One of the important advantages of polarimetric weather radars is their ability to discriminate between different types of hydrometeor and non-hydrometeor radar scatterers. Using a fuzzy logic classification algorithm, polarimetric measurands are combined to provide an identification of various hydrometeor types, such as rain, hail, graupel, wet snow, dry snow, and ice crystals of different orientation. These meteorological scatterers can be easily distinguished from non-meteorological targets, such as insects, birds, and ground clutter.

This study focuses on the recent development of a real-time hydrometeor classification algorithm that utilizes data from the NOAA/NSSL 11-cm dual-polarization radar (located in central Oklahoma). The classification algorithm provides information on meteorological and non-meteorological targets that are of interest to aviators, such as hail, rain/snow discrimination, and detection of migratory birds as a potential threat to aviation safety. In the Spring of 2001, a relatively simple version of this real-time algorithm was delivered to forecasters at the National Weather Service Forecast Office in Norman, OK. This paper discusses the development of this algorithm, along with the results of validation work using ground observations and 2D-video-disdrometer measurements.