Cloud Microphysics Retrieval Using S-band Dual-Polarization Radar Measurements

TLDR

Polarimetric radar observables can discriminate hydrometeor particle types, but overlapping values make the problem suitable for fuzzy logic. The study develops a real‑time fuzzy logic algorithm for hydrometeor particle identification. The algorithm is a simple fuzzy logic system designed for real‑time operation, with plans for further verification and optimization. Initial results are encouraging despite the lack of in situ verification.

Abstract

Recent studies have shown the utility of polarimetric radar observables and derived fields for discrimination of hydrometeor particle types. Because the values of the radar observables that delineate different particle types overlap and are not sharply defined, the problem is well suited for a fuzzy logic approach. In this preliminary study the authors have developed and implemented a fuzzy logic algorithm for hydrometeor particle identification that is simple and efficient enough to run in real time for operational use. Although there are no in situ measurements available for this particle-type verification, the initial results are encouraging. Plans for further verification and optimization of the algorithm are described.