wradlib.clutter.filter_cloudtype#

wradlib.clutter.filter_cloudtype(img, cloud, thrs=0, snow=False, low=False, cirrus=False, smoothing=None, grid='polar', scale=None)[source]#

Identification of non-meteorological echoes based on cloud type.

Parameters:

  • img (numpy.ndarray) – radar image to which the filter is to be applied

  • cloud (numpy.ndarray) – image with collocated cloud value from MSG SAFNWC PGE02 product

  • thrs (float) – Threshold above which to identify clutter

  • snow (bool) – Switch to use PGE02 class “land/sea snow” for clutter identification

  • low (bool) – Switch to use PGE02 class very low stratus, very low cumulus and low cumulus for clutter identification

  • cirrus (bool) – Switch to use PGE02 class “very thin cirrus” and “fractional clouds” for clutter identification

  • smoothing (float) – Size [m] of the smoothing window used to take into account various localisation errors (e.g. advection, parallax)

  • grid (str) – “polar” or “cartesian”

  • scale (float or tuple) – float or tuple of 2 floats range [m] scale for polar grid x[m] and y[m] scale for cartesian grid

Returns:

output (numpy.ndarray) – a boolean array containing TRUE where clutter has been identified.