wrf.smooth2d¶

wrf.smooth2d(field, passes, cenweight=2.0, meta=True)¶

Return the field smoothed.

The smoothing kernel applied is:

\[\begin{split}\frac{1}{4 + cenweight} * \begin{bmatrix} 0 & 1 & 0 \\ 1 & cenweight & 1 \\ 0 & 1 & 0 \end{bmatrix}\end{split}\]

Data values along the borders are left unchanged. This routine does not modify the original data supplied by the field parameter..

If you need more general purpose multidimensional filtering tools, try the scipy.ndimage.convolve() method.

Parameters:	field (`xarray.DataArray` or `numpy.ndarray`) – The field to smooth, which must be at least two dimensions. Missing/fill values will be ignored as long as the type is either a `numpy.ma.MaskedArray` or a `xarray.DataArray` with a _FillValue attribute. passes (`int`) – The number of smoothing passes. cenweight (`float`, optional) – The weight to apply to the center of the smoothing kernel. Default is 2.0. meta (`bool`) – Set to False to disable metadata and return `numpy.ndarray` instead of `xarray.DataArray`. Default is True.
Returns:	The smoothed field. If xarray is enabled and the meta parameter is True, then the result will be an `xarray.DataArray` object. Otherwise, the result will be either a `numpy.ndarray` or a `numpy.ma.MaskedArray` depending on the type for field.
Return type:	`xarray.DataArray`, `numpy.ma.MaskedArray` or `numpy.ndarray`)