Skip to article frontmatterSkip to article content

Along Track Altimetry Analysis

Project Pythia Logo Pangeo Logo

Along Track Altimetry Analysis


Overview

  1. Using CNES altimetry data
  2. Visualizing data using hvplot
  3. Use xhistogram to plot multidimensional data

Prerequisites

ConceptsImportanceNotes
Intro to PandasHelpful
Using hvplotHelpfulMatplotlib knowledge also helpful
DaskHelpful
xhistogramHelpful
  • Time to learn: 15 minutes

Imports


import fsspec
import xarray as xr
import numpy as np
import hvplot
import hvplot.dask
import hvplot.pandas
import hvplot.xarray
from xhistogram.xarray import histogram
from intake import open_catalog
Loading...

Load Data

The analysis ready along-track altimetry data were prepared by CNES. They are catalogged in the Pangeo Cloud Data Catalog here: https://catalog.pangeo.io/browse/master/ocean/altimetry/

We will work with Jason 3.

cat = open_catalog("https://raw.githubusercontent.com/pangeo-data/pangeo-datastore/master/intake-catalogs/ocean/altimetry.yaml")
print(list(cat))
ds = cat['j3'].to_dask()
ds
['al', 'alg', 'c2', 'e1', 'e1g', 'e2', 'en', 'enn', 'g2', 'h2', 'j1', 'j1g', 'j1n', 'j2', 'j2g', 'j2n', 'j3', 's3a', 's3b', 'tp', 'tpn']
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[2], line 3
      1 cat = open_catalog("https://raw.githubusercontent.com/pangeo-data/pangeo-datastore/master/intake-catalogs/ocean/altimetry.yaml")
      2 print(list(cat))
----> 3 ds = cat['j3'].to_dask()
      4 ds

File ~/micromamba/envs/po-cookbook-dev/lib/python3.13/site-packages/intake_xarray/base.py:8, in IntakeXarraySourceAdapter.to_dask(self)
      6 def to_dask(self):
      7     if "chunks" not in self.reader.kwargs:
----> 8         return self.reader(chunks={}).read()
      9     else:
     10         return self.reader.read()

File ~/micromamba/envs/po-cookbook-dev/lib/python3.13/site-packages/intake/readers/readers.py:121, in BaseReader.read(self, *args, **kwargs)
    119 kw.update(kwargs)
    120 args = kw.pop("args", ()) or args
--> 121 return self._read(*args, **kw)

File ~/micromamba/envs/po-cookbook-dev/lib/python3.13/site-packages/intake/readers/readers.py:1327, in XArrayDatasetReader._read(self, data, open_local, **kw)
   1325         f = fsspec.open(data.url, **(data.storage_options or {})).open()
   1326         return open_dataset(f, **kw)
-> 1327 return open_dataset(data.url, **kw)

File ~/micromamba/envs/po-cookbook-dev/lib/python3.13/site-packages/xarray/backends/api.py:715, in open_dataset(filename_or_obj, engine, chunks, cache, decode_cf, mask_and_scale, decode_times, decode_timedelta, use_cftime, concat_characters, decode_coords, drop_variables, create_default_indexes, inline_array, chunked_array_type, from_array_kwargs, backend_kwargs, **kwargs)
    703 decoders = _resolve_decoders_kwargs(
    704     decode_cf,
    705     open_backend_dataset_parameters=backend.open_dataset_parameters,
   (...)    711     decode_coords=decode_coords,
    712 )
    714 overwrite_encoded_chunks = kwargs.pop("overwrite_encoded_chunks", None)
--> 715 backend_ds = backend.open_dataset(
    716     filename_or_obj,
    717     drop_variables=drop_variables,
    718     **decoders,
    719     **kwargs,
    720 )
    721 ds = _dataset_from_backend_dataset(
    722     backend_ds,
    723     filename_or_obj,
   (...)    734     **kwargs,
    735 )
    736 return ds

