXrFLwkA4isj7a8ihDbFvKq/FqCMBEnJo2DE2f4Ai8GEj5tIseFmD7UjEiIiL6PSaKfhNutwFYRF/kDJOELrjtPqyzSxPVxX1SbbQjKVu+l4EMMJ5LH4vRbDBNTCBkWBdKza7+ztgsAZqp6IsMnVCTf0NWk7lbvxzslNrCoITTgu+p+THk2L4ZR34WT6WXp1Pi8rS9mwkQm4UcxeWUWSM4H8zB8/hP5DZwEA7WMSUrB9j5Vii8EE8XCujlFVHe8+ju6t6riCkKtgVDmyhEBd9c5rHmqgPE/XRu+ySfGVxQttcjpN0LtRVqwOfdMdclx3jhkeTTnygawiDb8oIb8sivkaueuG+CBLWBFF8yRfLCqtTJqKvM9Gs5MZokuSfJ2OI55/je1dqfACKko2Uglm8xFDvM0j8jOdnVPSaBKyYkFFC1bLLmJtIjmaMME7NcxZXV8T/yvGnGkVeiuLgkn6lhCaqP3Q5wEALc+Hc0w+b0rHhcgUjFcWrFQTiVKcRQNWUlrC1updEngkWUXd+/9v78yjqyjT/P+9VbfufnOzc7NgggJh38IAAdug2KJnXHq023VYRoZpYMC4tI497RgalcYG7e7TY+PR4XDsM91N64A482sU0JFlDCJrA7KFTRYTQ0LWm7vX8/uj6n2rLglJ5EIi4f2cwyG36q2qt97anvdZGZJJg8U13XHi5xJpboVs08bWatL+kSPAx4WXujFpq8zHSojq1WFa6JR+OVCyc/UBivPgGaZ1bK1p4cEBKfle/o7w5GjPte/GfB7IA6udm8ktAEjVNX36WJFFMpn0rKxkHy9zhZhRlsucs43ZB+LhML92sWDY0DA6rJBt2t9ME+5xmaIgrjLCzPftEcJUD8ND2AHEvjltqnVlCDgsrQAzYQBGXTBAe7EwnyIWvyQrVu670HhMhaJ/1GVTvTL2AgfAzX/tzSiioRivCajGCS5eo0sXqmRD6IkFY1xdfqOepDJrdH8uIAXOnYfbnwpAi3BjL37WVzUSS0g6yHwy2MvPkeY0jmtzGAWcw4bpj1RDsGM+Tc7sVCMLvI7a2swjqiw2B9z5+kdSf+k3HD3DC/em9MsxarWxhJuhiJEWIM2NtIFaOLbLn2G87Fl0pCkLdqiukZ+DIUyl8JmgI8PH/W1qj+jRfGdrkT5IM1PKbqMosz3Vw2vAWVI1AUiVrLDoH0mW4gAwUh9YTZnnW2oCiOoCoeJR4EjVIy31/kdbjcjEeCjKhWo1YuHrmbBmFtSZgGTelzvbDYtkXE8Wnm7+MLK/fQVppnHW/Wca6xLq+DHhlH0s49EYz6QPNZ5YeJf5ObHs4gkpPhT+UefJFB02XrA7HgrzQuLBmno+9ixVhS0jg5vR5PoG45AsKvXUIbTu36XtKxKFM0cXVJkptbWZJ5FsOXc+IYWAxJNaah/6lH5upOr3mdVkxpT1Z5lqL/DJhOywwZ6mV0xg5nKT3xEpLiCqJ89srTd869gYNV2A2qLtV40Zme5l03PPPiHm8TSbv82Tn5g58o+ld2BFlZvrjRQAksSzx7NzMaeEsaW4+fYUV3l/WLSry5/BzWtqYx2fqLEEv1kjC/i+Ik0BbiZPHTMGgOYzqTp0t4hI0ChCLRtR0WSq00cw32e6L1TcJGSaapzyQvLMzNkS4H6IWhJg7RpYnVbua+jN0Uy52cVF6C6EMPXtESlVBQKBQCAQCJJAaKZ6GMmVAotTm2VZYdTQAmA4h+paFwoFEK3VnNHVSIzPzrx9+ySUkwC02TQvxRKJIVyrqdVdupOyxZUC0vO2BM6dN+qJRZmZI8DNP2pE5Q6wbBmgRb0AgOL2cDMIqcRnVM7sVP3/NDj02ao7J8PI82Rz8KSQbHYmO2xcmwQYVdSZBki2GRFO5nIvqnn2x0pY2GSu3XBmpxkmIlNNQh6po6p8OZvN21O9hpN9QzOcWdrMl0f6OGxIY1qXvCxD8xWLIK6bu1i/JBiz60hzq5HQlM3GfRk86sfqcvIcS6y8RONXTajapplq0gb25ebcrNEDYR88VjuW09BcWnjeolYj8aY+W1fcTtPMnrgpMS07lWs9mINsNGDUCNPuEc2Zl2nMgvUnuWYgY7iRhNWsbWIaPWeag5tiSCXEgqwkjTZWjnQfN6FJijXBzAwA4QuNkFuNSE2mtTBraVlbUlUjUacpeMDIYRY0IqtMWjTz9nwsJQmyQ88FZKoPyNtGo4CuUTYnYWzRoyS/3nYYNft1J/6GMPoM08yxN9w2RBuXDB8/h0hzAC1VumnOpOVlJaXShg00auA5DE2gynLK2R2wNmjPulmbw66HWl+DeJUeHZY/kDtKUySIuB6MwTTWFAlxc1ssEOJjx01RulZZO1YYQGKC0Xg0dpHGini/2HJZT3YKNc7ffZJV4fUzWdRepLnViNq0WRNyurHgAGbutqZn8cjceDhsmMFZpHNqNtQG7XqcXf8Zz23m0WtFKjcOB7GcVzaTSU+WDZMeH9iLfjMTrmzSnrNIUABqQH+n6+caC4YTIl/5OUoWOFK1a58xRDNZKnk3ortQ1bhhqrwMrkfNlBCmehhSHIBTe/lKVoUXG4VJzcrU7vFY1PChcDvhydY+uJI7hSe0azmjfewiza2IBbWHtLWmBY16xIujr24iyMrj4douVeWh4Q3HtXbNX7dwvxbJJsFua/vxNcLQFajc3OVA1jDtZd+nZCQAPQM1C7EOBrjaOx5s5S9VI+pH5r5HZsEp8I02BsH6EE9BEGtqglX/6PEad7LEhSEAcOuRYtYMv5E0k4XHZ+eBgqlav1qb+ceE+ROFG5qNgr5+lfs/KRl6jb/UJm5KkjP83ARFpgK7XBBW4wnqfGa+4WaU5hRjjEwmFSawUlxF81k9WWhDEDa3YWZwMP+SdP0FZpG0yCNASzxpSmgKsBQCer8VI9pOdigJxXu1fqsJRZztekShK0MT3oP1Ie6L4vKn87E3F2JmNc/sqV4e1h8LBI1z1IVTtz9Dq+fGxi5mfGS0cQsipJsGo02tPJFlPBTlfeN16y6c59fZbN7lkwVTGL3VlF6ACUvmMPZ4KGI6hpcnJOWClRrnIf72fhlQMvRn8Tjz5QoirV+qdq5NES5QRvU+SLKEcH0L7xebTKTckGFUNCgapZ1Lhh9k1U1FVgUSyxB+UYoQQDMpXlzZQI02QmnUhFBnOMTdDAjGfWuOUmS+b2o0xvfBCvPaUlz83gg3GGk8mKBPcePesTqtPLpRdtj4s8DN3U4XJF1gtdid3HxvN5mO2fUO17cknFeaHqVr7zdIW2Zz8GdJ8qTyiMGYLmSqdXVGoeG4yosan99bCQDILRwMqa8hKPLIvZhqJD9m0bIUTYzwY+t1YUx1pULWTYJqw3kjnQaffF6U5FM2JoI2j/6eYbX77C50FxRXkUxlZfPzf70gzHwCgUAgEAgESSA0Uz0M1X0NWDVH0lh9DZ8dWuwOHiHEZzPN9Vw74uhvJMdUA03cpOHIMMwgTMMSjzSi+bSmPfCc0FXakmTM3N1G0k1Z0XOy1Aa5Sc+V6URKvrbe5lH4zJnN6DUtg+ZY7B9dgMxR2myaRc1ZZNmYScohnhg03NDMZ4gxs0mCmelMSRhZXphwY5jn2QlmpMBSx2qPGSYGp34uzqw02HLytb5m5bWpAwiYIqqiEb6e7av+5AW01holSVjOKK7dy+lnlMNIMUqeqC0Npv3qWrjWoJEzKBrlmrRonWYKslgVQzMVifHcS0wL4Pa3GKagJuPatJw7D58eAapkaZpGshmzaoti48EFFlOOMYbdZ+fX057m5TPmVt1sHA+FE0u06H/bfXrtvVCMX5vg+QZYnQlFaWCRJW4GtMgSZKbd8Lr4/cNMihZZ4tfGYncYmkSrkTyWaSVbz9fzpIZmWIRpLBgBc1W3WBV+PVSuSWmBql8bxeVMqNeo7cfK80xJNivUJuM+YKYnJTVV2yY734ikjMe51s99AzMnq9wp26Oq3EzMnjk1GuNO9hQnbtLLnHI75HztWWJmp7jVbmhFokHuNM7rBJqSQEqyjAir2WfSFBjax/1w6do/OSOH589iz2prTT0fL8Xt4NeJa1WjMf6OicgSrE42dvr9ZtISpw3sywNp4qEIz5PG8oopbgc3yduybLA4tLHliYXlGgR0DWikKYg0ZvYsHsMd8VWz9pu5SMSi/J3KIhvDDS1G0tlojEfz8UCLumqel09tbUbsrGYWjdQ3wJ6rad3tA0dp612pJqd0G8iq3/+6mc8SCQJh3aE/FOAWBCOaNsavDcVVk8bMiHZlJaUsJw6gu7gWavP95S9/waJFi7Bv3z643W7ccsstWLNmzVU/7qUQwlQPU/PROrhuvRmAXjeMvQSiUSOrN/sQhFoTN+YFg22QPKkAAGvY8PFh5hHZJvMoKhadJitfcTNFpCnAE9+11urRPTYJKSxZYh83F5aC9SGjqHHA8FNypGovYldOOk9QyArRmiMTKRRIMLUwoYKZf9SoYZpQYSqmrOhCVUOIJ7GTFGtC2gVAS7jnHWwUFObFnhXTR57VJww28FQUrAiqdu5tHwtndhovisw+nJInlftcaaY1w1RpDuEHNBOVkalb4R9PFtEm2azcp0NJS+M+TUEWmRiNIVSv1xa0yegztj8ALbs2MzGhtUE7vqnfFqsCyWaYhRhMaHD7U/lHUnbYDCFPf9mHGlq5v5rNbYMthfnJads7UmLcR05SrAmZnQEj4k0bisTwdpbGwAifVw0fM6vCJxNMqJIdIaOYtCTxyEImWLJ7FNA+nOw+ykjxGfXw9CiqeCiMYF2L3o9WOKKG0GD+XzsvhWemtqd6YM/Wrj/zXbLYHPz+oWjUlBjUMJWy/dlS3FyYMj9/xCM5vUgdrKWakH0ZRiSYZJgUAV3gjIYM063+/FusNp5N3S7V8PssrEcZxqMxI/FpIMSjH92Fzfw+YveLzevi7xDF7TT8rpgp1eSXKUkS4EgUpO2pHvgGaulIrNn5Rq3Eb87wZ4wJx8Gael5TMB2AXe8LF6YkCRFdoA3Wh8DqEVBrEyKsgLFJoGTm93g4nCBEAbqgnMruKRvsqdp6t7kYO3vnNtahVU+aHA2EjCjEY/u0DlhtWloT6AIpe8/o7wI10ISYXt8wVn2a19ljZmaLLCW8b9h4Wp1WuPXC5ey8v/l/29FdkBpPzsx3lX2mVq9ejdmzZ2Px4sW47bbbQETYv3//VT1mZwhhSiAQCAQCwTVBLBZDWVkZli5dilmzZvHlRUXdlzqiPYQw1cMEay6g5fBBAIBnYBFkvTaa5PbyGaZkjkZis7Dmej4bldxeQ6PVatRfYzjSHNxcxDQHoYZmroUIVNfhQqU2e2JmLWeaA5lDtBm4OyeDmwYuHKnmDpvM6VyyycgYYOHH5U6VZsdnU2QiNw00t3LVuhmVl6WIcs2Tqmpqb1mRuVo80hxCxlDN+ZTN5i12J49GslgVPp6q3XBktbST+0k7bmJiUGeagzu+N56sQcZQbYykFD0/UEsDVH3WabE5+AyV4nHDRMUdaC+YonbChlM3K62jWOHpq/B+xXTzDNMkhuoaobj12oJ5WVzjo0ZjUJv0e0LXCMoOj5EHx2pPKCHEYCYmlz+dR7OFTA73zOwVj8QTEmzykiL6GCluBZ78TN4vbgKCtr0t1WOKoowi2qKNZywY5poZVoolMS+UEV3JTKWqyRHe6rRxR25FL3XkuyGVrw81BA2NRM152HzatWFRr/FIjDtEu/wZXDvAgjZiwQg/V8Xt4BF6Zk0bT2hptXEtGgCTudYwPbOIM1uKy4ikVI2INJYIM/WmPNhuHKatT80xTHoRXZMRi2hBK4BW11EPNJCc+jMDmLMewWlK1AoAkeq6BJM6Mx1HAyF49dpvrCahLcWNkH4ftJw7z+8JVuLJnJRTdthg0dezd03KkEFQ8rTnkmKRhNqQbAzYfdgajSJQpTuIR6PIYvdXVh9+LJZY1XuDYXKP1tdzZ3aGWYsWCxjlp7gJzXwfOWy81BXrU7yxzshVV19j0s45YE3Rrj/TeEueVP6sUzDAg1i4VjIe50EmkfoGrpFi2j2b08Xvf7Orgj3FzjWYjHBVLbqL77Jmavfu3Th37hwkScLo0aNRXV2NUaNGYdmyZRg6dOhVO25nCGGqh3Fmp8PmNVTaPBO5w82jdiTdB8YqyWCvAbW+BlFVs+VbWU02GCZBW4qbhwRHAyH+AmHZrKPVAV5frbXW8HnKGqp9GB2pTi7IBKrqeDQTAB5Jxl7JWtROnP/NBRRzHUAWCtzSwl8osUCwTQQQYGT9DtaH+Iec7d/qtPKElmkD8+C7ST93/eUVOnMGIT3U3pXdZLz0sk0FYYO6D5rZtymuJoSSA1oWYnb8UL0hBNrYRz5mJAiVkGhG4xm3TZF97GVt87p5ygXeXlURD+vmqliUH4t9FNIHF/DUDGbfJYqrPAEgMTNwLGyEbMfCPJqJ/W91OY2oOTXOBRxHqpebo4wItzpEA6z2nYULG+xj4M5J58WHFX9f4/7VBTSKx40w9ca6ixIUJiZ/ld2OxO1YItYwywge5ONt87qRemNixJDV7eQCVLQlAmjfXm0MdUHN158J3/0NM3o4hIhuBrNIxvUy10xrPqOZek5+dIAL8/3u0FIbZE6awH3nKBrl58ueOa0QuEno0J8Plu09FgjxVBiuwSO0AtvQk6/qSVfNBYlhqrtoibAC4vo1Dhn+QpLTDatuknazLNuBEDcXM183dj3YPcXMXRRX+Qc+3NBs+MuZBENzTUKeJV5PMSBn+I3JRFhKrG+p75dN6GSHHVan9nfTVxcQrNWSnKboApTssPH7xJOfxf3V1FArpJCeoJMlwozGAP11ZZElfj7s3ms6WcXrUcqKBGeml/cB0Py4mJCnuJ3wFujm/T43QMnXhENVLxZNsgLo18DSdJ6nyOD1F00mf8XrgpWlrjHVUmSJi2OtIf78mSfDTDh1xg2/zKvNlRKmmpqaEpbb7XbY7fb2NukyJ3S/34ULF+L1119HYWEhXnvtNZSWluLo0aNIT+++cTIjhKkegvQZZUs4giY9/NgeCEK26/lqoICsuqZEL0CqtgS4JkdtDcFi0T7e1oDhS8U0GuFgGBEWUh6OGLMyFpoeiaJFf/kFYzFYSNcsMX+IiEkrFFcRj2hvp2A0hkhM93mKs7QGBEXfrjkUBnRBQbIZ/VL1fkeCYbTo/QpGokZJDxjaj5A+4w/GYgATpmLawxmLG7lrmsMRyPr5WqwqP++wqTxDTB8bqbnFGHxWUiTQinirke+FhYEzP5OWSBSBOCsLEUMzCxM3zYS5MKVaIKmmsHTmzKrvP2TuVziCaJiV6dDHOBQxlWCxIMR8XcL6rFiWEGXrTcIUAFh1B212H1hbAiCr7lcTC/ExYH2hoOFrAzXO96tGYtxnKagftzUSRVS/HlaJIOn3Lc/XFI7Apm+vBIKwRI2PCKALRUFjLNh5RUMRyPrYsuPLFmvCdjyFRiTC2zGtSiQcQThiCPjaOMh8WUs0Bln/2x4MQ7Em5kCyKPFEYSrI+mXkUZNYapJIDM369QrEDIfhZn2MbIEgZKuucQi2QmUTFnNaAabBUY3JBhuL1nCEZ75GoBVyM9P8Eixx/RxZ+L1ZmIqFYAkxYUr/P9xqOA6rKlSWJ03vS3M4ghb9eoZM/msUiUJiWskgc4ZXEQwZ9wGYRlg/70goAqtFe2/EwxE+CYJ+/kqgFbKiTyrCQf5MRIJhBEzPAqBpQsOmd4zChCF9vVnbpgbDUGy6tikU4uPMJhXSRWH5XEsVYmNgvPtkWBDTr62sn4siGc+aVZJg1b0Q5UArFF2Tp6qaQECy1dAatgQQZ+9iU9471XT/s/Nmk8hIMAwrvx8iaGb3dFxFlN1fIe0z3aL/pu4oeByPIqmj6PdtXz1Yh1FeXo6FCxe2u8nChQvx85//vMPd7tixg3/Dfvazn+GBBx4AAKxcuRL5+fl477338OMf/ziZnl82FuqWKyO4mLNnz7a50QQCgUAg6IgzZ84gPz//quw7FAqhX79+qK6uTnpffr8ff/3rX+FwGBrJjjRTtbW1qK3t2JRZWFiIbdu24bbbbsPWrVtx880383Xjx4/H7bffjldeeSXpvl8OQjPVQ+Tm5uLMmTPwer2wWCydb9DNNDU1oW/fvjhz5gxSWLFeQZcQY5ccYvwuHzF2yfFdHj8iQnNzM3Jzc6/aMRwOB06ePIlIJNJ5406w2WwJglRnZGZmIjMzs9N2xcXFsNvtOHLkCBemotEoTp06hYKCgk62vnoIYaqHkCTpqs0uriQpKSnfuZfKtYIYu+QQ43f5iLFLju/q+Pl8vs4bJYnD4fhWQlB3k5KSgjlz5qC8vBx9+/ZFQUEBli5dCgD40Y9+1GP9EsKUQCAQCASCa4alS5fCarVi2rRpCAaDGD9+PP73f/8XaWlpnW98lRDClEAgEAgEgmsGRVGwbNkyLFu2rKe7whG1+QTtYrfbUV5ennQY6/WIGLvkEON3+YixSw4xfoLLRUTzCQQCgUAgECSB0EwJBAKBQCAQJIEQpgQCgUAgEAiSQAhTAoFAIBAIBEkghCmBQCAQCASCJBDCVC/nlVdewcSJE+FyuZCqFwe9mNOnT+Oee+6B2+1GZmYmnnjiiTYZcPfv34/S0lI4nU7k5eVh0aJFbWpEbd68GcXFxXA4HLjxxhvx5ptvtjnW6tWrMWTIENjtdgwZMgTvv//+FTvXq01hYSEsFkvCv+effz6hTXeOZW/kd7/7Hfr16weHw4Hi4mJs3bq1p7vUrSxcuLDNPeb3+/l6IsLChQuRm5sLp9OJyZMn48svv0zYRzgcxoIFC5CZmQm32417770XZ8+eTWhTX1+PadOmwefzwefzYdq0aWhoaOiOU7yibNmyBffccw9yc3NhsViwdu3ahPXdOV5defYFvRgS9GpefPFFev311+npp58mn8/XZn0sFqNhw4bRrbfeSrt376aNGzdSbm4uzZ8/n7dpbGykPn360MMPP0z79++n1atXk9frpWXLlvE2J06cIJfLRWVlZXTw4EF6++23SVEU+q//+i/epqKigmRZpsWLF9OhQ4do8eLFZLVa6fPPP7+qY3ClKCgooEWLFlFVVRX/19zczNd351j2RlatWkWKotDbb79NBw8epLKyMnK73fTVV1/1dNe6jfLycho6dGjCPVZTU8PXL1myhLxeL61evZr2799PDz30EOXk5FBTUxNvM2fOHMrLy6ONGzfS7t276dZbb6WRI0dSLBbjbe68804aNmwYVVRUUEVFBQ0bNozuvvvubj3XK8G6devoZz/7Ga1evZoA0Pvvv5+wvrvGqyvPvqB3I4Sp64SVK1e2K0ytW7eOJEmic+fO8WV/+tOfyG63U2NjIxER/e53vyOfz0ehUIi3+cUvfkG5ubmkqioRET333HM0aNCghH3/+Mc/pgkTJvDfDz74IN15550JbaZOnUoPP/xw0ufXHRQUFNCvfvWrS67vzrHsjYwbN47mzJmTsGzQoEH0/PPP91CPup/y8nIaOXJku+tUVSW/309Llizhy0KhEPl8PnrzzTeJiKihoYEURaFVq1bxNufOnSNJkuijjz4iIqKDBw8SgIRJzLZt2wgAHT58+CqcVfdwsTDVnePVlWdf0LsRZr7rnG3btmHYsGEJxTOnTp2KcDiMXbt28TalpaUJieymTp2Kr7/+GqdOneJt7rjjjoR9T506FTt37kQ0Gu2wTUVFxdU4tavCq6++ioyMDIwaNQqvvPJKghq/O8eytxGJRLBr1642533HHXdcU/fHlaCyshK5ubno168fHn74YZw4cQIAcPLkSVRXVyeMkd1uR2lpKR+jXbt2IRqNJrTJzc3FsGHDeJtt27bB5/Nh/PjxvM2ECRPg8/l61Vh353h15dkX9G6EMHWdU11djT59+iQsS0tLg81mQ3V19SXbsN+dtYnFYqitre2wDdvHd52ysjKsWrUKn376KebPn49f//rXmDdvHl/fnWPZ26itrUU8Hr+m748rwfjx4/H73/8e69evx9tvv43q6mpMnDgRdXV1fBw6GqPq6mrYbLY2NcoubpOdnd3m2NnZ2b1qrLtzvLry7At6N0KYugZpz0n14n87d+7s8v4sFkubZUSUsPziNqQ7TF+JNu0dv7v4NmP51FNPobS0FCNGjMA//uM/4s0338SKFStQV1fH99edY9kb+a7dH93NXXfdhQceeADDhw/H7bffjr/85S8AgHfeeYe3uZwx6uwe7Op+rkW6a7yupzEVtEUUOr4GmT9/Ph5++OEO2xQWFnZpX36/H9u3b09YVl9fj2g0ymdafr+/zeyqpqYGADptY7VakZGR0WGbi2d03UkyYzlhwgQAwLFjx5CRkdGtY9nbyMzMhCzL37n7o6dxu90YPnw4Kisr8YMf/ACApgXJycnhbcxj5Pf7EYlEUF9fn6BtqampwcSJE3mbb775ps2xzp8/36vGmkVBdsd4deXZF/RuhGbqGiQzMxODBg3q8J/D4ejSvkpKSnDgwAFUVVXxZRs2bIDdbkdxcTFvs2XLlgT/oA0bNiA3N5cLGiUlJdi4cWPCvjds2ICxY8dCUZQO27CXVk+QzFju2bMHAPiLujvHsrdhs9lQXFzc5rw3btzYo/dHTxMOh3Ho0CHk5OSgX79+8Pv9CWMUiUSwefNmPkbFxcVQFCWhTVVVFQ4cOMDblJSUoLGxEV988QVvs337djQ2Nvaqse7O8erKsy/o5fSA07ugG/nqq69oz5499POf/5w8Hg/t2bOH9uzZw0P6WUjvlClTaPfu3fTxxx9Tfn5+QkhvQ0MD9enThx555BHav38/rVmzhlJSUtoN53/qqafo4MGDtGLFijbh/J999hnJskxLliyhQ4cO0ZIlS66Z1AgVFRX0+uuv0549e+jEiRP05z//mXJzc+nee+/lbbpzLHsjLDXCihUr6ODBg/Tkk0+S2+2mU6dO9XTXuo1nnnmGNm3aRCdOnKDPP/+c7r77bvJ6vXwMlixZQj6fj9asWUP79++nRx55pN1Q//z8fPr4449p9+7ddNttt7Ub6j9ixAjatm0bbdu2jYYPH35NpkZobm7m7zQA/Bll6TS6a7y68uwLejdCmOrlzJgxgwC0+ffpp5/yNl999RX97d/+LTmdTkpPT6f58+cnhO4TEe3bt4++973vkd1uJ7/fTwsXLuSh/IxNmzbR6NGjyWazUWFhIS1fvrxNf9577z0qKioiRVFo0KBBtHr16qty3leaXbt20fjx48nn85HD4aCioiIqLy+nQCCQ0K47x7I38sYbb1BBQQHZbDYaM2YMbd68uae71K2wPEiKolBubi7df//99OWXX/L1qqpSeXk5+f1+stvtdMstt9D+/fsT9hEMBmn+/PmUnp5OTqeT7r77bjp9+nRCm7q6OnrsscfI6/WS1+ulxx57jOrr67vjFK8on376abvvtxkzZhBR945XV559Qe/FQnRR6mWBQCAQCAQCQZcRPlMCgUAgEAgESSCEKYFAIBAIBIIkEMKUQCAQCAQCQRIIYUogEAgEAoEgCYQwJRAIBAKBQJAEQpgSCAQCgUAgSAIhTAkEAoFAIBAkgRCmBIJuZPLkyXjyySev6jE2bdoEi8WChoaGq3qc3sjF16ewsBC//vWve6w/HcGus8Vi4XX7LpdTp07xfY0aNeqK9E8guJ4QhY4Fgm5kzZo1V7S+3uTJkzFq1KiED/7EiRNRVVUFn893xY5zvbJjxw643e4rus+ZM2eioaEBa9euvSL7O3LkCLKzs5PaR9++fVFVVYVly5bh448/viL9EgiuJ4QwJRBcASKRCGw2W6ft0tPTr3pfbDYb/H7/VT/OtQoRIR6Pw2rt/PWXlZXVDT1KjuzsbKSmpia1D1mW4ff74fF4rkynBILrDGHmEwguYvLkyZg/fz7mz5+P1NRUZGRk4IUXXoC58lJhYSFefvllzJw5Ez6fD7NnzwYArF69GkOHDoXdbkdhYSFee+21Nvs2m5EikQiee+455OXlwe12Y/z48di0aVPCNp999hlKS0vhcrmQlpaGqVOnor6+HjNnzsTmzZvxm9/8hptoTp061a6Zr7N+FRYWYvHixXj88cfh9Xpxww034K233urSeP3+97+Hx+NBZWUlX7ZgwQIMHDgQgUCg0+3D4TCee+459O3bF3a7HQMGDMCKFSv4+s2bN2PcuHGw2+3IycnB888/j1gslrD9E088gezsbDgcDtx8883YsWMHX8/GY/369Rg7dizsdju2bt2KQCCA6dOnw+PxICcnp82YsHExa/0sFgv+4z/+A3/3d38Hl8uFAQMG4L//+7/5+ng8jlmzZqFfv35wOp0oKirCb37zG75+4cKFeOedd/DBBx/wa8au97lz5/DQQw8hLS0NGRkZuO+++3Dq1KlOx+9iJk+ejAULFuDJJ59EWloa+vTpg7feeguBQAD/8A//AK/Xi5tuugkffvjht963QCC4BD1bGlAg+O5RWlpKHo+HysrK6PDhw/Sf//mf5HK56K233uJtCgoKKCUlhZYuXUqVlZVUWVlJO3fuJEmSaNGiRXTkyBFauXIlOZ1OWrlyZcK+y8rK+O9HH32UJk6cSFu2bKFjx47R0qVLyW6309GjR4mIaM+ePWS322nu3Lm0d+9eOnDgAP32t7+l8+fPU0NDA5WUlNDs2bOpqqqKqqqqKBaL8eKvrBBrV/pVUFBA6enp9MYbb1BlZSX94he/IEmS6NChQ10asx/96Ef0N3/zNxSNRunDDz8kRVHoiy++6NK2Dz74IPXt25fWrFlDx48fp48//phWrVpFRERnz54ll8tF8+bNo0OHDtH7779PmZmZVF5ezrd/4oknKDc3l9atW0dffvklzZgxg9LS0qiuro6IjGK4I0aMoA0bNtCxY8eotraW5s6dS/n5+bRhwwbat28f3X333fy6m8flV7/6Ff8NgPLz8+mPf/wjVVZW0hNPPEEej4cfKxKJ0IsvvkhffPEFnThxgt87f/7zn4mIqLm5mR588EG68847+TULh8MUCARowIAB9Pjjj9O+ffvo4MGD9Oijj1JRURGFw+F2x+3i68woLS0lr9dLL730Eh09epReeuklkiSJ7rrrLnrrrbfo6NGjNHfuXMrIyGhTqLu8vJxGjhzZpesmEAgMhDAlEFxEaWkpDR48mFRV5cv+5V/+hQYPHsx/FxQU0A9+8IOE7R599FH6/ve/n7Ds2WefpSFDhiTsm32sjx07RhaLhc6dO5ewzZQpU+inP/0pERE98sgjNGnSpA77av74E7X9yHalXwUFBfT3f//3/LeqqpSdnU3Lly+/5LHNXLhwgfLz82nu3LnUp08fevnll7u03ZEjRwgAbdy4sd31//qv/0pFRUUJ1+KNN94gj8dD8XicWlpaSFEU+sMf/sDXRyIRys3NpV/+8pdEZIzH2rVreZvm5may2WxcaCMiqqurI6fT2akw9cILL/DfLS0tZLFY6MMPP7zkOc6bN48eeOAB/nvGjBl03333JbRZsWJFm/MMh8PkdDpp/fr17e63I2Hq5ptv5r9jsRi53W6aNm0aX1ZVVUUAaNu2bQnbCmFKILg8hJlPIGiHCRMmwGKx8N8lJSWorKxEPB7ny8aOHZuwzaFDhzBp0qSEZZMmTWqzHWP37t0gIgwcOBAej4f/27x5M44fPw4A2Lt3L6ZMmZLUuXS1XyNGjOB/WywW+P1+1NTUdOkYaWlpWLFiBZYvX46bbroJzz//fJe227t3L2RZRmlp6SX7XlJSknAtJk2ahJaWFpw9exbHjx9HNBpNOD9FUTBu3DgcOnQoYV/m63X8+HFEIhGUlJTwZenp6SgqKuq0z+Zxcrvd8Hq9CeP05ptvYuzYscjKyoLH48Hbb7+N06dPd7jPXbt24dixY/B6vfw+SE9PRygU4vfCt8HcR1mWkZGRgeHDh/Nlffr0AYAuX1+BQNAxwgFdILhMLo7yIqKEjz5bdilUVYUsy9i1axdkWU5YxxyBnU5n0v3sar8ujjK0WCxQVbXLx9myZQtkWcbXX3+NQCCAlJSUTrfp7Pw66rvFYkn4u7PtzNero+vSGR2N07vvvounnnoKr732GkpKSuD1erF06VJs3769w32qqori4mL84Q9/aLPucpzg2+ujeRkbm29zfQUCwaURmimBoB0+//zzNr8HDBjQRugxM2TIEPzf//1fwrKKigoMHDiw3e1Gjx6NeDyOmpoa9O/fP+Efi8YbMWIEPvnkk0se02aztav1SqZfl0NFRQV++ctf4n/+53+QkpKCBQsWdGm74cOHQ1VVbN68ud31Q4YMQUVFRYLwU1FRAa/Xi7y8PPTv3x82my3h/KLRKHbu3InBgwdf8rj9+/eHoigJ17m+vh5Hjx7tUr8vxdatWzFx4kTMmzcPo0ePRv/+/dtoltq7ZmPGjEFlZSWys7Pb3AsixYVA8N1HCFMCQTucOXMGTz/9NI4cOYI//elP+O1vf4uysrIOt3nmmWfwySef4KWXXsLRo0fxzjvv4N///d/xk5/8pN32AwcOxGOPPYbp06djzZo1OHnyJHbs2IFXX30V69atAwD89Kc/xY4dOzBv3jzs27cPhw8fxvLly1FbWwtAizbbvn07Tp06hdra2nY1Dd+2X9+W5uZmTJs2DQsWLMBdd92FP/7xj3j33Xfx3nvvdbptYWEhZsyYgccffxxr167FyZMnsWnTJrz77rsAgHnz5uHMmTNYsGABDh8+jA8++ADl5eV4+umnIUkS3G435s6di2effRYfffQRDh48iNmzZ6O1tRWzZs265HE9Hg9mzZqFZ599Fp988gkOHDiAmTNnQpKSeyX2798fO3fuxPr163H06FH827/9W0JkITvnffv24ciRI6itrUU0GsVjjz2GzMxM3Hfffdi6dStOnjyJzZs3o6ysDGfPnk2qTwKB4OojhCmBoB2mT5+OYDCIcePG4Z//+Z+xYMEC/NM//VOH24wZMwbvvvsuVq1ahWHDhuHFF1/EokWLMHPmzEtus3LlSkyfPh3PPPMMioqKcO+992L79u3o27cvAE3g2rBhA/76179i3LhxKCkpwQcffMBzJP3kJz+BLMsYMmQIsrKy2vXNuZx+fRvKysrgdruxePFiAMDQoUPx6quvYs6cOTh37lyn2y9fvhw//OEPMW/ePAwaNAizZ8/mKRXy8vKwbt06fPHFFxg5ciTmzJmDWbNm4YUXXuDbL1myBA888ACmTZuGMWPG4NixY1i/fj3S0tI6PO7SpUtxyy234N5778Xtt9+Om2++GcXFxUmMBDBnzhzcf//9eOihhzB+/HjU1dVh3rx5CW1mz56NoqIi7lf12WefweVyYcuWLbjhhhtw//33Y/DgwXj88ccRDAa7ZC4VCAQ9i4WScR4QCHoh7WUVv1KUlJRgypQpePnll6/4vgXXF5s2bcKtt96K+vr6pJN2MhYuXIi1a9di7969V2R/AsH1gtBMCQTdQDgcxs6dO/Hll19i6NChPd0dQS8iPz8fjzzySFL7OH36NDweD9cuCgSCb4eI5hMIuoEPP/wQ06dPxz333IMf/vCHPd2db8XixYsv+ZH93ve+12Em7a1bt+Kuu+665PqWlpak+3e9Mn78eJ51PtkyMLm5uVwbZbfbk+2aQHDdIcx8AoGgQy5cuIALFy60u87pdCIvL++S2waDwQ79pvr37590/wQCgaCnEcKUQCAQCAQCQRIInymBQCAQCASCJBDClEAgEAgEAkESCGFKIBAIBAKBIAmEMCUQCAQCgUCQBEKYEggEAoFAIEgCIUwJBAKBQCAQJIEQpgQCgUAgEAiSQAhTAoFAIBAIBEnw/wGLF7XE4JsGpQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# We can use xarray's plotting features to get time-labeled plots.\n",
    "hour_to_plot = 17 #UTC (6hrs after simulation start)\n",
    "\n",
    "#This line shows the U winds at 10m from the surface at 18UTC\n",
    "ds[\"U10\"].sel(Time=f\"{case_date:%Y-%m-%d} {hour_to_plot}:00\").plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "id": "fcdda6d1-622c-48b5-bc8e-3ffb034030f7",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_1554/326214781.py:4: UserWarning: More than one latitude coordinate present for variable .\n",
      "  div = mpcalc.divergence(QVAPOR*ds[\"U10\"].sel(Time=f\"{case_date:%Y-%m-%d} {hour_to_plot}:00\"), QVAPOR*ds[\"V10\"].sel(Time=f\"{case_date:%Y-%m-%d} {hour_to_plot}:00\"))\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Horizontal Moisture Divergence: 10m')"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Calculate the divergence of the flow\n",
    "# Multiply by the water vapor (QVAPOR) to get the moisture divergenc\n",
    "\n",
    "div = mpcalc.divergence(QVAPOR*ds[\"U10\"].sel(Time=f\"{case_date:%Y-%m-%d} {hour_to_plot}:00\"), QVAPOR*ds[\"V10\"].sel(Time=f\"{case_date:%Y-%m-%d} {hour_to_plot}:00\"))\n",
    "\n",
    "# start figure and set axis\n",
    "fig, ax = plt.subplots(figsize=(5, 5))\n",
    "\n",
    "# plot divergence and scale by 1e5\n",
    "cf = ax.contourf(ds.y, ds.x, div*1e5 , range(-15, 16, 1), cmap=plt.cm.bwr_r) #* 1e5\n",
    "plt.colorbar(cf, pad=0, aspect=50)\n",
    "#ax.barbs(ds.y.values, ds.x.values, ds.U10.sel(Time=f\"{case_date:%Y-%m-%d} {hour_to_plot}:00\"), ds.V10.sel(Time=f\"{case_date:%Y-%m-%d} {hour_to_plot}:00\"), color='black', length=0.5, alpha=0.5)\n",
    "#ax.set(xlim=(260, 270), ylim=(30, 40))\n",
    "ax.set_title('Horizontal Moisture Divergence: 10m')\n",
    "#ax.set_\n",
    "\n",
    "#plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "880254a3-5401-4224-88e7-9b141fc3a09f",
   "metadata": {},
   "source": [
    "### Moisture convergence at 1km"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "id": "4e57262a-0bc7-4ad2-8805-4a016086379f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(250, 250)"
      ]
     },
     "execution_count": 148,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Load in u, v, and q data\n",
    "#U and V have staggered x and y dimensions. The following unstaggers them to align with QVAPOR \n",
