Physically based rain estimation using polarimetric radar measurements

Abstract

Polarimetric radar has been successful in characterizing cloud and precipitation. Polarization parameters such as radar reflectivity (Z), differential reflectivity (Z_DR), linear reflectivity difference (Z_DP), and specific differential propagation phase shift (K_DP) provide more information about precipitation and allow better characterization of hydrometeors, accurate rain rate estimation, and retrieval of rain drop size distribution (DSD). In the past, rain rate (R) estimation from S-Pol was based on empirical models such as Z-R, R (Z, Z_DR) and R (K_DP) relations, which were derived from regression analyses of radar and rain gauge measurements or numerical simulations, and are prone to errors. In this paper, we derive various rain estimators using a physically-based raindrop size distribution (DSD) model: constrained Gamma DSD. The constrain condition, the shape-slope relation in Gamma DSD, is derived from video-disdrometer observations and has been shown to represent a physical nature of rain and useful in rain DSD retrievals from remote measurements. The relation is then used to retrieve rain DSDs from two remote measurements and t derive rain estimators from polarimetric radar measurements. The derived rain estimators are then used to retrieve rain parameters from S-pol measurements. The results are also verified and compared with ground measurements.