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     : 2.3.4
xarray    : 2025.10.1
matplotlib: 3.10.7
pandas    : 2.3.3
sys       : 3.13.9 | packaged by conda-forge | (main, Oct 22 2025, 23:33:35) [GCC 14.3.0]
appdirs   : 1.4.4
pyresample: 1.34.2
dask      : 2025.10.0

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: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)), '87010e28-937d-4870-a2c3-3aa3aee2f74b']

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:596, 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)
    584 decoders = _resolve_decoders_kwargs(
    585     decode_cf,
    586     open_backend_dataset_parameters=backend.open_dataset_parameters,
   (...)    592     decode_coords=decode_coords,
    593 )
    595 overwrite_encoded_chunks = kwargs.pop("overwrite_encoded_chunks", None)
--> 596 backend_ds = backend.open_dataset(
    597     filename_or_obj,
    598     drop_variables=drop_variables,
    599     **decoders,
    600     **kwargs,
    601 )
    602 ds = _dataset_from_backend_dataset(
    603     backend_ds,
    604     filename_or_obj,
   (...)    615     **kwargs,
    616 )
    617 return ds

File ~/micromamba/envs/gridding-cookbook-dev/lib/python3.13/site-packages/xarray/backends/netCDF4_.py:744, 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)
    722 def open_dataset(
    723     self,
    724     filename_or_obj: T_PathFileOrDataStore,
   (...)    741     autoclose=False,
    742 ) -> Dataset:
    743     filename_or_obj = _normalize_path(filename_or_obj)
--> 744     store = NetCDF4DataStore.open(
    745         filename_or_obj,
    746         mode=mode,
    747         format=format,
    748         group=group,
    749         clobber=clobber,
    750         diskless=diskless,
    751         persist=persist,
    752         auto_complex=auto_complex,
    753         lock=lock,
    754         autoclose=autoclose,
    755     )
    757     store_entrypoint = StoreBackendEntrypoint()
    758     with close_on_error(store):

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

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

File ~/micromamba/envs/gridding-cookbook-dev/lib/python3.13/site-packages/xarray/backends/netCDF4_.py:527, in NetCDF4DataStore._acquire(self, needs_lock)
    526 def _acquire(self, needs_lock=True):
--> 527     with self._manager.acquire_context(needs_lock) as root:
    528         ds = _nc4_require_group(root, self._group, self._mode)
    529     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.

re(Gridding)

Introduction to Verde