    "U = ds.U.interp(x_stag=ds.x)\n",
    "V = ds.V.interp(y_stag=ds.y)\n",
    "\n",
    "z = 1000 \n",
    "\n",
    "QVAPOR = ds[\"QVAPOR\"].sel(z=z,method='nearest').sel(Time=f\"{case_date:%Y-%m-%d} {hour_to_plot}:00\")\n",
    "QVAPOR.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "id": "1b08a427-7b76-4c0d-a111-1b7eb33c8071",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(250, 250)\n",
      "(250, 250)\n"
     ]
    }
   ],
   "source": [
    "U_at_z = U.sel(z=z,method='nearest').sel(Time=f\"{case_date:%Y-%m-%d} {hour_to_plot}:00\")\n",
    "V_at_z = V.sel(z=z,method='nearest').sel(Time=f\"{case_date:%Y-%m-%d} {hour_to_plot}:00\")\n",
    "\n",
    "print(U_at_z.shape)\n",
    "print(V_at_z.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "id": "5ceb190c-caae-4023-801e-c0c141ea0694",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_1554/3030828318.py:4: UserWarning: More than one longitude coordinate present for variable .\n",
      "  div2 = mpcalc.divergence(QVAPOR*U_at_z, QVAPOR*V_at_z)\n",
      "/tmp/ipykernel_1554/3030828318.py:4: UserWarning: More than one latitude coordinate present for variable .\n",
      "  div2 = mpcalc.divergence(QVAPOR*U_at_z, QVAPOR*V_at_z)\n",
      "/tmp/ipykernel_1554/3030828318.py:4: UserWarning: More than one time coordinate present for variable .\n",
      "  div2 = mpcalc.divergence(QVAPOR*U_at_z, QVAPOR*V_at_z)\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 500x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Calculate the divergence of the flow\n",
    "# Multiply by the water vapor (QVAPOR) to get the moisture divergenc\n",
    "\n",
    "div2 = mpcalc.divergence(QVAPOR*U_at_z, QVAPOR*V_at_z)\n",
    "\n",
    "# start figure and set axis\n",
    "fig2, ax = plt.subplots(figsize=(5, 5))\n",
    "\n",
    "# plot divergence and scale by 1e5\n",
    "cf = ax.contourf(ds.y, ds.x, div2*1e5 , range(-15, 16, 1), cmap=plt.cm.bwr_r) #* 1e5\n",
    "plt.colorbar(cf, pad=0, aspect=50)\n",
    "#ax.barbs(ds.y.values, ds.x.values, ds.U10.sel(Time=f\"{case_date:%Y-%m-%d} {hour_to_plot}:00\"), ds.V10.sel(Time=f\"{case_date:%Y-%m-%d} {hour_to_plot}:00\"), color='black', length=0.5, alpha=0.5)\n",
    "#ax.set(xlim=(260, 270), ylim=(30, 40))\n",
    "ax.set_title('Horizontal Moisture Divergence: 1000m')\n",
    "\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "id": "410e42e9-ed44-490e-93bf-1b0a8435634d",
   "metadata": {},
   "outputs": [
    {
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       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 255GB\n",
       "Dimensions:                    (Time: 91, y: 250, x: 250, soil_layers_stag: 5,\n",
       "                                z: 226, x_stag: 251, y_stag: 251, z_stag: 227,\n",
       "                                force_layers: 751)\n",
       "Coordinates: (12/15)\n",
       "    CLAT                       (y, x) float32 250kB dask.array&lt;chunksize=(125, 125), meta=np.ndarray&gt;\n",
       "    XLAT                       (y, x) float32 250kB dask.array&lt;chunksize=(125, 125), meta=np.ndarray&gt;\n",
       "    XLONG                      (y, x) float32 250kB dask.array&lt;chunksize=(125, 125), meta=np.ndarray&gt;\n",
       "    XTIME                      (Time) datetime64[ns] 728B dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;\n",
       "    XLAT_U                     (y, x_stag) float32 251kB dask.array&lt;chunksize=(125, 126), meta=np.ndarray&gt;\n",
       "    XLONG_U                    (y, x_stag) float32 251kB dask.array&lt;chunksize=(125, 126), meta=np.ndarray&gt;\n",
       "    ...                         ...\n",
       "  * z_stag                     (z_stag) float32 908B 1.0 0.9959 ... 0.002178 0.0\n",
       "  * Time                       (Time) datetime64[ns] 728B 2019-04-04T12:00:00...\n",
       "  * y_stag                     (y_stag) float64 2kB -1.25e+04 ... 1.25e+04\n",
       "  * y                          (y) float64 2kB -1.245e+04 ... 1.245e+04\n",
       "  * x                          (x) float64 2kB -1.245e+04 ... 1.245e+04\n",
       "  * x_stag                     (x_stag) float64 2kB -1.25e+04 ... 1.25e+04\n",
       "Dimensions without coordinates: soil_layers_stag, force_layers\n",
       "Data variables: (12/251)\n",
       "    Times                      (Time) |S19 2kB dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
       "    LU_INDEX                   (Time, y, x) float32 23MB dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;\n",
       "    ZS                         (Time, soil_layers_stag) float32 2kB dask.array&lt;chunksize=(1, 5), meta=np.ndarray&gt;\n",
       "    DZS                        (Time, soil_layers_stag) float32 2kB dask.array&lt;chunksize=(1, 5), meta=np.ndarray&gt;\n",
       "    VAR_SSO                    (Time, y, x) float32 23MB dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;\n",
       "    U                          (Time, z, y, x_stag) float32 5GB dask.array&lt;chunksize=(1, 226, 125, 126), meta=np.ndarray&gt;\n",
       "    ...                         ...\n",
       "    geopotential               (Time, z_stag, y, x) float32 5GB dask.array&lt;chunksize=(1, 227, 125, 125), meta=np.ndarray&gt;\n",
       "    geopotential_height        (Time, z_stag, y, x) float32 5GB dask.array&lt;chunksize=(1, 227, 125, 125), meta=np.ndarray&gt;\n",
       "    wind_east                  (Time, z, y, x) float32 5GB dask.array&lt;chunksize=(1, 226, 125, 125), meta=np.ndarray&gt;\n",
       "    wind_north                 (Time, z, y, x) float32 5GB dask.array&lt;chunksize=(1, 226, 125, 125), meta=np.ndarray&gt;\n",
       "    wind_east_10               (Time, y, x) float32 23MB dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;\n",
       "    wind_north_10              (Time, y, x) float32 23MB dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;\n",
       "Attributes: (12/142)\n",
       "    TITLE:                                  OUTPUT FROM WRF V3.8.1 MODEL\n",
       "    START_DATE:                            2019-04-04_12:00:00\n",
       "    SIMULATION_START_DATE:                 2019-04-04_12:00:00\n",
       "    WEST-EAST_GRID_DIMENSION:              251\n",
       "    SOUTH-NORTH_GRID_DIMENSION:            251\n",
       "    BOTTOM-TOP_GRID_DIMENSION:             227\n",
       "    ...                                    ...\n",
       "    config_aerosol:                        NA\n",
       "    config_forecast_time:                  15.0 h\n",
       "    config_boundary_method:                Periodic\n",
       "    config_microphysics:                   Thompson (mp_physics=8)\n",
       "    config_nickname:                       runlas20190404v1addhm\n",
       "    simulation_origin_host:                cumulus-login2.ccs.ornl.gov</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-b1235d9f-747b-41fe-873d-9fa361bb9c6b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b1235d9f-747b-41fe-873d-9fa361bb9c6b' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>Time</span>: 91</li><li><span class='xr-has-index'>y</span>: 250</li><li><span class='xr-has-index'>x</span>: 250</li><li><span>soil_layers_stag</span>: 5</li><li><span class='xr-has-index'>z</span>: 226</li><li><span class='xr-has-index'>x_stag</span>: 251</li><li><span class='xr-has-index'>y_stag</span>: 251</li><li><span class='xr-has-index'>z_stag</span>: 227</li><li><span>force_layers</span>: 751</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-61031b7c-67eb-4cbf-bcb4-838a01424098' class='xr-section-summary-in' type='checkbox'  checked><label for='section-61031b7c-67eb-4cbf-bcb4-838a01424098' class='xr-section-summary' >Coordinates: <span>(15)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>CLAT</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(125, 125), meta=np.ndarray&gt;</div><input id='attrs-fa6c5d8d-b89d-4c81-8b14-eab6671607a8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fa6c5d8d-b89d-4c81-8b14-eab6671607a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-707694f3-d750-4391-93b1-42615dfae780' class='xr-var-data-in' type='checkbox'><label for='data-707694f3-d750-4391-93b1-42615dfae780' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>COMPUTATIONAL GRID LATITUDE, SOUTH IS NEGATIVE</dd><dt><span>units :</span></dt><dd>degree_north</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 244.14 kiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (250, 250) </td>\n",
       "                        <td> (125, 125) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 4 chunks in 34 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
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       "  <line x1=\"0\" y1=\"60\" x2=\"120\" y2=\"60\" />\n",
       "  <line x1=\"0\" y1=\"120\" x2=\"120\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"60\" y1=\"0\" x2=\"60\" y2=\"120\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >250</text>\n",
       "  <text x=\"140.000000\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,60.000000)\">250</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>XLAT</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(125, 125), meta=np.ndarray&gt;</div><input id='attrs-e8ccce13-56e4-44e7-9df8-42619ce9ec6d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e8ccce13-56e4-44e7-9df8-42619ce9ec6d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6894f62d-a96e-44e1-856f-95948ceae84b' class='xr-var-data-in' type='checkbox'><label for='data-6894f62d-a96e-44e1-856f-95948ceae84b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>LATITUDE, SOUTH IS NEGATIVE</dd><dt><span>units :</span></dt><dd>degree_north</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 244.14 kiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (250, 250) </td>\n",
       "                        <td> (125, 125) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 4 chunks in 34 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
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       "  <line x1=\"0\" y1=\"120\" x2=\"120\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"60\" y1=\"0\" x2=\"60\" y2=\"120\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >250</text>\n",
       "  <text x=\"140.000000\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,60.000000)\">250</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>XLONG</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(125, 125), meta=np.ndarray&gt;</div><input id='attrs-9b6b2141-02ec-48df-86c4-d8cd3d82a2a5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9b6b2141-02ec-48df-86c4-d8cd3d82a2a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e23c1222-c02c-4231-b00e-48175bf096cd' class='xr-var-data-in' type='checkbox'><label for='data-e23c1222-c02c-4231-b00e-48175bf096cd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>LONGITUDE, WEST IS NEGATIVE</dd><dt><span>units :</span></dt><dd>degree_east</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
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       "                        <th> Array </th>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "                        <td> 244.14 kiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "        <td>\n",
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       "                <tbody>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "                        <td> 61.52 kiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (125, 126) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>XLONG_U</span></div><div class='xr-var-dims'>(y, x_stag)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(125, 126), meta=np.ndarray&gt;</div><input id='attrs-58167aaf-7381-4cb8-a614-a41b4803de8f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-58167aaf-7381-4cb8-a614-a41b4803de8f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4412032e-f22d-4da4-83fe-c4546c12ecfb' class='xr-var-data-in' type='checkbox'><label for='data-4412032e-f22d-4da4-83fe-c4546c12ecfb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>LONGITUDE, WEST IS NEGATIVE</dd><dt><span>units :</span></dt><dd>degree_east</dd><dt><span>stagger :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>XLONG_V</span></div><div class='xr-var-dims'>(y_stag, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(126, 125), meta=np.ndarray&gt;</div><input id='attrs-ff24c16e-2f5c-444d-906f-13aadd4802c8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ff24c16e-2f5c-444d-906f-13aadd4802c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1431b77c-64af-4e49-ba83-4fe1806503b7' class='xr-var-data-in' type='checkbox'><label for='data-1431b77c-64af-4e49-ba83-4fe1806503b7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>LONGITUDE, WEST IS NEGATIVE</dd><dt><span>units :</span></dt><dd>degree_east</dd><dt><span>stagger :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 245.12 kiB </td>\n",
       "                        <td> 61.52 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (251, 250) </td>\n",
       "                        <td> (126, 125) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 4 chunks in 34 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"169\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
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       "\n",
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       "  <polygon points=\"0.0,0.0 119.5219123505976,0.0 119.5219123505976,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"59.760956\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >250</text>\n",
       "  <text x=\"139.521912\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,139.521912,60.000000)\">251</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>z</span></div><div class='xr-var-dims'>(z)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.9979 0.9938 ... 0.005743 0.001089</div><input id='attrs-d336e1b0-7857-42ed-92e2-3ed46dda2593' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d336e1b0-7857-42ed-92e2-3ed46dda2593' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-794a9949-603e-46dd-b432-7909a729c3ac' class='xr-var-data-in' type='checkbox'><label for='data-794a9949-603e-46dd-b432-7909a729c3ac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>eta values on half (mass) levels</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>standard_name :</span></dt><dd>atmosphere_sigma_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([0.997944, 0.993847, 0.989777, ..., 0.01304 , 0.005743, 0.001089],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>z_stag</span></div><div class='xr-var-dims'>(z_stag)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.0 0.9959 0.9918 ... 0.002178 0.0</div><input id='attrs-e47dc4b3-a4a4-48d0-8487-9c5419140c6f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e47dc4b3-a4a4-48d0-8487-9c5419140c6f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-257fc58a-f780-427a-8882-a004d189f07d' class='xr-var-data-in' type='checkbox'><label for='data-257fc58a-f780-427a-8882-a004d189f07d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>eta values on full (w) levels</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd>Z</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>c_grid_axis_shift :</span></dt><dd>0.5</dd><dt><span>standard_name :</span></dt><dd>atmosphere_sigma_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1.      , 0.995887, 0.991808, ..., 0.009308, 0.002178, 0.      ],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Time</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-04-04T12:00:00 ... 2019-04-...</div><input id='attrs-778a2f09-9f41-477d-9a9b-ba7659e98294' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-778a2f09-9f41-477d-9a9b-ba7659e98294' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3f26b02-e1a7-41f0-b9fd-5ff7caee8f04' class='xr-var-data-in' type='checkbox'><label for='data-b3f26b02-e1a7-41f0-b9fd-5ff7caee8f04' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>minutes since 2019-04-04 12:00:00</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-04-04T12:00:00.000000000&#x27;, &#x27;2019-04-04T12:10:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T12:20:00.000000000&#x27;, &#x27;2019-04-04T12:30:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T12:40:00.000000000&#x27;, &#x27;2019-04-04T12:50:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T13:00:00.000000000&#x27;, &#x27;2019-04-04T13:10:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T13:20:00.000000000&#x27;, &#x27;2019-04-04T13:30:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T13:40:00.000000000&#x27;, &#x27;2019-04-04T13:50:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T14:00:00.000000000&#x27;, &#x27;2019-04-04T14:10:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T14:20:00.000000000&#x27;, &#x27;2019-04-04T14:30:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T14:40:00.000000000&#x27;, &#x27;2019-04-04T14:50:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T15:00:00.000000000&#x27;, &#x27;2019-04-04T15:10:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T15:20:00.000000000&#x27;, &#x27;2019-04-04T15:30:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T15:40:00.000000000&#x27;, &#x27;2019-04-04T15:50:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T16:00:00.000000000&#x27;, &#x27;2019-04-04T16:10:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T16:20:00.000000000&#x27;, &#x27;2019-04-04T16:30:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T16:40:00.000000000&#x27;, &#x27;2019-04-04T16:50:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T17:00:00.000000000&#x27;, &#x27;2019-04-04T17:10:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T17:20:00.000000000&#x27;, &#x27;2019-04-04T17:30:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T17:40:00.000000000&#x27;, &#x27;2019-04-04T17:50:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T18:00:00.000000000&#x27;, &#x27;2019-04-04T18:10:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T18:20:00.000000000&#x27;, &#x27;2019-04-04T18:30:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T18:40:00.000000000&#x27;, &#x27;2019-04-04T18:50:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T19:00:00.000000000&#x27;, &#x27;2019-04-04T19:10:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T19:20:00.000000000&#x27;, &#x27;2019-04-04T19:30:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T19:40:00.000000000&#x27;, &#x27;2019-04-04T19:50:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T20:00:00.000000000&#x27;, &#x27;2019-04-04T20:10:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T20:20:00.000000000&#x27;, &#x27;2019-04-04T20:30:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T20:40:00.000000000&#x27;, &#x27;2019-04-04T20:50:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T21:00:00.000000000&#x27;, &#x27;2019-04-04T21:10:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T21:20:00.000000000&#x27;, &#x27;2019-04-04T21:30:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T21:40:00.000000000&#x27;, &#x27;2019-04-04T21:50:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T22:00:00.000000000&#x27;, &#x27;2019-04-04T22:10:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T22:20:00.000000000&#x27;, &#x27;2019-04-04T22:30:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T22:40:00.000000000&#x27;, &#x27;2019-04-04T22:50:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T23:00:00.000000000&#x27;, &#x27;2019-04-04T23:10:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T23:20:00.000000000&#x27;, &#x27;2019-04-04T23:30:00.000000000&#x27;,\n",
