Hydrometeor classification system using dual-polarization radar measurements

Abstract

Hydrometeor classification system using fuzzy logic technique based on dual-polarization radar measurements is presented. In this study, five radar measurements (horizontal reflectivity, differential reflectivity, specific differential phase, correlation coefficient, and linear depolarization ratio), and height relating to environmental melting level are used as input variables of the system. The hydrometeor classification system chooses one of nine different hydrometeor categories as output. The system presented in this paper is a further development of an existing hydrometeor classification system model developed at Colorado State University. The hydrometeor classification system is evaluated by comparison against the in situ sample data collected by instrumentation on T-28 aircraft during Severe Thunderstorm Electrification and Precipitation Study (STEPS).