Regridding schemes#

Iris natively supports data regridding with its iris.cube.Cube.regrid() method and a set of predefined regridding schemes provided in the analysis module (further details are given on this page). Here, further regridding schemes are provided that are compatible with iris.cube.Cube.regrid().

Example:

from esmvalcore.preprocessor.regrid_schemes import ESMPyAreaWeighted

regridded_cube = cube.regrid(target_grid, ESMPyAreaWeighted())

Regridding schemes.

Classes:

`ESMPyAreaWeighted`([mask_threshold])	ESMPy area-weighted regridding scheme.
`ESMPyLinear`([mask_threshold])	ESMPy bilinear regridding scheme.
`ESMPyNearest`([mask_threshold])	ESMPy nearest-neighbor regridding scheme.
`ESMPyRegridder`(src_cube, tgt_cube[, method, ...])	General ESMPy regridder.
`GenericFuncScheme`(func, **kwargs)	Regridding with a generic function.
`GenericRegridder`(src_cube, tgt_cube, func, ...)	Generic function regridder.
`UnstructuredLinear`()	Unstructured bilinear regridding scheme.
`UnstructuredLinearRegridder`(src_cube, tgt_cube)	Unstructured bilinear regridder.
`UnstructuredNearest`()	Unstructured nearest-neighbor regridding scheme.
`xESMF`(**kwargs)	xESMF regridding scheme.
`xESMFRegridder`(src_cube, tgt_cube, **kwargs)	xESMF regridding function.

class esmvalcore.preprocessor.regrid_schemes.ESMPyAreaWeighted(mask_threshold: float = 0.99)[source]#

ESMPy area-weighted regridding scheme.

This class can be used in iris.cube.Cube.regrid().

Does not support lazy regridding.

Methods:

regridder(src_cube, tgt_cube)

Get regridder.

Parameters:: mask_threshold (float)

regridder(src_cube: Cube, tgt_cube: Cube) → ESMPyRegridder#

Get regridder.

Parameters:

src_cube (Cube) – Cube defining the source grid.
tgt_cube (Cube) – Cube defining the target grid.

Returns:

Regridder instance.

Return type:

ESMPyRegridder

class esmvalcore.preprocessor.regrid_schemes.ESMPyLinear(mask_threshold: float = 0.99)[source]#

ESMPy bilinear regridding scheme.

This class can be used in iris.cube.Cube.regrid().

Does not support lazy regridding.

Methods:

regridder(src_cube, tgt_cube)

Get regridder.

Parameters:: mask_threshold (float)

regridder(src_cube: Cube, tgt_cube: Cube) → ESMPyRegridder#

Get regridder.

Parameters:

src_cube (Cube) – Cube defining the source grid.
tgt_cube (Cube) – Cube defining the target grid.

Returns:

Regridder instance.

Return type:

ESMPyRegridder

class esmvalcore.preprocessor.regrid_schemes.ESMPyNearest(mask_threshold: float = 0.99)[source]#

ESMPy nearest-neighbor regridding scheme.

This class can be used in iris.cube.Cube.regrid().

Does not support lazy regridding.

Methods:

regridder(src_cube, tgt_cube)

Get regridder.

Parameters:: mask_threshold (float)

regridder(src_cube: Cube, tgt_cube: Cube) → ESMPyRegridder#

Get regridder.

Parameters:

src_cube (Cube) – Cube defining the source grid.
tgt_cube (Cube) – Cube defining the target grid.

Returns:

Regridder instance.

Return type:

ESMPyRegridder

class esmvalcore.preprocessor.regrid_schemes.ESMPyRegridder(src_cube: Cube, tgt_cube: Cube, method: str = 'linear', mask_threshold: float = 0.99)[source]#

General ESMPy regridder.

Does not support lazy regridding nor weights caching.

Parameters:

src_cube (Cube) – Cube defining the source grid.
tgt_cube (Cube) – Cube defining the target grid.
method (str) – Regridding algorithm. Must be one of linear, area_weighted, nearest.
mask_threshold (float) – Threshold used to regrid mask of input cube.

class esmvalcore.preprocessor.regrid_schemes.GenericFuncScheme(func: Callable, **kwargs)[source]#

Regridding with a generic function.

This class can be used in iris.cube.Cube.regrid().

Does support lazy regridding if func does.

Parameters:

func (Callable) – Generic regridding function with signature f(src_cube: Cube, grid_cube: Cube, **kwargs) -> Cube.
**kwargs – Keyword arguments for the generic regridding function.

Methods:

regridder(src_cube, tgt_cube)

Get regridder.

regridder(src_cube: Cube, tgt_cube: Cube) → GenericRegridder[source]#

Get regridder.

