Mitigating Ground-Clutter Contamination on Polarimetric Doppler Weather Radars

Ground clutter contamination continues to be a prime concern for the weather radar community. The removal of ground-clutter contamination becomes much more important for polarimetric Doppler weather radars given that the polarimetric variables are more susceptible to this contamination. If not effectively mitigated; ground clutter contamination can artificially inflate/deflate quantitative precipitation estimates, adversely affect polarimetric classification algorithms, and obscure Doppler-velocity signatures of weather. Modern ground clutter mitigation techniques automate the removal of ground clutter contamination from radar data by focusing on the characteristics of the ground clutter signals (i.e., near-zero Doppler velocities and narrow spectrum widths). However, weather signals that exhibit similar characteristics may be miss-identified as ground clutter contamination and thus become severely attenuated by the filtering process. Fortunately, the use of dual-polarization information has the potential to assist in the discrimination of ground-clutter signals from narrow-spectrum-width weather signals along the zero-isodop. In this work, we combine the ground clutter mitigation qualities of the Clutter Environment Analysis using Adaptive Processing (CLEAN-AP) filter (Torres and Warde 2014) with the weather discrimination qualities of the Weather Environment Thresholding (WET) algorithm (Warde and Torres 2015) to achieve a more robust and effective mitigation of ground clutter. It is demonstrated that WET can be used to prevent the potentially detrimental application of the CLEAN-AP filter in regions with significant weather signals. The performance of the proposed algorithm is illustrated using several archived WSR-88D polarimetric data cases.