Evaluation of Cloud Microphysics for All-Sky Radiance Simulation During Two Typical Heavy Rainfall Events in South China

Evaluating and understanding the accuracy of cloud microphysical (MP) schemes in numerical weather pre-diction (NWP) models is crucial for assimilating satellite radiance data under cloudy conditions. This study leverages surface observations, radar reflectivity data, and Himawari-8 satellite radiance data from both water vapor and window channels to assess the performance of four prevalent cloud MP schemes: WSM6, WDM6, Thompson, and Morrison, as implemented in the Weather Research and Forecasting (WRF) model. The assessment focuses on two typical heavy rain events in South China: a warm-sector torrential rainfall (WSTR) event and a squall line (SL) event. The findings reveal that the cloud MP schemes exhibit varying levels of accuracy across the two events. Notably, for the WSTR event, the WDM6 scheme shows the closest alignment with observed rainfall in terms of precipitation forecast. In contrast, the Thompson scheme outperforms the others during the SL event. The simulation of infrared (IR) radiance data from cloud and rain areas remains a significant challenge, particularly for ice clouds, which exhibit greater forecast uncertainty compared to water clouds. Identifying the optimal scheme for describing the full cloud process during rainfall events remains challenging among the evaluated MP schemes. Specifically, the WDM6 scheme stands out in forecasting clear skies and water clouds, while the Morrison and Thompson schemes are found to be more adept at predicting ice clouds. The discrepancies observed between the accuracy of precipitation forecast and cloud prediction highlight the need for further research to identify an MP scheme that effectively balances precipitation forecast with accurate cloudy radiative transfer (RT) si-mulation for data assimilation (DA). This research offers valuable insights into the selection of cloud microphysics parameterization schemes for all-sky radiance assimilation, particularly under diverse rainfall processes.