       "       &#x27;2019-04-04T23:40:00.000000000&#x27;, &#x27;2019-04-04T23:50:00.000000000&#x27;,\n",
       "       &#x27;2019-04-05T00:00:00.000000000&#x27;, &#x27;2019-04-05T00:10:00.000000000&#x27;,\n",
       "       &#x27;2019-04-05T00:20:00.000000000&#x27;, &#x27;2019-04-05T00:30:00.000000000&#x27;,\n",
       "       &#x27;2019-04-05T00:40:00.000000000&#x27;, &#x27;2019-04-05T00:50:00.000000000&#x27;,\n",
       "       &#x27;2019-04-05T01:00:00.000000000&#x27;, &#x27;2019-04-05T01:10:00.000000000&#x27;,\n",
       "       &#x27;2019-04-05T01:20:00.000000000&#x27;, &#x27;2019-04-05T01:30:00.000000000&#x27;,\n",
       "       &#x27;2019-04-05T01:40:00.000000000&#x27;, &#x27;2019-04-05T01:50:00.000000000&#x27;,\n",
       "       &#x27;2019-04-05T02:00:00.000000000&#x27;, &#x27;2019-04-05T02:10:00.000000000&#x27;,\n",
       "       &#x27;2019-04-05T02:20:00.000000000&#x27;, &#x27;2019-04-05T02:30:00.000000000&#x27;,\n",
       "       &#x27;2019-04-05T02:40:00.000000000&#x27;, &#x27;2019-04-05T02:50:00.000000000&#x27;,\n",
       "       &#x27;2019-04-05T03:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y_stag</span></div><div class='xr-var-dims'>(y_stag)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.25e+04 -1.24e+04 ... 1.25e+04</div><input id='attrs-b744b6e1-1b03-4169-bdfe-441d27b04271' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b744b6e1-1b03-4169-bdfe-441d27b04271' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d998051b-27fd-4850-9cac-39e7846ddd8a' class='xr-var-data-in' type='checkbox'><label for='data-d998051b-27fd-4850-9cac-39e7846ddd8a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>c_grid_axis_shift :</span></dt><dd>0.5</dd></dl></div><div class='xr-var-data'><pre>array([-12500., -12400., -12300., ...,  12300.,  12400.,  12500.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.245e+04 -1.235e+04 ... 1.245e+04</div><input id='attrs-dce45720-5c59-4b71-b46f-18b75f3dcdb2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dce45720-5c59-4b71-b46f-18b75f3dcdb2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a558a188-6db9-4b2e-9763-8a253258cc98' class='xr-var-data-in' type='checkbox'><label for='data-a558a188-6db9-4b2e-9763-8a253258cc98' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-12450., -12350., -12250., ...,  12250.,  12350.,  12450.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.245e+04 -1.235e+04 ... 1.245e+04</div><input id='attrs-83316ca5-7c90-4773-b5c9-0a63d9b77199' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-83316ca5-7c90-4773-b5c9-0a63d9b77199' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1f639921-ee98-41b8-bd10-06b323103e08' class='xr-var-data-in' type='checkbox'><label for='data-1f639921-ee98-41b8-bd10-06b323103e08' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([-12450., -12350., -12250., ...,  12250.,  12350.,  12450.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x_stag</span></div><div class='xr-var-dims'>(x_stag)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.25e+04 -1.24e+04 ... 1.25e+04</div><input id='attrs-318335e8-e1a2-4e61-94e0-6fad4d33cc03' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-318335e8-e1a2-4e61-94e0-6fad4d33cc03' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2b736a2f-7c1f-4b52-a077-3868f6c19067' class='xr-var-data-in' type='checkbox'><label for='data-2b736a2f-7c1f-4b52-a077-3868f6c19067' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>c_grid_axis_shift :</span></dt><dd>0.5</dd></dl></div><div class='xr-var-data'><pre>array([-12500., -12400., -12300., ...,  12300.,  12400.,  12500.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2ec97db3-6eb7-49d8-8bd4-21f364a99cd9' class='xr-section-summary-in' type='checkbox'  ><label for='section-2ec97db3-6eb7-49d8-8bd4-21f364a99cd9' class='xr-section-summary' >Data variables: <span>(251)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>Times</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>|S19</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-227ba399-94aa-44be-bb64-f0fadf5dea46' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-227ba399-94aa-44be-bb64-f0fadf5dea46' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a94ac3f4-18a2-4295-a70d-9890d7be2250' class='xr-var-data-in' type='checkbox'><label for='data-a94ac3f4-18a2-4295-a70d-9890d7be2250' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 1.69 kiB </td>\n",
       "                        <td> 19 B </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (1,) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
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       "                        <td colspan=\"2\"> |S19 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>LU_INDEX</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-5824a1ae-ae20-4671-87ce-3dd98469004e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5824a1ae-ae20-4671-87ce-3dd98469004e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a9d4e744-689a-41ff-b7a8-6d147558f206' class='xr-var-data-in' type='checkbox'><label for='data-a9d4e744-689a-41ff-b7a8-6d147558f206' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>LAND USE CATEGORY</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "                        <td> 21.70 MiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ZS</span></div><div class='xr-var-dims'>(Time, soil_layers_stag)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 5), meta=np.ndarray&gt;</div><input id='attrs-f7e2dda3-7e5c-4b45-a3d3-b0b8aef590a6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f7e2dda3-7e5c-4b45-a3d3-b0b8aef590a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-20a7f12f-3d5e-43e0-aa91-0f5d60269692' class='xr-var-data-in' type='checkbox'><label for='data-20a7f12f-3d5e-43e0-aa91-0f5d60269692' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>DEPTHS OF CENTERS OF SOIL LAYERS</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>stagger :</span></dt><dd>Z</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <th> Shape </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VAR_SSO</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-e5f502a5-a337-4017-98fc-4dde16fb0869' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e5f502a5-a337-4017-98fc-4dde16fb0869' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-07526440-7ca2-4f88-b40b-959d229f1c4b' class='xr-var-data-in' type='checkbox'><label for='data-07526440-7ca2-4f88-b40b-959d229f1c4b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>Variance of Subgrid Scale Orography MSL</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.70 MiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
       "                    </tr>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 250, 250) </td>\n",
       "                        <td> (1, 125, 125) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 364 chunks in 33 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>U</span></div><div class='xr-var-dims'>(Time, z, y, x_stag)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226, 125, 126), meta=np.ndarray&gt;</div><input id='attrs-67a191b6-825b-473d-8793-c30c1e9764f4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-67a191b6-825b-473d-8793-c30c1e9764f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a68d174-2835-4f76-a0d5-580b87ffd612' class='xr-var-data-in' type='checkbox'><label for='data-3a68d174-2835-4f76-a0d5-580b87ffd612' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>x-wind component</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>stagger :</span></dt><dd>X</dd><dt><span>standard_name :</span></dt><dd>x_wind</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "                        <th> Chunk </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.81 GiB </td>\n",
       "                        <td> 13.58 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 226, 250, 251) </td>\n",
       "                        <td> (1, 226, 125, 126) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                        <th> Chunk </th>\n",
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       "                        <th> Bytes </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>LH_FORCE</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-030acb6c-b610-427c-8770-62463f6b1344' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-030acb6c-b610-427c-8770-62463f6b1344' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-00d92932-891c-40b4-8760-0b649806bb34' class='xr-var-data-in' type='checkbox'><label for='data-00d92932-891c-40b4-8760-0b649806bb34' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>SCM ideal surface latent heat flux</dd><dt><span>units :</span></dt><dd>W m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HFX_FORCE_TEND</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-8905de28-928e-43c0-b442-30535caf84ce' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8905de28-928e-43c0-b442-30535caf84ce' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ad1ea624-0c00-4277-ab81-8d657a1f5ee2' class='xr-var-data-in' type='checkbox'><label for='data-ad1ea624-0c00-4277-ab81-8d657a1f5ee2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>SCM ideal surface sensible heat flux tendency</dd><dt><span>units :</span></dt><dd>W m-2 s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <th> Data type </th>\n",
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       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
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       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
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       "                        <td> 13.47 MiB </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>FNM</span></div><div class='xr-var-dims'>(Time, z)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226), meta=np.ndarray&gt;</div><input id='attrs-d61c2f47-cc7b-45ec-8392-9abbb0f7a4ce' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d61c2f47-cc7b-45ec-8392-9abbb0f7a4ce' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2d86c4de-b6cd-4ad0-a902-ba947496e763' class='xr-var-data-in' type='checkbox'><label for='data-2d86c4de-b6cd-4ad0-a902-ba947496e763' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>upper weight for vertical stretching</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <th> Shape </th>\n",
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       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                    <tr>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>RDN</span></div><div class='xr-var-dims'>(Time, z)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226), meta=np.ndarray&gt;</div><input id='attrs-8b4749ce-bec5-4916-a19b-330ada589653' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8b4749ce-bec5-4916-a19b-330ada589653' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-936ed1d8-595b-477b-b69a-0bf8021bc158' class='xr-var-data-in' type='checkbox'><label for='data-936ed1d8-595b-477b-b69a-0bf8021bc158' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>inverse d(eta) values between half (mass) levels</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 80.34 kiB </td>\n",
       "                        <td> 904 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 226) </td>\n",
       "                        <td> (1, 226) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DNW</span></div><div class='xr-var-dims'>(Time, z)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226), meta=np.ndarray&gt;</div><input id='attrs-9e73a5f6-b051-4155-a499-c7244b3679be' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9e73a5f6-b051-4155-a499-c7244b3679be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f69469c5-7eb5-4a3b-a44a-5fed6d04a79e' class='xr-var-data-in' type='checkbox'><label for='data-f69469c5-7eb5-4a3b-a44a-5fed6d04a79e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>d(eta) values between full (w) levels</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 80.34 kiB </td>\n",
       "                        <td> 904 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 226) </td>\n",
       "                        <td> (1, 226) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DN</span></div><div class='xr-var-dims'>(Time, z)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226), meta=np.ndarray&gt;</div><input id='attrs-797f1c75-c2da-48bb-a949-f41c9f84a6a2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-797f1c75-c2da-48bb-a949-f41c9f84a6a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e15bb267-dc38-4777-9a63-1864f951b14b' class='xr-var-data-in' type='checkbox'><label for='data-e15bb267-dc38-4777-9a63-1864f951b14b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>d(eta) values between half (mass) levels</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 80.34 kiB </td>\n",
       "                        <td> 904 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 226) </td>\n",
       "                        <td> (1, 226) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CFN</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-9dc56eef-d38b-46a5-8f08-13ecf7495356' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9dc56eef-d38b-46a5-8f08-13ecf7495356' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-70b94919-8a7d-45ae-8c5f-38945c5604d8' class='xr-var-data-in' type='checkbox'><label for='data-70b94919-8a7d-45ae-8c5f-38945c5604d8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>extrapolation constant</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (6,) </td>\n",
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       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CFN1</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-5ff6835d-6658-4b0c-b6d1-3fa5ac200746' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ff6835d-6658-4b0c-b6d1-3fa5ac200746' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-31baa890-ce40-482b-baf5-77e4cce7c674' class='xr-var-data-in' type='checkbox'><label for='data-31baa890-ce40-482b-baf5-77e4cce7c674' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>extrapolation constant</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (6,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>THIS_IS_AN_IDEAL_RUN</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-f1b0f086-8dc2-4bfe-ad08-1770e8344054' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f1b0f086-8dc2-4bfe-ad08-1770e8344054' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e22d6f28-2d11-48f9-ad3d-1fe302f14648' class='xr-var-data-in' type='checkbox'><label for='data-e22d6f28-2d11-48f9-ad3d-1fe302f14648' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>106</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>T/F flag: this is an ARW ideal simulation</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
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       "                        <td> 24 B </td>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
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       "                        <td colspan=\"2\"> int32 numpy.ndarray </td>\n",
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       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
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       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.70 MiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
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       "                        <th> Shape </th>\n",
       "                        <td> (91, 250, 250) </td>\n",
