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

numpy     : 2.3.5
sys       : 3.13.9 | packaged by conda-forge | (main, Oct 22 2025, 23:33:35) [GCC 14.3.0]
matplotlib: 3.10.8
dask      : 2025.11.0
appdirs   : 1.4.4
pyresample: 1.34.2
xarray    : 2025.11.0
pandas    : 2.3.3

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:219, in CachingFileManager._acquire_with_cache_info(self, needs_lock)
    218 try:
--> 219     file = self._cache[self._key]
    220 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)), '53cd6e09-5d96-4949-8787-1fec58b769f3']

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:606, 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)
    594 decoders = _resolve_decoders_kwargs(
    595     decode_cf,
    596     open_backend_dataset_parameters=backend.open_dataset_parameters,
   (...)    602     decode_coords=decode_coords,
    603 )
    605 overwrite_encoded_chunks = kwargs.pop("overwrite_encoded_chunks", None)
--> 606 backend_ds = backend.open_dataset(
    607     filename_or_obj,
    608     drop_variables=drop_variables,
    609     **decoders,
    610     **kwargs,
    611 )
    612 ds = _dataset_from_backend_dataset(
    613     backend_ds,
    614     filename_or_obj,
   (...)    625     **kwargs,
    626 )
    627 return ds

File ~/micromamba/envs/gridding-cookbook-dev/lib/python3.13/site-packages/xarray/backends/netCDF4_.py:758, 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)
    736 def open_dataset(
    737     self,
    738     filename_or_obj: T_PathFileOrDataStore,
   (...)    755     autoclose=False,
    756 ) -> Dataset:
    757     filename_or_obj = _normalize_path(filename_or_obj)
--> 758     store = NetCDF4DataStore.open(
    759         filename_or_obj,
    760         mode=mode,
    761         format=format,
    762         group=group,
    763         clobber=clobber,
    764         diskless=diskless,
    765         persist=persist,
    766         auto_complex=auto_complex,
    767         lock=lock,
    768         autoclose=autoclose,
    769     )
    771     store_entrypoint = StoreBackendEntrypoint()
    772     with close_on_error(store):

File ~/micromamba/envs/gridding-cookbook-dev/lib/python3.13/site-packages/xarray/backends/netCDF4_.py:525, in NetCDF4DataStore.open(cls, filename, mode, format, group, clobber, diskless, persist, auto_complex, lock, lock_maker, autoclose)
    521 else:
    522     manager = CachingFileManager(
    523         netCDF4.Dataset, filename, mode=mode, kwargs=kwargs
    524     )
--> 525 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:429, in NetCDF4DataStore.__init__(self, manager, group, mode, lock, autoclose)
    427 self._group = group
    428 self._mode = mode
--> 429 self.format = self.ds.data_model
    430 self._filename = self.ds.filepath()
    431 self.is_remote = is_remote_uri(self._filename)

File ~/micromamba/envs/gridding-cookbook-dev/lib/python3.13/site-packages/xarray/backends/netCDF4_.py:534, in NetCDF4DataStore.ds(self)
    532 @property
    533 def ds(self):
--> 534     return self._acquire()

File ~/micromamba/envs/gridding-cookbook-dev/lib/python3.13/site-packages/xarray/backends/netCDF4_.py:528, in NetCDF4DataStore._acquire(self, needs_lock)
    527 def _acquire(self, needs_lock=True):
--> 528     with self._manager.acquire_context(needs_lock) as root:
    529         ds = _nc4_require_group(root, self._group, self._mode)
    530     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:207, in CachingFileManager.acquire_context(self, needs_lock)
    204 @contextmanager
    205 def acquire_context(self, needs_lock: bool = True) -> Iterator[T_File]:
    206     """Context manager for acquiring a file."""
--> 207     file, cached = self._acquire_with_cache_info(needs_lock)
    208     try:
    209         yield file

File ~/micromamba/envs/gridding-cookbook-dev/lib/python3.13/site-packages/xarray/backends/file_manager.py:225, in CachingFileManager._acquire_with_cache_info(self, needs_lock)
    223     kwargs = kwargs.copy()
    224     kwargs["mode"] = self._mode
--> 225 file = self._opener(*self._args, **kwargs)
    226 if self._mode == "w":
    227     # ensure file doesn't get overridden when opened again
    228     self._mode = "a"

File src/netCDF4/_netCDF4.pyx:2517, in netCDF4._netCDF4.Dataset.__init__()

File src/netCDF4/_netCDF4.pyx:2154, 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.