The Radar Echo Classifier (REC) uses fuzzy-logic techniques to determine the type of scatterer measured by the WSR-88D. Currently, three algorithms have been designed and tested: the AP detection algorithm (APDA) locates anomalously-propagated (AP) ground clutter return, the precipitation detection algorithm (PDA) determines convective and stratiform precipitation regions, and the insect clear air detection algorithm (ICADA) defines return from insects in the boundary layer. These algorithms have been developed using data from WSR-88D systems located across the USA and from various field campaigns of the NCAR S-Pol polarimetric radar.
Expert users of the WSR-88D data provided the "truth" data sets used to optimize the algorithm performances. For the S-Pol data sets, the polarimetric variables are input into a fuzzy logic polarimetric identification (PID) algorithm to determine the type of radar echo return that is present. The PID output is used as the "truth" field for optimization of algorithm performance. Results will be presented and statistical estimates of performance shown.