       "                        <td> (1, 125, 125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>T2</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-e1882f14-d9cf-4103-83c9-0bda14d86e97' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e1882f14-d9cf-4103-83c9-0bda14d86e97' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-25c50a02-dde3-42cd-a15a-22f793684f60' class='xr-var-data-in' type='checkbox'><label for='data-25c50a02-dde3-42cd-a15a-22f793684f60' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>TEMP at 2 M</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>stagger :</span></dt><dd></dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>long_name :</span></dt><dd>air_temperature_at_2m_agl</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.70 MiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "                        <td> (1, 125, 125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TH2</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-18f69bae-ab56-4e08-84b3-c4fafa75461b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-18f69bae-ab56-4e08-84b3-c4fafa75461b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-52af06da-2de9-4783-8f14-0c39b44ce170' class='xr-var-data-in' type='checkbox'><label for='data-52af06da-2de9-4783-8f14-0c39b44ce170' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>POT TEMP at 2 M</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>stagger :</span></dt><dd></dd><dt><span>standard_name :</span></dt><dd>air_potential_temperature</dd><dt><span>long_name :</span></dt><dd>air_potential_temperature_at_2m_agl</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>U10</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-856bb84f-c429-4b91-94f5-1cb7de2a5b65' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-856bb84f-c429-4b91-94f5-1cb7de2a5b65' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-38443efa-c5a3-4c7f-98b4-db8aaab84802' class='xr-var-data-in' type='checkbox'><label for='data-38443efa-c5a3-4c7f-98b4-db8aaab84802' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>U at 10 M</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>stagger :</span></dt><dd></dd><dt><span>standard_name :</span></dt><dd>x_wind</dd><dt><span>long_name :</span></dt><dd>x_wind_at_10m_agl</dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>RDX</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-d0288867-28bc-4ef7-951b-5036b4b1869b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d0288867-28bc-4ef7-951b-5036b4b1869b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-700291d2-04ba-4d72-876c-1819ee39d014' class='xr-var-data-in' type='checkbox'><label for='data-700291d2-04ba-4d72-876c-1819ee39d014' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>INVERSE X GRID LENGTH</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
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       "                <tbody>\n",
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       "                        <td> 24 B </td>\n",
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       "                        <th> Shape </th>\n",
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       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>RESM</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-8ce1e5ec-f483-4371-bb88-916df7110f19' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8ce1e5ec-f483-4371-bb88-916df7110f19' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0e6f17d1-34b3-4f24-9be8-b2fc9759b20f' class='xr-var-data-in' type='checkbox'><label for='data-0e6f17d1-34b3-4f24-9be8-b2fc9759b20f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>TIME WEIGHT CONSTANT FOR SMALL STEPS</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (6,) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ZETATOP</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-153d78c7-40d3-4bac-aec5-31017e838266' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-153d78c7-40d3-4bac-aec5-31017e838266' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a97e713c-906b-447a-8fbf-b057c46b37e1' class='xr-var-data-in' type='checkbox'><label for='data-a97e713c-906b-447a-8fbf-b057c46b37e1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>ZETA AT MODEL TOP</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (6,) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CF1</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-f010c648-0abc-4104-8450-385ca4d1317a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f010c648-0abc-4104-8450-385ca4d1317a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b9f7268a-a185-4caa-b78b-f842ee508053' class='xr-var-data-in' type='checkbox'><label for='data-b9f7268a-a185-4caa-b78b-f842ee508053' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>2nd order extrapolation constant</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (6,) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CF2</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-c34ec0a6-e6ac-4efd-a083-1a316bb5883b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c34ec0a6-e6ac-4efd-a083-1a316bb5883b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5385eaa5-4c47-4f44-bcdc-3da4a044f670' class='xr-var-data-in' type='checkbox'><label for='data-5385eaa5-4c47-4f44-bcdc-3da4a044f670' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>2nd order extrapolation constant</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (6,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CF3</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-45439e26-dfa8-4106-9f03-6e8828e1a401' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-45439e26-dfa8-4106-9f03-6e8828e1a401' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f57e81e7-859c-40c7-91da-a709cda87e3b' class='xr-var-data-in' type='checkbox'><label for='data-f57e81e7-859c-40c7-91da-a709cda87e3b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>2nd order extrapolation constant</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (6,) </td>\n",
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       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ITIMESTEP</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-b41f1abf-8eb8-4f6b-b04b-1f0f1d7dfb2b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b41f1abf-8eb8-4f6b-b04b-1f0f1d7dfb2b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-591d52a4-79b9-4a9e-b0de-16022c239a49' class='xr-var-data-in' type='checkbox'><label for='data-591d52a4-79b9-4a9e-b0de-16022c239a49' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>106</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd></dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
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       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>QVAPOR</span></div><div class='xr-var-dims'>(Time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-e19f896e-5939-41b6-89a6-00b6e1ce8f5b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e19f896e-5939-41b6-89a6-00b6e1ce8f5b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2fbff558-0b91-442a-871d-4b467bfa10db' class='xr-var-data-in' type='checkbox'><label for='data-2fbff558-0b91-442a-871d-4b467bfa10db' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>Water vapor mixing ratio</dd><dt><span>units :</span></dt><dd>kg kg-1</dd><dt><span>stagger :</span></dt><dd></dd><dt><span>standard_name :</span></dt><dd>humidity_mixing_ratio</dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>QRAIN</span></div><div class='xr-var-dims'>(Time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-b46bb4fb-d7ba-4685-bbb4-0106c8e7c6ef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b46bb4fb-d7ba-4685-bbb4-0106c8e7c6ef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-341046db-6a80-4f11-9101-00bfb05a7cf7' class='xr-var-data-in' type='checkbox'><label for='data-341046db-6a80-4f11-9101-00bfb05a7cf7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>Rain water mixing ratio</dd><dt><span>units :</span></dt><dd>kg kg-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
       "                        <td> 13.47 MiB </td>\n",
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       "                        <th> Dask graph </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>QICE</span></div><div class='xr-var-dims'>(Time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-919f20e8-1d83-43e7-b5b0-661d111fb490' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-919f20e8-1d83-43e7-b5b0-661d111fb490' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-10298004-013b-4936-874e-e04d984608d1' class='xr-var-data-in' type='checkbox'><label for='data-10298004-013b-4936-874e-e04d984608d1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>Ice mixing ratio</dd><dt><span>units :</span></dt><dd>kg kg-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <th> Chunk </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
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       "                        <td> 4.79 GiB </td>\n",
       "                        <td> 13.47 MiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
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       "                    <tr>\n",
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       "        <td>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.70 MiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <th> Dask graph </th>\n",
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       "                        <th> Data type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SHDMIN</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-4143ebc2-0cb3-405c-a99f-5f00279da2da' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4143ebc2-0cb3-405c-a99f-5f00279da2da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-62bccecc-7f20-4963-ac99-71507cab5f75' class='xr-var-data-in' type='checkbox'><label for='data-62bccecc-7f20-4963-ac99-71507cab5f75' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>ANNUAL MIN VEG FRACTION</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "                        <th> Array </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 108.48 MiB </td>\n",
       "                        <td> 305.18 kiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                        <th> Data type </th>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 108.48 MiB </td>\n",
       "                        <td> 305.18 kiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SH2O</span></div><div class='xr-var-dims'>(Time, soil_layers_stag, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 5, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-855efe11-5c4e-4081-99b8-55876c6d204a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-855efe11-5c4e-4081-99b8-55876c6d204a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-906c60c3-2c2e-415d-a152-f8e75666abd0' class='xr-var-data-in' type='checkbox'><label for='data-906c60c3-2c2e-415d-a152-f8e75666abd0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>SOIL LIQUID WATER</dd><dt><span>units :</span></dt><dd>m3 m-3</dd><dt><span>stagger :</span></dt><dd>Z</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "                        <td> 108.48 MiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SEAICE</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-42f30968-0884-42c6-9c35-8555f8495a74' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-42f30968-0884-42c6-9c35-8555f8495a74' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8bba6c20-d583-49ad-a413-5b12c0e98455' class='xr-var-data-in' type='checkbox'><label for='data-8bba6c20-d583-49ad-a413-5b12c0e98455' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>SEA ICE FLAG</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.70 MiB </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SFROFF</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-36a6bd1c-f2f7-45a2-8b0d-f4eea1cca6e3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-36a6bd1c-f2f7-45a2-8b0d-f4eea1cca6e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4220e151-7322-4042-8a7a-b595269ac927' class='xr-var-data-in' type='checkbox'><label for='data-4220e151-7322-4042-8a7a-b595269ac927' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>SURFACE RUNOFF</dd><dt><span>units :</span></dt><dd>mm</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VEGFRA</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-f3c4a8a0-6430-4b97-81a9-e0b7ab22b2f1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f3c4a8a0-6430-4b97-81a9-e0b7ab22b2f1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7ce196d8-70ad-45e7-adf1-ade0730a1f90' class='xr-var-data-in' type='checkbox'><label for='data-7ce196d8-70ad-45e7-adf1-ade0730a1f90' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>VEGETATION FRACTION</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd><dt><span>standard_name :</span></dt><dd>vegetation_area_fraction</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "                        <td> 21.70 MiB </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>GRDFLX</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-675251df-a8b4-4034-9a88-ec0a284da461' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-675251df-a8b4-4034-9a88-ec0a284da461' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb8eba8e-fcfd-4f33-88b8-174ca798c5c2' class='xr-var-data-in' type='checkbox'><label for='data-fb8eba8e-fcfd-4f33-88b8-174ca798c5c2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>GROUND HEAT FLUX</dd><dt><span>units :</span></dt><dd>W m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <td> 21.70 MiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 250, 250) </td>\n",
       "                        <td> (1, 125, 125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ACGRDFLX</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-e624829b-ed45-407b-b6c7-bf4af77f22a3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e624829b-ed45-407b-b6c7-bf4af77f22a3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-52aa8926-1d52-42db-90ec-f45cdc3c6ad2' class='xr-var-data-in' type='checkbox'><label for='data-52aa8926-1d52-42db-90ec-f45cdc3c6ad2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>ACCUMULATED GROUND HEAT FLUX</dd><dt><span>units :</span></dt><dd>J m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "                        <th> Dask graph </th>\n",
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       "                        <td> 21.70 MiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
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       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.70 MiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 250, 250) </td>\n",
       "                        <td> (1, 125, 125) </td>\n",
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       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.70 MiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 250, 250) </td>\n",
       "                        <td> (1, 125, 125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "                        <td> 21.70 MiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MAPFAC_U</span></div><div class='xr-var-dims'>(Time, y, x_stag)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 126), meta=np.ndarray&gt;</div><input id='attrs-e27b2a11-d871-4224-bda2-b3c73e1f7dc2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e27b2a11-d871-4224-bda2-b3c73e1f7dc2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-91c5f9df-d809-4aee-9e93-3a0ff97a8350' class='xr-var-data-in' type='checkbox'><label for='data-91c5f9df-d809-4aee-9e93-3a0ff97a8350' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>Map scale factor on u-grid</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
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       "                    <tr>\n",
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       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
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       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.78 MiB </td>\n",
       "                        <td> 61.52 kiB </td>\n",
       "                    </tr>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1, 125, 126) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MAPFAC_V</span></div><div class='xr-var-dims'>(Time, y_stag, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 126, 125), meta=np.ndarray&gt;</div><input id='attrs-cd7d51d2-82b8-494c-81a1-690e4b5dd8c9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cd7d51d2-82b8-494c-81a1-690e4b5dd8c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-456e4f46-73ce-4e71-9cc3-9488e5b2c2d3' class='xr-var-data-in' type='checkbox'><label for='data-456e4f46-73ce-4e71-9cc3-9488e5b2c2d3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>Map scale factor on v-grid</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1, 126, 125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MAPFAC_MX</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-ad6f9daf-587f-41af-bfee-ce296e10b38c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ad6f9daf-587f-41af-bfee-ce296e10b38c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-19de5704-9eaf-4e98-9bc9-0adc47b0c71d' class='xr-var-data-in' type='checkbox'><label for='data-19de5704-9eaf-4e98-9bc9-0adc47b0c71d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>Map scale factor on mass grid, x direction</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MAPFAC_UY</span></div><div class='xr-var-dims'>(Time, y, x_stag)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 126), meta=np.ndarray&gt;</div><input id='attrs-4018f6b1-c2a3-4430-918c-b2c8668998ea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4018f6b1-c2a3-4430-918c-b2c8668998ea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-261608bb-8b86-4c3a-bb50-754a871ade8c' class='xr-var-data-in' type='checkbox'><label for='data-261608bb-8b86-4c3a-bb50-754a871ade8c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>Map scale factor on u-grid, y direction</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
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       "                    <tr>\n",
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       "                        <th> Chunk </th>\n",
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       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.78 MiB </td>\n",
       "                        <td> 61.52 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1, 125, 126) </td>\n",
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       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MAPFAC_VX</span></div><div class='xr-var-dims'>(Time, y_stag, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 126, 125), meta=np.ndarray&gt;</div><input id='attrs-aa0e2d7e-1802-4a61-a063-62b797db670f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aa0e2d7e-1802-4a61-a063-62b797db670f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-13f11698-218b-47fa-adf7-0677b4ab18d0' class='xr-var-data-in' type='checkbox'><label for='data-13f11698-218b-47fa-adf7-0677b4ab18d0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>Map scale factor on v-grid, x direction</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.78 MiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1, 126, 125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.78 MiB </td>\n",
