wradlib.clutter.classify_echo_fuzzy(dat, weights=None, trpz=None, thresh=0.5)

Fuzzy echo classification and clutter identification based on polarimetric moments.

The implementation is based on [Vulpiani et al., 2012]. At the moment, it only distinguishes between meteorological and non-meteorological echos.

Changed in version 1.4.0: The implementation was extended using depolarization ratio (dr) and clutter phase alignment (cpa).

For Clutter Phase Alignment (CPA) see [Hubbert et al., 2009a] and [Hubbert et al., 2009b]

For each decision variable and radar bin, the algorithm uses trapezoidal functions in order to define the membership to the non-meteorological echo class. Based on pre-defined weights, a linear combination of the different degrees of membership is computed. The echo is assumed to be non-meteorological in case the linear combination exceeds a threshold.

At the moment, the following decision variables are considered:

• Texture of differential reflectivity (zdr) (mandatory)
• Texture of correlation coefficient (rho) (mandatory)
• Texture of differential propagation phase (phidp) (mandatory)
• Doppler velocity (dop) (mandatory)
• Static clutter map (map) (mandatory)
texture - texture
depolarization - depolarization ratio