Radar Simulation Studies for Hydrometeor Classification from Range Profile of Polarimetric Radar Signatures

Hydrometeor classification is critical for accurate estimate of precipitation fall rate from radar. In particular, detailed classification method is needed for mixed-phased precipitation. Many hydrometeor classification methods have been developed, however, there are still needs for improvements, in particular for mixed-phased precipitation. In the previous conference on Radar Meteorology, we presented a method for rain and dry snow classification for the dual-frequency precipitation radar (DPR) equipped on the Global Precipitation Mission. In the method, values of radar signals were not directly used but the increase/decrease tendencies of signals in range profile are used. The dual frequency ratio (DFR) which is defined as a ratio of the equivalent radar reflectivity at Ku-band and at Ka-band, monotonically increases with radar range for rain because of the difference in attenuation between Ku and Ka-band. While for dry snow, the DFR should be constant for homogeneous snow range region because of less attenuation. This different propertie in the range profile can be used for classification. Similar method can be applied for polarimetric radar. The specific differential attenuation, which is defined as a difference of the specific attenuation between horizontal and vertical polarization, increases as rain rate increases. The differential radar reflectivity, therefore, should increases with path integrated Ze for rain of constant rain rate. For dry snow and hail, this feature may not appear. In the present study, we focused on the attenuation effects on the polarimetric signatures and made simulations for radar-received signals in rain and dry snow conditions for X and C-band radars. Based on the results of simulation, we propose a method for hydrometeor classification from range profiles of the polarimetric signatures for polarimetric radar.