       "                        <td> 61.52 kiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                        <th> Data type </th>\n",
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       "                        <td> 21.78 MiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1, 126, 125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.70 MiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1, 125, 125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                        <th> Data type </th>\n",
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       "                        <th> Bytes </th>\n",
       "                        <td> 21.70 MiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
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       "                        <th> Data type </th>\n",
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       "                        <th> Array </th>\n",
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       "                <tbody>\n",
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       "                        <td> 21.70 MiB </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HGT</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-db88770c-ab27-4b14-b75d-ef55cdaace1f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-db88770c-ab27-4b14-b75d-ef55cdaace1f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bae5593b-493a-49ec-bdf2-3457eaa8fd18' class='xr-var-data-in' type='checkbox'><label for='data-bae5593b-493a-49ec-bdf2-3457eaa8fd18' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>Terrain Height</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>stagger :</span></dt><dd></dd><dt><span>standard_name :</span></dt><dd>surface_altitude</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1, 125, 125) </td>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (6,) </td>\n",
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       "                    <tr>\n",
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       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLP</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-4bf55059-8e6e-4f27-8300-a3f32b965dc5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4bf55059-8e6e-4f27-8300-a3f32b965dc5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0de138be-0bc9-41f2-8354-7a9dfc4cb8e5' class='xr-var-data-in' type='checkbox'><label for='data-0de138be-0bc9-41f2-8354-7a9dfc4cb8e5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>BASE STATE LAPSE RATE</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (6,) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TISO</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-a280d378-39f4-4263-a744-de65b5048cb8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a280d378-39f4-4263-a744-de65b5048cb8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-59ce734a-928e-498f-8410-28a0e568fa68' class='xr-var-data-in' type='checkbox'><label for='data-59ce734a-928e-498f-8410-28a0e568fa68' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>TEMP AT WHICH THE BASE T TURNS CONST</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (6,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TLP_STRAT</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-b2dad09e-8179-4bf9-bfb1-bdeccec7b28a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b2dad09e-8179-4bf9-bfb1-bdeccec7b28a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6cfb00ec-c954-4bb2-b2a1-ada8e385ad07' class='xr-var-data-in' type='checkbox'><label for='data-6cfb00ec-c954-4bb2-b2a1-ada8e385ad07' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>BASE STATE LAPSE RATE (DT/D(LN(P)) IN STRATOSPHERE</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (6,) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>P_STRAT</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-e6687105-4ca2-4c13-962c-276b5b246538' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e6687105-4ca2-4c13-962c-276b5b246538' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-593564d6-5b19-4193-89da-cd41d5c0dd95' class='xr-var-data-in' type='checkbox'><label for='data-593564d6-5b19-4193-89da-cd41d5c0dd95' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>BASE STATE PRESSURE AT BOTTOM OF STRATOSPHERE</dd><dt><span>units :</span></dt><dd>Pa</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (6,) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "        </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MAX_MSTFX</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-9b87678f-3e01-499b-b417-53bb42ef5e30' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9b87678f-3e01-499b-b417-53bb42ef5e30' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba389d2a-ec51-46ac-85b6-9a3d84170983' class='xr-var-data-in' type='checkbox'><label for='data-ba389d2a-ec51-46ac-85b6-9a3d84170983' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>Max map factor in domain</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
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       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
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       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
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       "                    <tr>\n",
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       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>GRAUPELNC</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-5719bcf1-3643-4bcd-b202-e1cd11f7612a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5719bcf1-3643-4bcd-b202-e1cd11f7612a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d86bb96a-1367-4381-a1b9-ff31fcfe7a7a' class='xr-var-data-in' type='checkbox'><label for='data-d86bb96a-1367-4381-a1b9-ff31fcfe7a7a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>ACCUMULATED TOTAL GRID SCALE GRAUPEL</dd><dt><span>units :</span></dt><dd>mm</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
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       "                        <th> Array </th>\n",
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       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.70 MiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
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       "                        <th> Data type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HAILNC</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-b6ea48c9-dff6-4087-b64e-0a0861de832f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b6ea48c9-dff6-4087-b64e-0a0861de832f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a3e03b4-90da-4ed9-b6cb-1cb9c2d62403' class='xr-var-data-in' type='checkbox'><label for='data-5a3e03b4-90da-4ed9-b6cb-1cb9c2d62403' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>ACCUMULATED TOTAL GRID SCALE HAIL</dd><dt><span>units :</span></dt><dd>mm</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "                        <td> 21.70 MiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 250, 250) </td>\n",
       "                        <td> (1, 125, 125) </td>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SWDOWN</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-2446318d-a0e7-4a1e-87e5-389888186a2b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2446318d-a0e7-4a1e-87e5-389888186a2b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a3140a6-683a-43c8-ba14-b308fc9a2836' class='xr-var-data-in' type='checkbox'><label for='data-6a3140a6-683a-43c8-ba14-b308fc9a2836' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>DOWNWARD SHORT WAVE FLUX AT GROUND SURFACE</dd><dt><span>units :</span></dt><dd>W m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                </thead>\n",
       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.70 MiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SWNORM</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-00115ad8-0277-44a8-af4f-b4dc2bbd4cf5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-00115ad8-0277-44a8-af4f-b4dc2bbd4cf5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e11834f-5790-49aa-8a26-4a65365255b4' class='xr-var-data-in' type='checkbox'><label for='data-5e11834f-5790-49aa-8a26-4a65365255b4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>NORMAL SHORT WAVE FLUX AT GROUND SURFACE (SLOPE-DEPENDENT)</dd><dt><span>units :</span></dt><dd>W m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "                        <td> 21.70 MiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ACSWDNT</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-6fd0b0dd-88b1-4bfb-94a2-75dd1c9ecf63' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6fd0b0dd-88b1-4bfb-94a2-75dd1c9ecf63' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f240570-557e-4e09-b9e7-8167a978872b' class='xr-var-data-in' type='checkbox'><label for='data-0f240570-557e-4e09-b9e7-8167a978872b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>ACCUMULATED DOWNWELLING SHORTWAVE FLUX AT TOP</dd><dt><span>units :</span></dt><dd>J m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ACSWDNTC</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-9ff9f1eb-631b-49bb-9bc9-bed23c3f9298' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9ff9f1eb-631b-49bb-9bc9-bed23c3f9298' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2616510e-418e-448f-892a-d55d1766869a' class='xr-var-data-in' type='checkbox'><label for='data-2616510e-418e-448f-892a-d55d1766869a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>ACCUMULATED DOWNWELLING CLEAR SKY SHORTWAVE FLUX AT TOP</dd><dt><span>units :</span></dt><dd>J m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ACSWDNBC</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-fdc05fed-d1e8-4ed1-8946-6183b139d857' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fdc05fed-d1e8-4ed1-8946-6183b139d857' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-762d44cc-1d93-43b7-8cf4-858a328fa269' class='xr-var-data-in' type='checkbox'><label for='data-762d44cc-1d93-43b7-8cf4-858a328fa269' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>ACCUMULATED DOWNWELLING CLEAR SKY SHORTWAVE FLUX AT BOTTOM</dd><dt><span>units :</span></dt><dd>J m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1, 125, 125) </td>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ACLWUPT</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-e31f466e-8ce4-415d-af67-d69b26f9fcd3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e31f466e-8ce4-415d-af67-d69b26f9fcd3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4052d4c4-511a-40a5-8562-b9e13102e5ba' class='xr-var-data-in' type='checkbox'><label for='data-4052d4c4-511a-40a5-8562-b9e13102e5ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>ACCUMULATED UPWELLING LONGWAVE FLUX AT TOP</dd><dt><span>units :</span></dt><dd>J m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ACLWDNTC</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-1b8ab84d-9fbc-4973-a3e8-1a4eb8764a80' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1b8ab84d-9fbc-4973-a3e8-1a4eb8764a80' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-75450c17-ae5a-45c0-868c-adecdd336405' class='xr-var-data-in' type='checkbox'><label for='data-75450c17-ae5a-45c0-868c-adecdd336405' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>ACCUMULATED DOWNWELLING CLEAR SKY LONGWAVE FLUX AT TOP</dd><dt><span>units :</span></dt><dd>J m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "        <td>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "                        <th> Shape </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>I_ACSWDNTC</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-01f7f3cc-1ea9-4f9b-95cf-983388a3e54e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-01f7f3cc-1ea9-4f9b-95cf-983388a3e54e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-02a013c7-5c8f-4f7c-916b-73bc2a98dc28' class='xr-var-data-in' type='checkbox'><label for='data-02a013c7-5c8f-4f7c-916b-73bc2a98dc28' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>106</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>BUCKET FOR DOWNWELLING CLEAR SKY SHORTWAVE FLUX AT TOP</dd><dt><span>units :</span></dt><dd>J m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "                        <th> Shape </th>\n",
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       "                        <td> (1, 125, 125) </td>\n",
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       "                        <th> Data type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>I_ACSWUPB</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-344c833d-b08d-4ce9-965b-0b5080cdbec4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-344c833d-b08d-4ce9-965b-0b5080cdbec4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6198e510-c1a7-4f9e-8eb9-54ddd6148621' class='xr-var-data-in' type='checkbox'><label for='data-6198e510-c1a7-4f9e-8eb9-54ddd6148621' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>106</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>BUCKET FOR UPWELLING SHORTWAVE FLUX AT BOTTOM</dd><dt><span>units :</span></dt><dd>J m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>I_ACSWDNBC</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-9f484352-2e02-4b78-857e-124cbb6d4d8c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9f484352-2e02-4b78-857e-124cbb6d4d8c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c6f8fa0-0ca7-4acc-bf3d-2618874406c3' class='xr-var-data-in' type='checkbox'><label for='data-3c6f8fa0-0ca7-4acc-bf3d-2618874406c3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>106</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>BUCKET FOR DOWNWELLING CLEAR SKY SHORTWAVE FLUX AT BOTTOM</dd><dt><span>units :</span></dt><dd>J m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>I_ACLWDNT</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-845284b1-e887-4510-87aa-4b26df5e42d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-845284b1-e887-4510-87aa-4b26df5e42d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7185f2da-1d77-4531-a6fb-0b038647a96e' class='xr-var-data-in' type='checkbox'><label for='data-7185f2da-1d77-4531-a6fb-0b038647a96e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>106</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>BUCKET FOR DOWNWELLING LONGWAVE FLUX AT TOP</dd><dt><span>units :</span></dt><dd>J m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>I_ACLWUPBC</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-1f072405-d113-428b-b9cb-ef2ba7e34f01' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f072405-d113-428b-b9cb-ef2ba7e34f01' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0bba9a2d-fe8b-403c-950d-5b0c67f3973d' class='xr-var-data-in' type='checkbox'><label for='data-0bba9a2d-fe8b-403c-950d-5b0c67f3973d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>106</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>BUCKET FOR UPWELLING CLEAR SKY LONGWAVE FLUX AT BOTTOM</dd><dt><span>units :</span></dt><dd>J m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>I_ACLWDNB</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-9d7946ef-4c0d-4a6e-af2a-4b60e8eb8a87' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9d7946ef-4c0d-4a6e-af2a-4b60e8eb8a87' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d68f306-e89c-483e-86fa-56a5da93e0d3' class='xr-var-data-in' type='checkbox'><label for='data-8d68f306-e89c-483e-86fa-56a5da93e0d3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>106</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>BUCKET FOR DOWNWELLING LONGWAVE FLUX AT BOTTOM</dd><dt><span>units :</span></dt><dd>J m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>I_ACLWDNBC</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-0066c1cb-0016-4ac8-8e2b-5ed32b3fd39d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0066c1cb-0016-4ac8-8e2b-5ed32b3fd39d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1267bb50-ad1f-42c3-85e4-31115e3c3fde' class='xr-var-data-in' type='checkbox'><label for='data-1267bb50-ad1f-42c3-85e4-31115e3c3fde' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>106</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>BUCKET FOR DOWNWELLING CLEAR SKY LONGWAVE FLUX AT BOTTOM</dd><dt><span>units :</span></dt><dd>J m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SWDNTC</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-4ed6f141-f757-4db6-bc80-cb0002c13fee' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4ed6f141-f757-4db6-bc80-cb0002c13fee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-babbfa17-59a3-4da2-804a-c4629138edbc' class='xr-var-data-in' type='checkbox'><label for='data-babbfa17-59a3-4da2-804a-c4629138edbc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>INSTANTANEOUS DOWNWELLING CLEAR SKY SHORTWAVE FLUX AT TOP</dd><dt><span>units :</span></dt><dd>W m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "                        <td> 21.70 MiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
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       "                        <td> 21.70 MiB </td>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 21.70 MiB </td>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ALBBCK</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-713b09f3-4861-4bf7-9405-fd8dfc3e9fa1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-713b09f3-4861-4bf7-9405-fd8dfc3e9fa1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5788385a-3525-47f4-bfb6-4ab65454e2ba' class='xr-var-data-in' type='checkbox'><label for='data-5788385a-3525-47f4-bfb6-4ab65454e2ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>BACKGROUND ALBEDO</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PBLH</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-e5823a51-3d02-47dc-8527-23624904ffd2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e5823a51-3d02-47dc-8527-23624904ffd2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b2ba8ee-c6f1-499f-978e-f68729f60577' class='xr-var-data-in' type='checkbox'><label for='data-4b2ba8ee-c6f1-499f-978e-f68729f60577' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>PBL HEIGHT</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>stagger :</span></dt><dd></dd><dt><span>standard_name :</span></dt><dd>atmosphere_boundary_layer_thickness</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                <tbody>\n",