File ~/micromamba/envs/po-cookbook-dev/lib/python3.13/site-packages/xarray/backends/zarr.py:1587, in ZarrBackendEntrypoint.open_dataset(self, filename_or_obj, mask_and_scale, decode_times, concat_characters, decode_coords, drop_variables, use_cftime, decode_timedelta, group, mode, synchronizer, consolidated, chunk_store, storage_options, zarr_version, zarr_format, store, engine, use_zarr_fill_value_as_mask, cache_members)
   1585 filename_or_obj = _normalize_path(filename_or_obj)
   1586 if not store:
-> 1587     store = ZarrStore.open_group(
   1588         filename_or_obj,
   1589         group=group,
   1590         mode=mode,
   1591         synchronizer=synchronizer,
   1592         consolidated=consolidated,
   1593         consolidate_on_close=False,
   1594         chunk_store=chunk_store,
   1595         storage_options=storage_options,
   1596         zarr_version=zarr_version,
   1597         use_zarr_fill_value_as_mask=None,
   1598         zarr_format=zarr_format,
   1599         cache_members=cache_members,
   1600     )
   1602 store_entrypoint = StoreBackendEntrypoint()
   1603 with close_on_error(store):

File ~/micromamba/envs/po-cookbook-dev/lib/python3.13/site-packages/xarray/backends/zarr.py:664, in ZarrStore.open_group(cls, store, mode, synchronizer, group, consolidated, consolidate_on_close, chunk_store, storage_options, append_dim, write_region, safe_chunks, align_chunks, zarr_version, zarr_format, use_zarr_fill_value_as_mask, write_empty, cache_members)
    638 @classmethod
    639 def open_group(
    640     cls,
   (...)    657     cache_members: bool = True,
    658 ):
    659     (
    660         zarr_group,
    661         consolidate_on_close,
    662         close_store_on_close,
    663         use_zarr_fill_value_as_mask,
--> 664     ) = _get_open_params(
    665         store=store,
    666         mode=mode,
    667         synchronizer=synchronizer,
    668         group=group,
    669         consolidated=consolidated,
    670         consolidate_on_close=consolidate_on_close,
    671         chunk_store=chunk_store,
    672         storage_options=storage_options,
    673         zarr_version=zarr_version,
    674         use_zarr_fill_value_as_mask=use_zarr_fill_value_as_mask,
    675         zarr_format=zarr_format,
    676     )
    678     return cls(
    679         zarr_group,
    680         mode,
   (...)    689         cache_members=cache_members,
    690     )

File ~/micromamba/envs/po-cookbook-dev/lib/python3.13/site-packages/xarray/backends/zarr.py:1791, in _get_open_params(store, mode, synchronizer, group, consolidated, consolidate_on_close, chunk_store, storage_options, zarr_version, use_zarr_fill_value_as_mask, zarr_format)
   1787 group = open_kwargs.pop("path")
   1789 if consolidated:
   1790     # TODO: an option to pass the metadata_key keyword
-> 1791     zarr_root_group = zarr.open_consolidated(store, **open_kwargs)
   1792 elif consolidated is None:
   1793     # same but with more error handling in case no consolidated metadata found
   1794     try:

File ~/micromamba/envs/po-cookbook-dev/lib/python3.13/site-packages/zarr/api/synchronous.py:222, in open_consolidated(use_consolidated, *args, **kwargs)
    217 def open_consolidated(*args: Any, use_consolidated: Literal[True] = True, **kwargs: Any) -> Group:
    218     """
    219     Alias for :func:`open_group` with ``use_consolidated=True``.
    220     """
    221     return Group(
--> 222         sync(async_api.open_consolidated(*args, use_consolidated=use_consolidated, **kwargs))
    223     )

File ~/micromamba/envs/po-cookbook-dev/lib/python3.13/site-packages/zarr/core/sync.py:163, in sync(coro, loop, timeout)
    160 return_result = next(iter(finished)).result()
    162 if isinstance(return_result, BaseException):
--> 163     raise return_result
    164 else:
    165     return return_result