Parameters:

src_cube (Cube) – Cube defining the source grid.
tgt_cube (Cube) – Cube defining the target grid.

Returns:

Regridder instance.

Return type:

GenericRegridder

class esmvalcore.preprocessor.regrid_schemes.GenericRegridder(src_cube: Cube, tgt_cube: Cube, func: Callable, **kwargs)[source]#

Generic function regridder.

Does support lazy regridding if func does. Does not support weights caching.

Parameters:

src_cube (Cube) – Cube defining the source grid.
tgt_cube (Cube) – Cube defining the target grid.
func (Callable) – Generic regridding function with signature f(src_cube: Cube, grid_cube: Cube, **kwargs) -> Cube.
**kwargs – Keyword arguments for the generic regridding function.

class esmvalcore.preprocessor.regrid_schemes.UnstructuredLinear[source]#

Unstructured bilinear regridding scheme.

This class can be used in iris.cube.Cube.regrid().

Supports lazy regridding.

Warning

This will drop all cell measures, ancillary variables and aux factories, and any auxiliary coordinate that spans the dimension of the unstrucutred grid.

Methods:

regridder(src_cube, tgt_cube)

Get regridder.

regridder(src_cube: Cube, tgt_cube: Cube) → UnstructuredLinearRegridder[source]#

Get regridder.

Parameters:

src_cube (Cube) – Cube defining the source grid.
tgt_cube (Cube) – Cube defining the target grid.

Returns:

Regridder instance.

Return type:

UnstructuredLinearRegridder

class esmvalcore.preprocessor.regrid_schemes.UnstructuredLinearRegridder(src_cube: Cube, tgt_cube: Cube)[source]#

Unstructured bilinear regridder.

Supports lazy regridding and weights caching.

Warning

This will drop all cell measures, ancillary variables and aux factories, and any auxiliary coordinate that spans the dimension of the unstrucutred grid.

Parameters:

src_cube (Cube) – Cube defining the source grid.
tgt_cube (Cube) – Cube defining the target grid.

class esmvalcore.preprocessor.regrid_schemes.UnstructuredNearest[source]#

Unstructured nearest-neighbor regridding scheme.

This class is a wrapper around iris.analysis.UnstructuredNearest that removes any additional X or Y coordinates prior to regridding if necessary. It can be used in iris.cube.Cube.regrid().

Methods:

regridder(src_cube, tgt_cube)

Get regridder.

regridder(src_cube: Cube, tgt_cube: Cube) → UnstructuredNearestNeigbourRegridder[source]#

Get regridder.

Parameters:

src_cube (Cube) – Cube defining the source grid.
tgt_cube (Cube) – Cube defining the target grid.

Returns:

Regridder instance.

Return type:

UnstructuredNearestNeigbourRegridder

class esmvalcore.preprocessor.regrid_schemes.xESMF(**kwargs)[source]#

xESMF regridding scheme.

This is a wrapper around xesmf.frontend.Regridder so it can be used in iris.cube.Cube.regrid(). It uses the ncdata package to convert the iris.cube.Cube to an xarray.Dataset before regridding and back after regridding.

Supports lazy regridding.

Masks are converted to numpy.nan before regridding and converted back to masks after regridding.

Parameters:: **kwargs – Any keyword argument to xesmf.frontend.Regridder or xesmf.frontend.Regridder.__call__() can be provided. By default, the arguments ignore_degenerate=True, keep_attrs=True, skipna=True, and unmapped_to_nan=True will be used.

kwargs#: Keyword arguments that will be provided to the regridder.

Methods:

regridder(src_cube, tgt_cube)

Create xESMF regridding function.

regridder(src_cube: Cube, tgt_cube: Cube) → xESMFRegridder[source]#

Create xESMF regridding function.

Parameters:

src_cube (Cube) – Cube defining the source grid.
tgt_cube (Cube) – Cube defining the target grid.

Returns:

xESMF regridding function.

Return type:

xESMFRegridder

class esmvalcore.preprocessor.regrid_schemes.xESMFRegridder(src_cube: Cube, tgt_cube: Cube, **kwargs)[source]#

xESMF regridding function.

This is a wrapper around xesmf.frontend.Regridder so it can be used in iris.cube.Cube.regrid().

Supports lazy regridding.

Parameters:

src_cube (Cube) – Cube describing the source grid.
tgt_cube (Cube) – Cube describing the target grid.
**kwargs – Any keyword argument to xesmf.frontend.Regridder or xesmf.frontend.Regridder.__call__() can be provided.

kwargs#: Keyword arguments to xesmf.frontend.Regridder.

default_call_kwargs#: Default keyword arguments to xesmf.frontend.Regridder.__call__().