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       "        <td>\n",
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       "                    <tr>\n",
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       "                        <th> Chunk </th>\n",
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       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 80.34 kiB </td>\n",
       "                        <td> 904 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 226) </td>\n",
       "                        <td> (1, 226) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> int32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>m33</span></div><div class='xr-var-dims'>(Time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-fa76d9fe-8a87-4392-b8f1-c802b6ac3f2d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fa76d9fe-8a87-4392-b8f1-c802b6ac3f2d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-268cef0c-678f-4e4b-8769-9b02e1620591' class='xr-var-data-in' type='checkbox'><label for='data-268cef0c-678f-4e4b-8769-9b02e1620591' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>33 component of NBA subgrid stress tensor</dd><dt><span>units :</span></dt><dd>m2 s-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
       "                        <td> 13.47 MiB </td>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
       "                        <td> 13.47 MiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>m13</span></div><div class='xr-var-dims'>(Time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-be80e7d3-b102-44e2-a9fc-cd1ba568b6f9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-be80e7d3-b102-44e2-a9fc-cd1ba568b6f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-25e60585-69c6-4152-9329-fc31f826a462' class='xr-var-data-in' type='checkbox'><label for='data-25e60585-69c6-4152-9329-fc31f826a462' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>13 component of NBA subgrid stress tensor</dd><dt><span>units :</span></dt><dd>m2 s-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "                </thead>\n",
       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
       "                        <td> 13.47 MiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                        <th> Data type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>m23</span></div><div class='xr-var-dims'>(Time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-8a3ed94d-550d-47e0-a3e8-994f03c3ced2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8a3ed94d-550d-47e0-a3e8-994f03c3ced2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-31f3e5f6-e844-4f5b-a22e-e9c05136f610' class='xr-var-data-in' type='checkbox'><label for='data-31f3e5f6-e844-4f5b-a22e-e9c05136f610' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>23 component of NBA subgrid stress tensor</dd><dt><span>units :</span></dt><dd>m2 s-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
       "                        <td> 13.47 MiB </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 226, 250, 250) </td>\n",
       "                        <td> (1, 226, 125, 125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 364 chunks in 33 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 266.96 kiB </td>\n",
       "                        <td> 2.93 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 751) </td>\n",
       "                        <td> (1, 751) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>U_LS_TEND</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-3fdd2fcd-8968-4da5-a4f1-72a3199316b4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3fdd2fcd-8968-4da5-a4f1-72a3199316b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3d11bd3-57c8-47d6-9264-59beb6756d4f' class='xr-var-data-in' type='checkbox'><label for='data-b3d11bd3-57c8-47d6-9264-59beb6756d4f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>tendency large-scale zonal wind velocity</dd><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 266.96 kiB </td>\n",
       "                        <td> 2.93 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 751) </td>\n",
       "                        <td> (1, 751) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>V_LS</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-b58ae0fa-6231-417f-a025-f1a623415a45' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b58ae0fa-6231-417f-a025-f1a623415a45' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1f7a3a88-ee09-4984-8d4f-70df0b35dee2' class='xr-var-data-in' type='checkbox'><label for='data-1f7a3a88-ee09-4984-8d4f-70df0b35dee2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>large-scale meridional wind velocity</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
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       "                    <tr>\n",
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       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 266.96 kiB </td>\n",
       "                        <td> 2.93 kiB </td>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>V_LS_TEND</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-95989766-3337-4f39-81dd-41ae5105db21' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-95989766-3337-4f39-81dd-41ae5105db21' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fc59dc18-e617-45ec-8b06-6138013fff55' class='xr-var-data-in' type='checkbox'><label for='data-fc59dc18-e617-45ec-8b06-6138013fff55' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>tendency large-scale meridional wind velocity</dd><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "            <table style=\"border-collapse: collapse;\">\n",
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       "                        <th> Array </th>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>W_LS</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-8feea093-d0cc-4353-8bba-df5a3daf230c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8feea093-d0cc-4353-8bba-df5a3daf230c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6ddd76e1-7543-4247-b64e-0b677459e9e7' class='xr-var-data-in' type='checkbox'><label for='data-6ddd76e1-7543-4247-b64e-0b677459e9e7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>large-scale vertical velocity</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 266.96 kiB </td>\n",
       "                        <td> 2.93 kiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 751) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>W_LS_TEND</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-001b641b-7e1d-49ba-80a4-fa5fef789cb6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-001b641b-7e1d-49ba-80a4-fa5fef789cb6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-24ecaeb5-8a17-4101-99a8-6cf693d607fa' class='xr-var-data-in' type='checkbox'><label for='data-24ecaeb5-8a17-4101-99a8-6cf693d607fa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>tendency large-scale vertical velocity</dd><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 266.96 kiB </td>\n",
       "                        <td> 2.93 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 751) </td>\n",
       "                        <td> (1, 751) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>INV_TAU_S</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-11b5c553-dc63-49de-95dd-0c98a983593c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-11b5c553-dc63-49de-95dd-0c98a983593c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fcb02cce-7451-447e-a0ae-21771b6035a3' class='xr-var-data-in' type='checkbox'><label for='data-fcb02cce-7451-447e-a0ae-21771b6035a3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>inverse relaxation time for scalars</dd><dt><span>units :</span></dt><dd>s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
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       "                    <tr>\n",
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       "                        <th> Shape </th>\n",
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       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>INV_TAU_M</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-bf6b19d3-edb2-4084-b733-9a5ca48d0798' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bf6b19d3-edb2-4084-b733-9a5ca48d0798' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba9885be-9c31-48e5-b328-e91123480059' class='xr-var-data-in' type='checkbox'><label for='data-ba9885be-9c31-48e5-b328-e91123480059' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>inverse relaxation time for scalars</dd><dt><span>units :</span></dt><dd>s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 266.96 kiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TH_ADV</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-a145c5c9-5ab2-49b4-bc95-6f250a989d7b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a145c5c9-5ab2-49b4-bc95-6f250a989d7b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f23bbe32-dc37-4bd3-8164-af872ee14e6d' class='xr-var-data-in' type='checkbox'><label for='data-f23bbe32-dc37-4bd3-8164-af872ee14e6d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>tendency theta advection</dd><dt><span>units :</span></dt><dd>K s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "                        <th> Array </th>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "                        <td> 266.96 kiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TH_ADV_TEND</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-095113f3-fba9-4ad9-a2ac-a980372c5f01' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-095113f3-fba9-4ad9-a2ac-a980372c5f01' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-285c3462-5eef-4915-bd7d-6a1eca03ba97' class='xr-var-data-in' type='checkbox'><label for='data-285c3462-5eef-4915-bd7d-6a1eca03ba97' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>tendency of tendency theta advection</dd><dt><span>units :</span></dt><dd>K s-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 266.96 kiB </td>\n",
       "                        <td> 2.93 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 751) </td>\n",
       "                        <td> (1, 751) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TH_RLX</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-261f8ec3-a434-4df0-a6cf-c6b6a7b4f87a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-261f8ec3-a434-4df0-a6cf-c6b6a7b4f87a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-796a5662-4561-443e-bd57-0c4433b63daf' class='xr-var-data-in' type='checkbox'><label for='data-796a5662-4561-443e-bd57-0c4433b63daf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>theta relaxation</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 266.96 kiB </td>\n",
       "                        <td> 2.93 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 751) </td>\n",
       "                        <td> (1, 751) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TH_RLX_TEND</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-cb7bd1c7-b2f2-445c-992c-4b058c7642db' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cb7bd1c7-b2f2-445c-992c-4b058c7642db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8dd42f16-8d58-4280-9950-f1f1ae3c9a91' class='xr-var-data-in' type='checkbox'><label for='data-8dd42f16-8d58-4280-9950-f1f1ae3c9a91' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>tendency theta relaxation</dd><dt><span>units :</span></dt><dd>K s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 266.96 kiB </td>\n",
       "                        <td> 2.93 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 751) </td>\n",
       "                        <td> (1, 751) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>QV_ADV</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-656c491c-2c81-4426-b364-7aee2cf2e6d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-656c491c-2c81-4426-b364-7aee2cf2e6d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e988b36-7845-43cd-be1b-07ae841b19a1' class='xr-var-data-in' type='checkbox'><label for='data-4e988b36-7845-43cd-be1b-07ae841b19a1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>tendency qv advection</dd><dt><span>units :</span></dt><dd>kg kg-1 s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 266.96 kiB </td>\n",
       "                        <td> 2.93 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 751) </td>\n",
       "                        <td> (1, 751) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>QV_ADV_TEND</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-3f09638f-4143-43c3-938e-0afb962e57fe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3f09638f-4143-43c3-938e-0afb962e57fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c4edb8b-088c-4a58-9dc9-2fee885c0cc3' class='xr-var-data-in' type='checkbox'><label for='data-3c4edb8b-088c-4a58-9dc9-2fee885c0cc3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>tendency of tendency qv advection</dd><dt><span>units :</span></dt><dd>kg kg-1 s-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 266.96 kiB </td>\n",
       "                        <td> 2.93 kiB </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 751) </td>\n",
       "                        <td> (1, 751) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>QV_RLX</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-97f76e17-086d-4972-b0a4-113e90b41182' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-97f76e17-086d-4972-b0a4-113e90b41182' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-52c26c6e-552a-4e11-b7f1-f693a762123c' class='xr-var-data-in' type='checkbox'><label for='data-52c26c6e-552a-4e11-b7f1-f693a762123c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>qv relaxation</dd><dt><span>units :</span></dt><dd>kg kg-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
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       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 266.96 kiB </td>\n",
       "                        <td> 2.93 kiB </td>\n",
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       "                    <tr>\n",
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       "                        <td> (1, 751) </td>\n",
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       "                    <tr>\n",
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       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
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       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>QV_RLX_TEND</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-3247e6d2-e0a0-46af-ad27-f285f91abfed' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3247e6d2-e0a0-46af-ad27-f285f91abfed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8bee9a7b-a0b1-4e87-ab2d-0c78092705da' class='xr-var-data-in' type='checkbox'><label for='data-8bee9a7b-a0b1-4e87-ab2d-0c78092705da' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>tendency qv relaxation</dd><dt><span>units :</span></dt><dd>kg kg-1 s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
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       "                </thead>\n",
       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 266.96 kiB </td>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Z_LS</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-8d2073bd-9d13-47ab-9f10-dc33466be9eb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8d2073bd-9d13-47ab-9f10-dc33466be9eb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a2319a5-8418-451e-8081-ec5ad6ab570b' class='xr-var-data-in' type='checkbox'><label for='data-1a2319a5-8418-451e-8081-ec5ad6ab570b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>z of large-scale forcings</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 266.96 kiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Z_LS_TEND</span></div><div class='xr-var-dims'>(Time, force_layers)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 751), meta=np.ndarray&gt;</div><input id='attrs-0e505f54-6e17-4b8b-a20a-7feb1fe788e0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0e505f54-6e17-4b8b-a20a-7feb1fe788e0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b6ba5fb4-73fb-48ba-9c83-736fc6ae678c' class='xr-var-data-in' type='checkbox'><label for='data-b6ba5fb4-73fb-48ba-9c83-736fc6ae678c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>tendency of z of large-scale forcings</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 266.96 kiB </td>\n",
       "                        <td> 2.93 kiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 751) </td>\n",
       "                        <td> (1, 751) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
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       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PRE_SH_FLX</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-d5f23472-b228-4906-b819-631c41867317' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d5f23472-b228-4906-b819-631c41867317' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6938459f-7795-4172-9a7d-69409ea88dc6' class='xr-var-data-in' type='checkbox'><label for='data-6938459f-7795-4172-9a7d-69409ea88dc6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>prescribed sensible heat flux</dd><dt><span>units :</span></dt><dd>W m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
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       "                        <td> 24 B </td>\n",
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       "                        <td> (6,) </td>\n",