File ~/micromamba/envs/po-cookbook-dev/lib/python3.13/site-packages/zarr/core/sync.py:119, in _runner(coro)
    114 """
    115 Await a coroutine and return the result of running it. If awaiting the coroutine raises an
    116 exception, the exception will be returned.
    117 """
    118 try:
--> 119     return await coro
    120 except Exception as ex:
    121     return ex

File ~/micromamba/envs/po-cookbook-dev/lib/python3.13/site-packages/zarr/api/asynchronous.py:382, in open_consolidated(use_consolidated, *args, **kwargs)
    377 if use_consolidated is not True:
    378     raise TypeError(
    379         "'use_consolidated' must be 'True' in 'open_consolidated'. Use 'open' with "
    380         "'use_consolidated=False' to bypass consolidated metadata."
    381     )
--> 382 return await open_group(*args, use_consolidated=use_consolidated, **kwargs)

File ~/micromamba/envs/po-cookbook-dev/lib/python3.13/site-packages/zarr/api/asynchronous.py:845, in open_group(store, mode, cache_attrs, synchronizer, path, chunk_store, storage_options, zarr_version, zarr_format, meta_array, attributes, use_consolidated)
    843 try:
    844     if mode in _READ_MODES:
--> 845         return await AsyncGroup.open(
    846             store_path, zarr_format=zarr_format, use_consolidated=use_consolidated
    847         )
    848 except (KeyError, FileNotFoundError):
    849     pass

File ~/micromamba/envs/po-cookbook-dev/lib/python3.13/site-packages/zarr/core/group.py:542, in AsyncGroup.open(cls, store, zarr_format, use_consolidated)
    535         raise FileNotFoundError(store_path)
    536 elif zarr_format is None:
    537     (
    538         zarr_json_bytes,
    539         zgroup_bytes,
    540         zattrs_bytes,
    541         maybe_consolidated_metadata_bytes,
--> 542     ) = await asyncio.gather(
    543         (store_path / ZARR_JSON).get(),
    544         (store_path / ZGROUP_JSON).get(),
    545         (store_path / ZATTRS_JSON).get(),
    546         (store_path / str(consolidated_key)).get(),
    547     )
    548     if zarr_json_bytes is not None and zgroup_bytes is not None:
    549         # warn and favor v3
    550         msg = f"Both zarr.json (Zarr format 3) and .zgroup (Zarr format 2) metadata objects exist at {store_path}. Zarr format 3 will be used."

File ~/micromamba/envs/po-cookbook-dev/lib/python3.13/site-packages/zarr/storage/_common.py:164, in StorePath.get(self, prototype, byte_range)
    162 if prototype is None:
    163     prototype = default_buffer_prototype()
--> 164 return await self.store.get(self.path, prototype=prototype, byte_range=byte_range)

File ~/micromamba/envs/po-cookbook-dev/lib/python3.13/site-packages/zarr/storage/_fsspec.py:300, in FsspecStore.get(self, key, prototype, byte_range)
    298 try:
    299     if byte_range is None:
--> 300         value = prototype.buffer.from_bytes(await self.fs._cat_file(path))
    301     elif isinstance(byte_range, RangeByteRequest):
    302         value = prototype.buffer.from_bytes(
    303             await self.fs._cat_file(
    304                 path,
   (...)    307             )
    308         )

File ~/micromamba/envs/po-cookbook-dev/lib/python3.13/site-packages/gcsfs/core.py:1117, in GCSFileSystem._cat_file(self, path, start, end, **kwargs)
   1115 else:
   1116     head = {}
-> 1117 headers, out = await self._call("GET", u2, headers=head)
   1118 return out

