Direct Assimilation of Dual-polarization Radar Using Hydrometeor Background Error Covariance in CMA-MESO and Microphysics Scheme Sensitivity

Numerical models play an important role in convective-scale forecasting, and dual-polarization radar observations can provide detailed microphysical data. In this study, we implemented a direct assimilation operator for dual-polarization radar data using the hydro-meteor background error covariance (HBEC) in China Meteorological Administration ME-SO-scale weather forecasting system (CMA-MESO, formerly GRAPES-MESO), and conducted assimilation and forecasting experiments with X-band and S-band dual-polarization radar data on two cases. The results indicated that the direct assimilation of du-al-polarization radar data enhanced the microphysical fields and the thermodynamic struc-ture of convective systems to some extent based on the HBEC, thereby improving precipi-tation forecasts. Among the sensitivity tests of microphysical parameterization schemes, including the Liuma scheme, the Thompson scheme, and the WSM6 scheme (WRF Single-Moment 6-class), it was found that the larger improvement in the equivalent potential tem-perature, relative humidity, wind, and accumulated precipitation forecasts occurred in the experiment using the WSM6 scheme as the distribution of solid precipitation particles was closer to the hydrometeor classification algorithm from dual-polarization radar observations in our cases.