Minimizing the impact of ground-clutter filtering along the zero-isodop in polarimetric Doppler weather radars

Modern ground clutter mitigation techniques automate the removal of ground clutter contamination from meteorological estimates allowing radar operators to focus on more vital roles such as the diagnoses of structure and potential impacts of weather events. For Doppler weather radars, ground clutter signals exhibit both near-zero Doppler velocities and narrow spectrum widths, characteristics that help with effective identification and filtering. However, weather signals that exhibit similar characteristics may be miss-identified as ground clutter contamination and thus become severely attenuated by the filtering process. Partial recovery of the weather signal lost in the ground-clutter-filtering process is possible with modern filters that interpolate through the filter notch. Still, it would be best to avoid the filtering process altogether if weather-only signals could be effectively identified. The use of dual-polarization variables may assist in the discrimination of ground clutter signals from narrow spectrum width weather signals along the zero-isodop (i.e., with near zero Doppler velocity). In this paper, we combine these discriminating properties of polarimetric Doppler weather radars to provide improved ground clutter mitigation. The performance of the proposed algorithm will be shown using archived WSR-88D polarimetric time-series data.