Introduction to Pyresample - (re)Gridding with xarray

https://pyresample.readthedocs.io/en/latest/

This package seems a bit more speciallized, and does not have as tight of integration with xarray like xESMF and Verde do. If working with satellite or swath data, this is not one to miss! This package integrates with Satpy https://satpy.readthedocs.io/en/stable/ .

(more) Integration with xarray¶

This is on the to-do list: https://pyresample.readthedocs.io/en/latest/roadmap.html?highlight=xarray#xarray-and-geoxarray

Prerequisites¶

Knowing your way around xarray, numpy is beneficial. This is not deisgned to be an introduction to any of those packages. Would do this notebook after doing the xESMF one!

Imports¶

import pandas as pd
import numpy as np
import xarray as xr

import matplotlib.pyplot as plt

from appdirs import *

import dask.array as da

import pyresample
from pyresample import image, geometry
from pyresample.bilinear import NumpyBilinearResampler

from xarray import DataArray
from pyresample.bilinear import XArrayBilinearResampler

import os

%load_ext watermark
%watermark --iversions

xarray    : 2025.6.1
appdirs   : 1.4.4
dask      : 2025.5.1
sys       : 3.13.5 | packaged by conda-forge | (main, Jun 16 2025, 08:27:50) [GCC 13.3.0]
numpy     : 2.2.6
matplotlib: 3.10.3
pyresample: 1.34.2
pandas    : 2.3.0

Loading in one netCDF¶

file = '../data/onestorm.nc'

Let’s open this file with xarray:

ds = xr.open_dataset(file)
ds

Trying to do the same thing with pyresample:

from pyresample.utils import load_cf_area

area_def, cf_info = load_cf_area('data/onestorm.nc', variable='visible', x='x', y='y')

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
File ~/micromamba/envs/gridding-cookbook-dev/lib/python3.13/site-packages/xarray/backends/file_manager.py:211, in CachingFileManager._acquire_with_cache_info(self, needs_lock)
    210 try:
--> 211     file = self._cache[self._key]
    212 except KeyError:

File ~/micromamba/envs/gridding-cookbook-dev/lib/python3.13/site-packages/xarray/backends/lru_cache.py:56, in LRUCache.__getitem__(self, key)
     55 with self._lock:
---> 56     value = self._cache[key]
     57     self._cache.move_to_end(key)

KeyError: [<class 'netCDF4._netCDF4.Dataset'>, ('/home/runner/work/gridding-cookbook/gridding-cookbook/notebooks/data/onestorm.nc',), 'r', (('clobber', True), ('diskless', False), ('format', 'NETCDF4'), ('persist', False)), 'b660bdca-eb6b-4166-b9cb-dc22993e277a']

During handling of the above exception, another exception occurred:

FileNotFoundError                         Traceback (most recent call last)
Cell In[6], line 1
----> 1 area_def, cf_info = load_cf_area('data/onestorm.nc', variable='visible', x='x', y='y')

File ~/micromamba/envs/gridding-cookbook-dev/lib/python3.13/site-packages/pyresample/utils/cf.py:444, in load_cf_area(nc_file, variable, y, x)
    441 if (x is not None and y is None) or (x is None and y is not None):
    442     raise ValueError("You must specify both or neither of x= and y=")
--> 444 nc_handle = _open_nc_file(nc_file)
    445 if variable is None:
    446     # if the variable=None, we search through all variables
    447     area_def, cf_info = _load_cf_area_several_variables(nc_handle)

File ~/micromamba/envs/gridding-cookbook-dev/lib/python3.13/site-packages/pyresample/utils/cf.py:478, in _open_nc_file(nc_file)
    475 if isinstance(nc_file, xr.Dataset):
    476     return nc_file
--> 478 return xr.open_dataset(nc_file)

File ~/micromamba/envs/gridding-cookbook-dev/lib/python3.13/site-packages/xarray/backends/api.py:687, 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, inline_array, chunked_array_type, from_array_kwargs, backend_kwargs, **kwargs)
    675 decoders = _resolve_decoders_kwargs(
    676     decode_cf,
    677     open_backend_dataset_parameters=backend.open_dataset_parameters,
   (...)    683     decode_coords=decode_coords,
    684 )
    686 overwrite_encoded_chunks = kwargs.pop("overwrite_encoded_chunks", None)
--> 687 backend_ds = backend.open_dataset(
    688     filename_or_obj,
    689     drop_variables=drop_variables,
    690     **decoders,
    691     **kwargs,
    692 )
    693 ds = _dataset_from_backend_dataset(
    694     backend_ds,
    695     filename_or_obj,
   (...)    705     **kwargs,
    706 )
    707 return ds

File ~/micromamba/envs/gridding-cookbook-dev/lib/python3.13/site-packages/xarray/backends/netCDF4_.py:666, in NetCDF4BackendEntrypoint.open_dataset(self, filename_or_obj, mask_and_scale, decode_times, concat_characters, decode_coords, drop_variables, use_cftime, decode_timedelta, group, mode, format, clobber, diskless, persist, auto_complex, lock, autoclose)
    644 def open_dataset(
    645     self,
    646     filename_or_obj: str | os.PathLike[Any] | ReadBuffer | AbstractDataStore,
   (...)    663     autoclose=False,
    664 ) -> Dataset:
    665     filename_or_obj = _normalize_path(filename_or_obj)
--> 666     store = NetCDF4DataStore.open(
    667         filename_or_obj,
    668         mode=mode,
    669         format=format,
    670         group=group,
    671         clobber=clobber,
    672         diskless=diskless,
    673         persist=persist,
    674         auto_complex=auto_complex,
    675         lock=lock,
    676         autoclose=autoclose,
    677     )
    679     store_entrypoint = StoreBackendEntrypoint()
    680     with close_on_error(store):

