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.

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