xarray.Dataset.regridder.horizontal#
- Dataset.regridder.horizontal(data_var, output_grid, tool='xesmf', **options)#
Apply horizontal regridding to
data_var
of the currentxr.Dataset
tooutput_grid
.When might
Regrid2
be preferred overxESMF
?If performing conservative regridding from a high/medium resolution lat/lon grid to a coarse lat/lon target,
Regrid2
may provide better results as it assumes grid cells with constant latitudes and longitudes whilexESMF
assumes the cells are connected by Great Circles 1.Supported tools, methods and grids:
- xESMF (https://pangeo-xesmf.readthedocs.io/en/latest/)
Methods:
Bilinear
Conservative
Conservative Normed
Patch
Nearest s2d
Nearest d2s
Grids:
Rectilinear
Curvilinear
Find options at
xcdat.regridder.xesmf.XESMFRegridder()
- Regrid2
Methods:
Conservative
Grids:
Rectilinear
Find options at
xcdat.regridder.regrid2.Regrid2Regridder()
- Parameters
data_var (
str
) – Name of the variable in thexr.Dataset
to regrid.output_grid (
xr.Dataset
) – Dataset containing output grid.tool (
str
) – Name of the regridding tool.**options (
Dict[str
,Any]
) – These options are passed to the tool being used for regridding. See specific regridder documentation for available options.
- Returns
xr.Dataset
– With thedata_var
variable on the grid defined inoutput_grid
.- Raises
ValueError – If tool is not supported.
References
Examples
Create destination grid:
>>> output_grid = xcdat.create_uniform_grid(-90, 90, 4.0, -180, 180, 5.0)
Regrid variable using “xesmf”:
>>> ds.regridder.horizontal("ts", output_grid, tool="xesmf", method="bilinear")
Regrid variable using “regrid2”:
>>> ds.regridder.horizontal("ts", output_grid, tool="regrid2")
Use convenience methods:
>>> ds.regridder.horizontal_xesmf("ts", output_grid, method="bilinear")
>>> ds.regridder.horizontal_regrid2("ts", output_grid)