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       "                        <th> Data type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PRE_SH_FLX_TEND</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-bf1ab9ce-6d68-4a76-8f8e-d8358a6845c2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bf1ab9ce-6d68-4a76-8f8e-d8358a6845c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6406987-3e02-4dd8-9d30-19397f2c3946' class='xr-var-data-in' type='checkbox'><label for='data-c6406987-3e02-4dd8-9d30-19397f2c3946' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>tendency prescribed sensible heat flux</dd><dt><span>units :</span></dt><dd>W m-2 s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
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       "                        <th> Shape </th>\n",
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       "                        <td> (6,) </td>\n",
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       "                    <tr>\n",
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       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PRE_LH_FLX</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-1bf91cd1-44a7-4111-ac67-3bdea74db63d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1bf91cd1-44a7-4111-ac67-3bdea74db63d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ba73891-92db-4715-8dd6-406bc99fafb2' class='xr-var-data-in' type='checkbox'><label for='data-8ba73891-92db-4715-8dd6-406bc99fafb2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>prescribed latent heat flux</dd><dt><span>units :</span></dt><dd>W m-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PRE_LH_FLX_TEND</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-b0f6225f-d6ee-4e7d-a224-d38b16250deb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b0f6225f-d6ee-4e7d-a224-d38b16250deb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b0ead87-91c8-482e-a0a5-91deef172e11' class='xr-var-data-in' type='checkbox'><label for='data-8b0ead87-91c8-482e-a0a5-91deef172e11' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>tendency prescribed latent heat flux</dd><dt><span>units :</span></dt><dd>W m-2 s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (6,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PRE_ALBEDO</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-0b860d0b-8501-4d2e-bfb0-c0cd1179b93b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0b860d0b-8501-4d2e-bfb0-c0cd1179b93b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c529346e-aa14-41bd-bf91-fbca591fa962' class='xr-var-data-in' type='checkbox'><label for='data-c529346e-aa14-41bd-bf91-fbca591fa962' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>prescribed albedo</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (6,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PRE_ALBEDO_TEND</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-18598c21-bb0e-4c02-85ac-0e0b0125c236' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-18598c21-bb0e-4c02-85ac-0e0b0125c236' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3374c48f-2d7c-4cbf-a392-028554658042' class='xr-var-data-in' type='checkbox'><label for='data-3374c48f-2d7c-4cbf-a392-028554658042' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>tendency prescribed albedo</dd><dt><span>units :</span></dt><dd>s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (6,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "        </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PRE_TSK</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-74132684-d441-4796-80ac-8a1e7ffbfa18' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-74132684-d441-4796-80ac-8a1e7ffbfa18' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ec0c1bb-d3fa-4da0-be04-4f1e3bef10ea' class='xr-var-data-in' type='checkbox'><label for='data-5ec0c1bb-d3fa-4da0-be04-4f1e3bef10ea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>prescribed skin temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91,) </td>\n",
       "                        <td> (6,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PRE_TSK_TEND</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-7ef05841-dc80-480a-8f56-968870e19de5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7ef05841-dc80-480a-8f56-968870e19de5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f36324d-89a2-4d76-80f4-173917f5d87f' class='xr-var-data-in' type='checkbox'><label for='data-4f36324d-89a2-4d76-80f4-173917f5d87f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>tendency prescribed skin temperature</dd><dt><span>units :</span></dt><dd>K s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (6,) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 16 chunks in 33 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NUM_MODES_AER</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6,), meta=np.ndarray&gt;</div><input id='attrs-1dc9c5d3-ad65-4eab-8790-c33ffb3a5d49' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1dc9c5d3-ad65-4eab-8790-c33ffb3a5d49' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c58fc7da-8f58-4db8-8a5c-afb0438219ef' class='xr-var-data-in' type='checkbox'><label for='data-c58fc7da-8f58-4db8-8a5c-afb0438219ef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>106</dd><dt><span>MemoryOrder :</span></dt><dd>0  </dd><dt><span>description :</span></dt><dd>Number of aerosol distribution modes</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
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       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 364 B </td>\n",
       "                        <td> 24 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (6,) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> int32 numpy.ndarray </td>\n",
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       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>RVLSTEN</span></div><div class='xr-var-dims'>(Time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-2c071c02-0971-4f01-af97-1931f18676fd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2c071c02-0971-4f01-af97-1931f18676fd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9d8fc0f7-59e9-4ff5-b577-77b0f6d0e228' class='xr-var-data-in' type='checkbox'><label for='data-9d8fc0f7-59e9-4ff5-b577-77b0f6d0e228' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>coupled v tendency due to LS forcing</dd><dt><span>units :</span></dt><dd>Pa m s-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                </thead>\n",
       "                <tbody>\n",
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       "                    <tr>\n",
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       "                        <td> 4.79 GiB </td>\n",
       "                        <td> 13.47 MiB </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>RQVLSTEN</span></div><div class='xr-var-dims'>(Time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-4945b3b5-a171-4e54-a0f6-4ff8a3894dca' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4945b3b5-a171-4e54-a0f6-4ff8a3894dca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b813a16-406f-4138-a002-a616de40d4db' class='xr-var-data-in' type='checkbox'><label for='data-8b813a16-406f-4138-a002-a616de40d4db' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>coupled Q_V tendency due to LS forcing</dd><dt><span>units :</span></dt><dd>Pa kg kg-1 s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
       "                        <td> 13.47 MiB </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1, 226, 125, 125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>THDT_LSHOR</span></div><div class='xr-var-dims'>(Time, z)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226), meta=np.ndarray&gt;</div><input id='attrs-55672966-7f16-4790-be01-a284cf272f74' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-55672966-7f16-4790-be01-a284cf272f74' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1af78cf3-97d5-4da6-a95b-91f51d2dba17' class='xr-var-data-in' type='checkbox'><label for='data-1af78cf3-97d5-4da6-a95b-91f51d2dba17' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>th tendency due to LS horizontal adv</dd><dt><span>units :</span></dt><dd>K s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 80.34 kiB </td>\n",
       "                        <td> 904 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 226) </td>\n",
       "                        <td> (1, 226) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>QVDT_LSHOR</span></div><div class='xr-var-dims'>(Time, z)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226), meta=np.ndarray&gt;</div><input id='attrs-7815bc86-dc45-4b97-ba0b-059e5e5d7534' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7815bc86-dc45-4b97-ba0b-059e5e5d7534' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a45fe7a-159b-48d0-b039-fa2351fafed0' class='xr-var-data-in' type='checkbox'><label for='data-3a45fe7a-159b-48d0-b039-fa2351fafed0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>qv tendency due to LS horizontal adv</dd><dt><span>units :</span></dt><dd>kg kg-1 s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 80.34 kiB </td>\n",
       "                        <td> 904 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 226) </td>\n",
       "                        <td> (1, 226) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>THDT_LSRLX</span></div><div class='xr-var-dims'>(Time, z)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226), meta=np.ndarray&gt;</div><input id='attrs-40a59a32-b897-41b9-8bac-d41ba3cdfc21' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-40a59a32-b897-41b9-8bac-d41ba3cdfc21' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-070334a1-59f2-4c12-b0f4-0694d46d1c94' class='xr-var-data-in' type='checkbox'><label for='data-070334a1-59f2-4c12-b0f4-0694d46d1c94' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>th tendency due to relaxation to LS</dd><dt><span>units :</span></dt><dd>K s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 80.34 kiB </td>\n",
       "                        <td> 904 B </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 226) </td>\n",
       "                        <td> (1, 226) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>QVDT_LSRLX</span></div><div class='xr-var-dims'>(Time, z)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226), meta=np.ndarray&gt;</div><input id='attrs-3c1ce6b3-303d-48da-9d07-67fe8f1c5049' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c1ce6b3-303d-48da-9d07-67fe8f1c5049' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-636c276b-4aee-485d-b354-8bf31edf44f0' class='xr-var-data-in' type='checkbox'><label for='data-636c276b-4aee-485d-b354-8bf31edf44f0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>qv tendency due to relaxation to LS</dd><dt><span>units :</span></dt><dd>kg kg-1 s-1</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
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       "                        <td> 904 B </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <th> Dask graph </th>\n",
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       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>UDT_LSRLX</span></div><div class='xr-var-dims'>(Time, z)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226), meta=np.ndarray&gt;</div><input id='attrs-6a62ee46-8b0a-475b-a7a3-e2c4e9ef2408' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6a62ee46-8b0a-475b-a7a3-e2c4e9ef2408' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7e7de917-d229-45a5-9064-cb19f94e5ea3' class='xr-var-data-in' type='checkbox'><label for='data-7e7de917-d229-45a5-9064-cb19f94e5ea3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>Z  </dd><dt><span>description :</span></dt><dd>u tendency due to relaxation to LS</dd><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 80.34 kiB </td>\n",
       "                        <td> 904 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 226) </td>\n",
       "                        <td> (1, 226) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 91 chunks in 33 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 80.34 kiB </td>\n",
       "                        <td> 904 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 226) </td>\n",
       "                        <td> (1, 226) </td>\n",
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       "                        <th> Dask graph </th>\n",
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       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EFFCS</span></div><div class='xr-var-dims'>(Time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-cc05ae09-83bd-44da-9eff-ee9e032be570' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc05ae09-83bd-44da-9eff-ee9e032be570' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8693eafa-92d6-40e3-9a97-61dadd02158a' class='xr-var-data-in' type='checkbox'><label for='data-8693eafa-92d6-40e3-9a97-61dadd02158a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>CLOUD DROPLET EFFECTIVE RADIUS</dd><dt><span>units :</span></dt><dd>micron</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <th> Shape </th>\n",
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       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>QVDT_PR</span></div><div class='xr-var-dims'>(Time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-2b714b55-5089-498d-8adf-a1f97df2bda9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2b714b55-5089-498d-8adf-a1f97df2bda9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-673d6ef8-7eab-4ef4-b8b8-f57a12d0bff3' class='xr-var-data-in' type='checkbox'><label for='data-673d6ef8-7eab-4ef4-b8b8-f57a12d0bff3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>Production rate of vapor by conversion to rain</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
       "                        <td> 13.47 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 226, 250, 250) </td>\n",
       "                        <td> (1, 226, 125, 125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>QVDT_COND</span></div><div class='xr-var-dims'>(Time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-852f30e2-e777-4cfd-9e96-108a32531411' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-852f30e2-e777-4cfd-9e96-108a32531411' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-53033798-e898-4f97-b258-cc1ec22bd77d' class='xr-var-data-in' type='checkbox'><label for='data-53033798-e898-4f97-b258-cc1ec22bd77d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>Production rate of vapor by conversion to rain</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
       "                        <td> 13.47 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 226, 250, 250) </td>\n",
       "                        <td> (1, 226, 125, 125) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 364 chunks in 33 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>QCDT_PR</span></div><div class='xr-var-dims'>(Time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-9babb299-4329-412d-b2e3-665836d5c952' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9babb299-4329-412d-b2e3-665836d5c952' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-991845fb-9803-485e-91aa-5a5f738e5454' class='xr-var-data-in' type='checkbox'><label for='data-991845fb-9803-485e-91aa-5a5f738e5454' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>Production rate of vapor by conversion to rain</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "                        <th> Dask graph </th>\n",
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       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "                        <th> Dask graph </th>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
       "                        <td> 13.47 MiB </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                        <th> Data type </th>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "                        <td> 21.70 MiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
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       "                        <th> Data type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>LAKEMASK</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-0d1aaea2-5342-4379-9789-a3a2e9c53825' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0d1aaea2-5342-4379-9789-a3a2e9c53825' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-152160a3-3d74-42a4-8041-c171bab7dc82' class='xr-var-data-in' type='checkbox'><label for='data-152160a3-3d74-42a4-8041-c171bab7dc82' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>LAKE MASK (1 FOR LAKE, 0 FOR NON-LAKE)</dd><dt><span>units :</span></dt><dd></dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "                        <td> 21.70 MiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                <tbody>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SST_INPUT</span></div><div class='xr-var-dims'>(Time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-323640b1-31eb-4ce8-b8a0-56ddbc43df8e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-323640b1-31eb-4ce8-b8a0-56ddbc43df8e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-be66ef47-1fd5-444a-be90-ee3960035e94' class='xr-var-data-in' type='checkbox'><label for='data-be66ef47-1fd5-444a-be90-ee3960035e94' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>SEA SURFACE TEMPERATURE FROM WRFLOWINPUT FILE</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>air_pressure</span></div><div class='xr-var-dims'>(Time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-8325780f-000f-4487-86f0-ed8274d40ba1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8325780f-000f-4487-86f0-ed8274d40ba1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-797f5325-7350-41bf-916e-5d6776facb06' class='xr-var-data-in' type='checkbox'><label for='data-797f5325-7350-41bf-916e-5d6776facb06' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Pa</dd><dt><span>standard_name :</span></dt><dd>air_pressure</dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "                        <td> (1, 226, 125, 125) </td>\n",