File ~/micromamba/envs/gridding-cookbook-dev/lib/python3.13/site-packages/xarray/backends/netCDF4_.py:452, in NetCDF4DataStore.open(cls, filename, mode, format, group, clobber, diskless, persist, auto_complex, lock, lock_maker, autoclose)
    448     kwargs["auto_complex"] = auto_complex
    449 manager = CachingFileManager(
    450     netCDF4.Dataset, filename, mode=mode, kwargs=kwargs
    451 )
--> 452 return cls(manager, group=group, mode=mode, lock=lock, autoclose=autoclose)

File ~/micromamba/envs/gridding-cookbook-dev/lib/python3.13/site-packages/xarray/backends/netCDF4_.py:393, in NetCDF4DataStore.__init__(self, manager, group, mode, lock, autoclose)
    391 self._group = group
    392 self._mode = mode
--> 393 self.format = self.ds.data_model
    394 self._filename = self.ds.filepath()
    395 self.is_remote = is_remote_uri(self._filename)

File ~/micromamba/envs/gridding-cookbook-dev/lib/python3.13/site-packages/xarray/backends/netCDF4_.py:461, in NetCDF4DataStore.ds(self)
    459 @property
    460 def ds(self):
--> 461     return self._acquire()

File ~/micromamba/envs/gridding-cookbook-dev/lib/python3.13/site-packages/xarray/backends/netCDF4_.py:455, in NetCDF4DataStore._acquire(self, needs_lock)
    454 def _acquire(self, needs_lock=True):
--> 455     with self._manager.acquire_context(needs_lock) as root:
    456         ds = _nc4_require_group(root, self._group, self._mode)
    457     return ds

File ~/micromamba/envs/gridding-cookbook-dev/lib/python3.13/contextlib.py:141, in _GeneratorContextManager.__enter__(self)
    139 del self.args, self.kwds, self.func
    140 try:
--> 141     return next(self.gen)
    142 except StopIteration:
    143     raise RuntimeError("generator didn't yield") from None

File ~/micromamba/envs/gridding-cookbook-dev/lib/python3.13/site-packages/xarray/backends/file_manager.py:199, in CachingFileManager.acquire_context(self, needs_lock)
    196 @contextlib.contextmanager
    197 def acquire_context(self, needs_lock=True):
    198     """Context manager for acquiring a file."""
--> 199     file, cached = self._acquire_with_cache_info(needs_lock)
    200     try:
    201         yield file

File ~/micromamba/envs/gridding-cookbook-dev/lib/python3.13/site-packages/xarray/backends/file_manager.py:217, in CachingFileManager._acquire_with_cache_info(self, needs_lock)
    215     kwargs = kwargs.copy()
    216     kwargs["mode"] = self._mode
--> 217 file = self._opener(*self._args, **kwargs)
    218 if self._mode == "w":
    219     # ensure file doesn't get overridden when opened again
    220     self._mode = "a"

File src/netCDF4/_netCDF4.pyx:2521, in netCDF4._netCDF4.Dataset.__init__()

File src/netCDF4/_netCDF4.pyx:2158, in netCDF4._netCDF4._ensure_nc_success()

FileNotFoundError: [Errno 2] No such file or directory: '/home/runner/work/gridding-cookbook/gridding-cookbook/notebooks/data/onestorm.nc'

This is supposed to fail. Will chat about pro’s and con’s in the summary.

Resampling of gridded data using pyresample¶

Link to this turtorial is here: https://pyresample.readthedocs.io/en/latest/swath.html#pyresample-bilinear

We will be deconstructing it a bit to get into the details, but all of the code is from the above link.

target_def = geometry.AreaDefinition('areaD',
                                     'Europe (3km, HRV, VTC)',
                                     'areaD',
                                     {'a': '6378144.0', 'b': '6356759.0',
                                      'lat_0': '50.00', 'lat_ts': '50.00',
                                      'lon_0': '8.00', 'proj': 'stere'},
                                     800, 800,
                                     [-1370912.72, -909968.64,
                                      1029087.28, 1490031.36])

Unlike using xESMF, this does not depend or work with xarray:

print('target def type', type(target_def))

target def type <class 'pyresample.geometry.AreaDefinition'>

data = DataArray(da.from_array(np.fromfunction(lambda y, x: y*x, (500, 100))), dims=('y', 'x'))
type(data)

xarray.core.dataarray.DataArray

lons = da.from_array(np.fromfunction(lambda y, x: 3 + x * 0.1, (500, 100)))
lats = da.from_array(np.fromfunction(lambda y, x: 75 - y * 0.1, (500, 100)))
source_def = geometry.SwathDefinition(lons=lons, lats=lats)

resampler = XArrayBilinearResampler(source_def, target_def, 30e3)
result = resampler.resample(data)
type(result)

/home/runner/micromamba/envs/gridding-cookbook-dev/lib/python3.13/site-packages/pyproj/crs/crs.py:1295: UserWarning: You will likely lose important projection information when converting to a PROJ string from another format. See: https://proj.org/faq.html#what-is-the-best-format-for-describing-coordinate-reference-systems
  proj = self._crs.to_proj4(version=version)

xarray.core.dataarray.DataArray

Can export to xarray¶

result.to_dataset()

data.to_dataset()

Summary¶

Pyresample is a speciallist program, with strong functionality with satpy. Would reccomend if swath/sat image data is part of your normal workflow. For others, the requirement of the data being CF compliant and API is a hurdle.

re(Gridding)

Introduction to Verde