Microphysical Characteristics of Super Typhoon Lekima (2019) and Its Impacts on Polarimetric Radar Remote Sensing of Precipitation

Abstract. The complex precipitation microphysics associated with super typhoon Lekima (2019) and its potential impacts on the consistency of multi-source datasets and radar quantitative precipitation estimation has been disentangled using a suite of in situ and remote sensing observations around the disastrous waterlogging area near the groove windward slope (GWS) of Yan Dang Mountain and Kuo Cang Mountain, China. The dynamic microphysical processes, in which breakup overwhelms over coalescence as the main outcome of the collision of precipitation particles, noticeably changes the self-consistency between radar reflectivity (Z_H), differential reflectivity (Z_DR) and the specific differential phase (K_DP), and their consistency with theoretical counterparts simulated with surface disdrometer measurements, which are quality-controlled in terms of fall velocity characteristics of different hydrometeors to remove wind effects, hailstones and graupels. The overwhelming breakup accounts for phenomenon that high concentration rather than size contributes more to large Z_H of the storm and the large deviation of attenuation-corrected Z_DR from its expected values (Ẑ_DR). As a result, although a comparable performance of Z_H-based rainfall estimates R() and K_DP-based rainfall estimates R(K_DP) can be achieved, R(Z_H, Z_DR) tends to overestimate precipitation. R(Z_H, Ẑ_DR) performs the best among all rainfall estimators and it is less sensitive to the potential microphysical processes, owning to the improved self-consistency between radar-measured Z_H, Z_DR and K_DP and their consistency with surface counterparts.