Hydrometeors Classification Using Fuzzy Logic for Cloud Radars

Abstract

A new synthesis of information forming the foundation for rule-based systems to deduce dominant bulk hydrometeor types and amounts using polarimetric radar data is presented. The relations are expressed as boundaries and thresholds in a space of polarimetric radar variables. Thus, the foundation is laid out for identification of hydrometeor types (species), estimation of characteristics of hydrometeor species (concentrations, shapes, sizes, and orientations) and quantification of bulk hydrometeor contents (amounts). This study presents a methodology to readily adapt and tune fuzzy logic algorithms using polarimetric observations. Because the design of the weighting functions is based entirely on observations, this method may be applied in the tropics or mid-latitudes at X-, C-, S-, or Ka-band wavelengths.