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       "                        <th> Dask graph </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geopotential</span></div><div class='xr-var-dims'>(Time, z_stag, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 227, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-b1003c9a-74d5-4607-bfd2-b749cc9b4a8d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b1003c9a-74d5-4607-bfd2-b749cc9b4a8d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-210f5938-a718-4f49-854e-feaedb00e81c' class='xr-var-data-in' type='checkbox'><label for='data-210f5938-a718-4f49-854e-feaedb00e81c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m**2 s**-2</dd><dt><span>standard_name :</span></dt><dd>geopotential</dd><dt><span>stagger :</span></dt><dd>Z</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.81 GiB </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (1, 227, 125, 125) </td>\n",
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       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 4.81 GiB </td>\n",
       "                        <td> 13.53 MiB </td>\n",
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       "                        <td> (1, 227, 125, 125) </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wind_east</span></div><div class='xr-var-dims'>(Time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 226, 125, 125), meta=np.ndarray&gt;</div><input id='attrs-46b7c648-21fb-44dd-8c7d-3617f03a0643' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-46b7c648-21fb-44dd-8c7d-3617f03a0643' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1405a40a-a532-4a27-add2-eb7a9ac62647' class='xr-var-data-in' type='checkbox'><label for='data-1405a40a-a532-4a27-add2-eb7a9ac62647' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>earth-relative x-wind component</dd><dt><span>standard_name :</span></dt><dd>eastward_wind</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>grid_mapping :</span></dt><dd>wrf_projection</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <th> Bytes </th>\n",
       "                        <td> 4.79 GiB </td>\n",
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       "                        <td> 21.70 MiB </td>\n",
       "                        <td> 61.04 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (91, 250, 250) </td>\n",
       "                        <td> (1, 125, 125) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 364 chunks in 135 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "          0.9857232570648193,    0.9816849231719971,    0.9776613116264343,\n",
       "          0.9736500978469849,    0.9696520566940308,    0.9656686782836914,\n",
       "          0.9616985321044922,\n",
       "       ...\n",
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       "          0.9636806845664978,\n",
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       "                         0.0],\n",
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       "               &#x27;2019-04-04 20:00:00&#x27;, &#x27;2019-04-04 20:10:00&#x27;,\n",
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       "               &#x27;2019-04-05 01:00:00&#x27;, &#x27;2019-04-05 01:10:00&#x27;,\n",
       "               &#x27;2019-04-05 01:20:00&#x27;, &#x27;2019-04-05 01:30:00&#x27;,\n",
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       "               &#x27;2019-04-05 02:20:00&#x27;, &#x27;2019-04-05 02:30:00&#x27;,\n",
       "               &#x27;2019-04-05 02:40:00&#x27;, &#x27;2019-04-05 02:50:00&#x27;,\n",
       "               &#x27;2019-04-05 03:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;Time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y_stag</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d1846288-2570-48ec-8f65-d87f9a165387' class='xr-index-data-in' type='checkbox'/><label for='index-d1846288-2570-48ec-8f65-d87f9a165387' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-12500.0, -12400.0, -12300.0, -12200.0, -12100.0, -12000.0, -11900.0,\n",
       "       -11800.0, -11700.0, -11600.0,\n",
       "       ...\n",
       "        11600.0,  11700.0,  11800.0,  11900.0,  12000.0,  12100.0,  12200.0,\n",
       "        12300.0,  12400.0,  12500.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;y_stag&#x27;, length=251))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-44dbe0d6-f383-43e8-aaec-a98de908b8bb' class='xr-index-data-in' type='checkbox'/><label for='index-44dbe0d6-f383-43e8-aaec-a98de908b8bb' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-12450.0, -12350.0, -12250.0, -12150.0, -12050.0, -11950.0, -11850.0,\n",
       "       -11750.0, -11650.0, -11550.0,\n",
       "       ...\n",
       "        11550.0,  11650.0,  11750.0,  11850.0,  11950.0,  12050.0,  12150.0,\n",
       "        12250.0,  12350.0,  12450.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=250))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c789a085-adde-4e2c-93e3-c002a9aaa8f2' class='xr-index-data-in' type='checkbox'/><label for='index-c789a085-adde-4e2c-93e3-c002a9aaa8f2' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-12450.0, -12350.0, -12250.0, -12150.0, -12050.0, -11950.0, -11850.0,\n",
       "       -11750.0, -11650.0, -11550.0,\n",
       "       ...\n",
       "        11550.0,  11650.0,  11750.0,  11850.0,  11950.0,  12050.0,  12150.0,\n",
       "        12250.0,  12350.0,  12450.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=250))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x_stag</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2ed5efba-f27a-474a-a5a2-47a2fd945c38' class='xr-index-data-in' type='checkbox'/><label for='index-2ed5efba-f27a-474a-a5a2-47a2fd945c38' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-12500.0, -12400.0, -12300.0, -12200.0, -12100.0, -12000.0, -11900.0,\n",
       "       -11800.0, -11700.0, -11600.0,\n",
       "       ...\n",
       "        11600.0,  11700.0,  11800.0,  11900.0,  12000.0,  12100.0,  12200.0,\n",
       "        12300.0,  12400.0,  12500.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;x_stag&#x27;, length=251))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0b8b6ccb-2549-491f-8f36-316b021dee47' class='xr-section-summary-in' type='checkbox'  ><label for='section-0b8b6ccb-2549-491f-8f36-316b021dee47' class='xr-section-summary' >Attributes: <span>(142)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>TITLE :</span></dt><dd> OUTPUT FROM WRF V3.8.1 MODEL</dd><dt><span>START_DATE :</span></dt><dd>2019-04-04_12:00:00</dd><dt><span>SIMULATION_START_DATE :</span></dt><dd>2019-04-04_12:00:00</dd><dt><span>WEST-EAST_GRID_DIMENSION :</span></dt><dd>251</dd><dt><span>SOUTH-NORTH_GRID_DIMENSION :</span></dt><dd>251</dd><dt><span>BOTTOM-TOP_GRID_DIMENSION :</span></dt><dd>227</dd><dt><span>DX :</span></dt><dd>100.0</dd><dt><span>DY :</span></dt><dd>100.0</dd><dt><span>SKEBS_ON :</span></dt><dd>0</dd><dt><span>SPEC_BDY_FINAL_MU :</span></dt><dd>1</dd><dt><span>USE_Q_DIABATIC :</span></dt><dd>0</dd><dt><span>GRIDTYPE :</span></dt><dd>C</dd><dt><span>DIFF_OPT :</span></dt><dd>2</dd><dt><span>KM_OPT :</span></dt><dd>2</dd><dt><span>DAMP_OPT :</span></dt><dd>3</dd><dt><span>DAMPCOEF :</span></dt><dd>0.2</dd><dt><span>KHDIF :</span></dt><dd>1.0</dd><dt><span>KVDIF :</span></dt><dd>1.0</dd><dt><span>MP_PHYSICS :</span></dt><dd>8</dd><dt><span>RA_LW_PHYSICS :</span></dt><dd>4</dd><dt><span>RA_SW_PHYSICS :</span></dt><dd>4</dd><dt><span>SF_SFCLAY_PHYSICS :</span></dt><dd>1</dd><dt><span>SF_SURFACE_PHYSICS :</span></dt><dd>1</dd><dt><span>BL_PBL_PHYSICS :</span></dt><dd>0</dd><dt><span>CU_PHYSICS :</span></dt><dd>0</dd><dt><span>SF_LAKE_PHYSICS :</span></dt><dd>0</dd><dt><span>SURFACE_INPUT_SOURCE :</span></dt><dd>3</dd><dt><span>SST_UPDATE :</span></dt><dd>0</dd><dt><span>GRID_FDDA :</span></dt><dd>0</dd><dt><span>GFDDA_INTERVAL_M :</span></dt><dd>0</dd><dt><span>GFDDA_END_H :</span></dt><dd>0</dd><dt><span>GRID_SFDDA :</span></dt><dd>0</dd><dt><span>SGFDDA_INTERVAL_M :</span></dt><dd>0</dd><dt><span>SGFDDA_END_H :</span></dt><dd>0</dd><dt><span>HYPSOMETRIC_OPT :</span></dt><dd>1</dd><dt><span>USE_THETA_M :</span></dt><dd>1</dd><dt><span>SF_URBAN_PHYSICS :</span></dt><dd>0</dd><dt><span>SHCU_PHYSICS :</span></dt><dd>0</dd><dt><span>MFSHCONV :</span></dt><dd>0</dd><dt><span>FEEDBACK :</span></dt><dd>0</dd><dt><span>SMOOTH_OPTION :</span></dt><dd>0</dd><dt><span>SWRAD_SCAT :</span></dt><dd>1.0</dd><dt><span>W_DAMPING :</span></dt><dd>0</dd><dt><span>RADT :</span></dt><dd>1.0</dd><dt><span>BLDT :</span></dt><dd>0.0</dd><dt><span>CUDT :</span></dt><dd>0.0</dd><dt><span>AER_OPT :</span></dt><dd>0</dd><dt><span>SWINT_OPT :</span></dt><dd>0</dd><dt><span>AER_TYPE :</span></dt><dd>1</dd><dt><span>AER_AOD550_OPT :</span></dt><dd>1</dd><dt><span>AER_ANGEXP_OPT :</span></dt><dd>1</dd><dt><span>AER_SSA_OPT :</span></dt><dd>1</dd><dt><span>AER_ASY_OPT :</span></dt><dd>1</dd><dt><span>AER_AOD550_VAL :</span></dt><dd>0.12</dd><dt><span>AER_ANGEXP_VAL :</span></dt><dd>1.3</dd><dt><span>AER_SSA_VAL :</span></dt><dd>1e-45</dd><dt><span>AER_ASY_VAL :</span></dt><dd>1e-45</dd><dt><span>MOIST_ADV_OPT :</span></dt><dd>2</dd><dt><span>SCALAR_ADV_OPT :</span></dt><dd>2</dd><dt><span>TKE_ADV_OPT :</span></dt><dd>2</dd><dt><span>DIFF_6TH_OPT :</span></dt><dd>0</dd><dt><span>DIFF_6TH_FACTOR :</span></dt><dd>0.12</dd><dt><span>OBS_NUDGE_OPT :</span></dt><dd>0</dd><dt><span>BUCKET_MM :</span></dt><dd>-1.0</dd><dt><span>BUCKET_J :</span></dt><dd>-1.0</dd><dt><span>PREC_ACC_DT :</span></dt><dd>0.0</dd><dt><span>SF_OCEAN_PHYSICS :</span></dt><dd>0</dd><dt><span>ISFTCFLX :</span></dt><dd>0</dd><dt><span>ISHALLOW :</span></dt><dd>0</dd><dt><span>ISFFLX :</span></dt><dd>11</dd><dt><span>ICLOUD :</span></dt><dd>1</dd><dt><span>ICLOUD_CU :</span></dt><dd>0</dd><dt><span>TRACER_PBLMIX :</span></dt><dd>1</dd><dt><span>SCALAR_PBLMIX :</span></dt><dd>0</dd><dt><span>YSU_TOPDOWN_PBLMIX :</span></dt><dd>0</dd><dt><span>GRAV_SETTLING :</span></dt><dd>0</dd><dt><span>DFI_OPT :</span></dt><dd>0</dd><dt><span>SIMULATION_INITIALIZATION_TYPE :</span></dt><dd>IDEALIZED DATA</dd><dt><span>WEST-EAST_PATCH_START_UNSTAG :</span></dt><dd>1</dd><dt><span>WEST-EAST_PATCH_END_UNSTAG :</span></dt><dd>250</dd><dt><span>WEST-EAST_PATCH_START_STAG :</span></dt><dd>1</dd><dt><span>WEST-EAST_PATCH_END_STAG :</span></dt><dd>251</dd><dt><span>SOUTH-NORTH_PATCH_START_UNSTAG :</span></dt><dd>1</dd><dt><span>SOUTH-NORTH_PATCH_END_UNSTAG :</span></dt><dd>250</dd><dt><span>SOUTH-NORTH_PATCH_START_STAG :</span></dt><dd>1</dd><dt><span>SOUTH-NORTH_PATCH_END_STAG :</span></dt><dd>251</dd><dt><span>BOTTOM-TOP_PATCH_START_UNSTAG :</span></dt><dd>1</dd><dt><span>BOTTOM-TOP_PATCH_END_UNSTAG :</span></dt><dd>226</dd><dt><span>BOTTOM-TOP_PATCH_START_STAG :</span></dt><dd>1</dd><dt><span>BOTTOM-TOP_PATCH_END_STAG :</span></dt><dd>227</dd><dt><span>GRID_ID :</span></dt><dd>1</dd><dt><span>PARENT_ID :</span></dt><dd>0</dd><dt><span>I_PARENT_START :</span></dt><dd>0</dd><dt><span>J_PARENT_START :</span></dt><dd>0</dd><dt><span>PARENT_GRID_RATIO :</span></dt><dd>1</dd><dt><span>DT :</span></dt><dd>0.5</dd><dt><span>CEN_LAT :</span></dt><dd>0.0</dd><dt><span>CEN_LON :</span></dt><dd>0.0</dd><dt><span>TRUELAT1 :</span></dt><dd>0.0</dd><dt><span>TRUELAT2 :</span></dt><dd>0.0</dd><dt><span>MOAD_CEN_LAT :</span></dt><dd>0.0</dd><dt><span>STAND_LON :</span></dt><dd>0.0</dd><dt><span>POLE_LAT :</span></dt><dd>0.0</dd><dt><span>POLE_LON :</span></dt><dd>0.0</dd><dt><span>GMT :</span></dt><dd>0.0</dd><dt><span>JULYR :</span></dt><dd>0</dd><dt><span>JULDAY :</span></dt><dd>1</dd><dt><span>MAP_PROJ :</span></dt><dd>0</dd><dt><span>MAP_PROJ_CHAR :</span></dt><dd>Cartesian</dd><dt><span>MMINLU :</span></dt><dd></dd><dt><span>NUM_LAND_CAT :</span></dt><dd>21</dd><dt><span>ISWATER :</span></dt><dd>16</dd><dt><span>ISLAKE :</span></dt><dd>0</dd><dt><span>ISICE :</span></dt><dd>0</dd><dt><span>ISURBAN :</span></dt><dd>0</dd><dt><span>ISOILWATER :</span></dt><dd>0</dd><dt><span>doi :</span></dt><dd>10.5439/1342961</dd><dt><span>contacts :</span></dt><dd>lasso@arm.gov, LASSO PI: William Gustafson (William.Gustafson@pnnl.gov), LASSO Co-PI: Andrew Vogelmann (vogelmann@bnl.gov)</dd><dt><span>site_id :</span></dt><dd>sgp</dd><dt><span>facility_id :</span></dt><dd>C1</dd><dt><span>location_description :</span></dt><dd>Southern Great Plains (SGP), Lamont, Oklahoma</dd><dt><span>date :</span></dt><dd>20190404</dd><dt><span>simulation_id_number :</span></dt><dd>4</dd><dt><span>model_type :</span></dt><dd>WRF</dd><dt><span>model_version :</span></dt><dd>3.8.1</dd><dt><span>model_github_hash :</span></dt><dd>b6b6a5cc4229eec1ea9b005746b5ebef2205fb07</dd><dt><span>output_domain_size :</span></dt><dd>25.0 km</dd><dt><span>output_number_of_levels :</span></dt><dd>226</dd><dt><span>output_horizontal_grid_spacing :</span></dt><dd>100 m</dd><dt><span>config_large_scale_forcing :</span></dt><dd>ECMWF</dd><dt><span>config_large_scale_forcing_scale :</span></dt><dd>114 km</dd><dt><span>config_large_scale_forcing_specifics :</span></dt><dd>sgpecmwfvarX1.c1,sgpecmwftenX1.c1,sgpecmwfsfc1lX1.c1,sgpecmwfsfceX1.c1 (v20191206)</dd><dt><span>config_surface_treatment :</span></dt><dd>VARANAL</dd><dt><span>config_surface_treatment_specifics :</span></dt><dd>sgp60varanarapC1.c1 (v20191126)</dd><dt><span>config_initial_condition :</span></dt><dd>Sounding</dd><dt><span>config_initial_condition_specifics :</span></dt><dd>sgpsondewnpnC1</dd><dt><span>config_aerosol :</span></dt><dd>NA</dd><dt><span>config_forecast_time :</span></dt><dd>15.0 h</dd><dt><span>config_boundary_method :</span></dt><dd>Periodic</dd><dt><span>config_microphysics :</span></dt><dd>Thompson (mp_physics=8)</dd><dt><span>config_nickname :</span></dt><dd>runlas20190404v1addhm</dd><dt><span>simulation_origin_host :</span></dt><dd>cumulus-login2.ccs.ornl.gov</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 255GB\n",
       "Dimensions:                    (Time: 91, y: 250, x: 250, soil_layers_stag: 5,\n",
       "                                z: 226, x_stag: 251, y_stag: 251, z_stag: 227,\n",
       "                                force_layers: 751)\n",
       "Coordinates: (12/15)\n",
       "    CLAT                       (y, x) float32 250kB dask.array<chunksize=(125, 125), meta=np.ndarray>\n",
       "    XLAT                       (y, x) float32 250kB dask.array<chunksize=(125, 125), meta=np.ndarray>\n",
       "    XLONG                      (y, x) float32 250kB dask.array<chunksize=(125, 125), meta=np.ndarray>\n",
       "    XTIME                      (Time) datetime64[ns] 728B dask.array<chunksize=(6,), meta=np.ndarray>\n",
       "    XLAT_U                     (y, x_stag) float32 251kB dask.array<chunksize=(125, 126), meta=np.ndarray>\n",
       "    XLONG_U                    (y, x_stag) float32 251kB dask.array<chunksize=(125, 126), meta=np.ndarray>\n",
       "    ...                         ...\n",
       "  * z_stag                     (z_stag) float32 908B 1.0 0.9959 ... 0.002178 0.0\n",
       "  * Time                       (Time) datetime64[ns] 728B 2019-04-04T12:00:00...\n",
       "  * y_stag                     (y_stag) float64 2kB -1.25e+04 ... 1.25e+04\n",
       "  * y                          (y) float64 2kB -1.245e+04 ... 1.245e+04\n",
       "  * x                          (x) float64 2kB -1.245e+04 ... 1.245e+04\n",
       "  * x_stag                     (x_stag) float64 2kB -1.25e+04 ... 1.25e+04\n",
       "Dimensions without coordinates: soil_layers_stag, force_layers\n",
       "Data variables: (12/251)\n",
       "    Times                      (Time) |S19 2kB dask.array<chunksize=(1,), meta=np.ndarray>\n",
       "    LU_INDEX                   (Time, y, x) float32 23MB dask.array<chunksize=(1, 125, 125), meta=np.ndarray>\n",
       "    ZS                         (Time, soil_layers_stag) float32 2kB dask.array<chunksize=(1, 5), meta=np.ndarray>\n",
       "    DZS                        (Time, soil_layers_stag) float32 2kB dask.array<chunksize=(1, 5), meta=np.ndarray>\n",
       "    VAR_SSO                    (Time, y, x) float32 23MB dask.array<chunksize=(1, 125, 125), meta=np.ndarray>\n",
       "    U                          (Time, z, y, x_stag) float32 5GB dask.array<chunksize=(1, 226, 125, 126), meta=np.ndarray>\n",
       "    ...                         ...\n",
       "    geopotential               (Time, z_stag, y, x) float32 5GB dask.array<chunksize=(1, 227, 125, 125), meta=np.ndarray>\n",
       "    geopotential_height        (Time, z_stag, y, x) float32 5GB dask.array<chunksize=(1, 227, 125, 125), meta=np.ndarray>\n",
       "    wind_east                  (Time, z, y, x) float32 5GB dask.array<chunksize=(1, 226, 125, 125), meta=np.ndarray>\n",
       "    wind_north                 (Time, z, y, x) float32 5GB dask.array<chunksize=(1, 226, 125, 125), meta=np.ndarray>\n",
       "    wind_east_10               (Time, y, x) float32 23MB dask.array<chunksize=(1, 125, 125), meta=np.ndarray>\n",
       "    wind_north_10              (Time, y, x) float32 23MB dask.array<chunksize=(1, 125, 125), meta=np.ndarray>\n",
       "Attributes: (12/142)\n",
       "    TITLE:                                  OUTPUT FROM WRF V3.8.1 MODEL\n",
       "    START_DATE:                            2019-04-04_12:00:00\n",
       "    SIMULATION_START_DATE:                 2019-04-04_12:00:00\n",
       "    WEST-EAST_GRID_DIMENSION:              251\n",
       "    SOUTH-NORTH_GRID_DIMENSION:            251\n",
       "    BOTTOM-TOP_GRID_DIMENSION:             227\n",
       "    ...                                    ...\n",
       "    config_aerosol:                        NA\n",
       "    config_forecast_time:                  15.0 h\n",
       "    config_boundary_method:                Periodic\n",
       "    config_microphysics:                   Thompson (mp_physics=8)\n",
       "    config_nickname:                       runlas20190404v1addhm\n",
       "    simulation_origin_host:                cumulus-login2.ccs.ornl.gov"
      ]
     },
     "execution_count": 144,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds"
   ]
  }
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