xarray.Dataset.spatial.mask_land

xarray.Dataset.spatial.mask_land#

Dataset.spatial.mask_land(data_var, method='regionmask', threshold=None, mask=None, output_mask=False, **options)#

Masks a data variable by land.

Parameters:

  • data_var (str) – The key of the data variable to mask.

  • method (str, optional) – The masking method, by default “regionmask”. Supported methods: “regionmask”, “pcmdi”.

  • threshold (float | None, optional) – The threshold used to determine cell classification, values below or equal to this are considered sea, defaults to 0.2.

  • mask (xr.DataArray | None, optional) – A custom mask to apply, by default None. If None, a mask is generated using the specified method.

  • output_mask (bool | str, optional) – If True, returns the mask as a DataArray along with the masked dataset. If a string, the name of the mask variable to add to the dataset. By default False.

  • **options (Any) – These options are passed directly to the method. See specific method documentation for available options: xcdat.mask.pcmdi_land_sea_mask() for PCMDI options.

Returns:

xr.Dataset – The dataset with the data variable masked by land.

Examples

Mask a data variable by land using the default method (regionmask):

>>> ds_masked = ds.spatial.mask_land("tas")

Mask a data variable by land using the PCMDI method with custom threshold:

>>> ds_masked = ds.spatial.mask_land("tas", method="pcmdi", threshold=0.3)

Mask a data variable by land using a custom mask and output the mask:

>>> custom_mask = xr.DataArray(...)  # Define your custom mask here
>>> ds_masked = ds.spatial.mask_land("tas", mask=custom_mask, output_mask=True)

Mask a data variable by land and add the mask to the dataset with a custom name:

>>> ds_masked = ds.spatial.mask_land("tas", output_mask="land_mask")
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