pyart.retrieve.kdp_schneebeli#

pyart.retrieve.kdp_schneebeli(radar, gatefilter=None, fill_value=None, psidp_field=None, kdp_field=None, phidp_field=None, band='C', rcov=0, pcov=0, prefilter_psidp=False, filter_opt=None, parallel=True)[source]#

Estimates Kdp with the Kalman filter method by Schneebeli and al. (2014) for a set of psidp measurements.

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.

  • band (char, optional) – Radar frequency band string. Accepted “X”, “C”, “S” (capital or not). The band is used to compute intercepts -c and slope b of the delta = b*Kdp+c relation.

  • rcov (3x3 float array, optional) – Measurement error covariance matrix.

  • pcov (4x4 float array, optional) – Scaled state transition error covariance matrix.

  • prefilter_psidp (bool, optional) – If set, the psidp measurements will first be filtered with the filter_psidp method, which can improve the quality of the final Kdp.

  • filter_opt (dict, optional) – The arguments for the prefilter_psidp method, if empty, the defaults arguments of this method will be used.

  • parallel (bool, optional) – Flag to enable parallel computation (one core for every psidp profile).

Returns:

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

  • kdp_std_dict (dict) – Estimated specific differential phase standard dev. data and metadata.

  • phidpr_dict, (dict) – Retrieved differential phase data and metadata.

References

Schneebeli, M., Grazioli, J., and Berne, A.: Improved Estimation of the Specific Differential Phase SHIFT Using a Compilation of Kalman Filter Ensembles, IEEE T. Geosci. Remote Sens., 52, 5137-5149, doi:10.1109/TGRS.2013.2287017, 2014.

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