pyart.retrieve.kdp_operational_mch#

pyart.retrieve.kdp_operational_mch(radar, gatefilter=None, fill_value=None, psidp_field=None, kdp_field=None, windsize=3)#

Estimates Kdp with the Vulpiani method for a 2D array of psidp measurements with the first dimension being the distance from radar and the second dimension being the angles (azimuths for PPI, elev for RHI).The input psidp is assumed to be pre-filtered (for ex. with the filter_psidp function)

Parameters:

  • radar (Radar) – Radar containing differential phase field.

  • gatefilter (GateFilter, optional) – A GateFilter indicating radar gates that should be excluded when analysing differential phase measurements.

  • fill_value (float, optional) – Value indicating missing or bad data in differential phase field, if not specified, the default in the Py-ART configuration file will be used

  • psidp_field (str, optional) – Total differential phase field. If None, the default field name must be specified in the Py-ART configuration file.

  • kdp_field (str, optional) – Specific differential phase field. If None, the default field name must be specified in the Py-ART configuration file.

  • phidp_field (str, optional) – Propagation differential phase field. If None, the default field name must be specified in the Py-ART configuration file.

  • windsize (int, optional) – Size in # of gates of the range derivative window. Should be even.

Returns:

kdp_dict (dict) – Retrieved specific differential phase data and metadata.

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