File ~/micromamba/envs/po-cookbook-dev/lib/python3.13/site-packages/gcsfs/core.py:483, in GCSFileSystem._call(self, method, path, json_out, info_out, *args, **kwargs)
    479 async def _call(
    480     self, method, path, *args, json_out=False, info_out=False, **kwargs
    481 ):
    482     logger.debug(f"{method.upper()}: {path}, {args}, {kwargs.get('headers')}")
--> 483     status, headers, info, contents = await self._request(
    484         method, path, *args, **kwargs
    485     )
    486     if json_out:
    487         return json.loads(contents)

File ~/micromamba/envs/po-cookbook-dev/lib/python3.13/site-packages/decorator.py:224, in decorate.<locals>.fun(*args, **kw)
    222 if not kwsyntax:
    223     args, kw = fix(args, kw, sig)
--> 224 return await caller(func, *(extras + args), **kw)

File ~/micromamba/envs/po-cookbook-dev/lib/python3.13/site-packages/gcsfs/retry.py:135, in retry_request(func, retries, *args, **kwargs)
    133     if retry > 0:
    134         await asyncio.sleep(min(random.random() + 2 ** (retry - 1), 32))
--> 135     return await func(*args, **kwargs)
    136 except (
    137     HttpError,
    138     requests.exceptions.RequestException,
   (...)    141     aiohttp.client_exceptions.ClientError,
    142 ) as e:
    143     if (
    144         isinstance(e, HttpError)
    145         and e.code == 400
    146         and "requester pays" in e.message
    147     ):

File ~/micromamba/envs/po-cookbook-dev/lib/python3.13/site-packages/gcsfs/core.py:476, in GCSFileSystem._request(self, method, path, headers, json, data, *args, **kwargs)
    473 info = r.request_info  # for debug only
    474 contents = await r.read()
--> 476 validate_response(status, contents, path, args)
    477 return status, headers, info, contents

File ~/micromamba/envs/po-cookbook-dev/lib/python3.13/site-packages/gcsfs/retry.py:120, in validate_response(status, content, path, args)
    118     raise requests.exceptions.ProxyError()
    119 elif "invalid" in str(msg):
--> 120     raise ValueError(f"Bad Request: {path}\n{msg}")
    121 elif error and not isinstance(error, str):
    122     raise HttpError(error)

ValueError: Bad Request: https://storage.googleapis.com/download/storage/v1/b/pangeo-cnes/o/alti%2Fj3%2F.zgroup?alt=media
User project specified in the request is invalid.

Load some data into memory:

# Select latitude, longitude, and sea level anomaly
ds_ll = ds[['latitude', 'longitude', 'sla_filtered']].reset_coords().astype('f4').load()
ds_ll

Convert to pandas dataframe:

df = ds_ll.to_dataframe()
df

Visualize with hvplot

df.hvplot.scatter(x='longitude', y='latitude', datashade=True)

Bin using xhistogram

lon_bins = np.arange(0, 361, 2)
lat_bins = np.arange(-70, 71, 2)

# helps with memory management
ds_ll_chunked = ds_ll.chunk({'time': '5MB'})

sla_variance = histogram(ds_ll_chunked.longitude, ds_ll_chunked.latitude,
                         bins=[lon_bins, lat_bins],
                         weights=ds_ll_chunked.sla_filtered.fillna(0.)**2)

norm = histogram(ds_ll_chunked.longitude, ds_ll_chunked.latitude,
                         bins=[lon_bins, lat_bins])


# let's get at least 200 points in a box for it to be unmasked
thresh = 200
sla_variance = sla_variance / norm.where(norm > thresh)
sla_variance
sla_variance.load()
# plot the sea level anomaly variance
sla_variance.plot(x='longitude_bin', figsize=(12, 6), vmax=0.2)

Summary


In this example we visualized sea level anomalies using along-track altimetry data using hvplot. Then, we used xhistogram to calculate and plot the variance of the data.

What’s next?

Other examples will look at other datasets to visualize sea surface temeratures, ocean depth, and currents.

Resources and references