A study of the 22 July 2024 torrential rain in eastern Gansu using a convection-permitting model

Forecasting the spatial extent and intensity of summer rainstorms in Northwest China poses significant challenges for convection-permitting models. In this study, the convection-permitting model CMA-LZ (China Meteorological Administration Lanzhou) is driven by initial and boundary conditions from the National Centers for Environmental Prediction Global Forecast System (NCEP-GFS) and the China Meteorological Administration Global Forecast System (CMA-GFS). Three cloud microphysics schemes—WSM6, LIU-MA, and Thompson are employed to simulate a rainstorm event occurring on 22 July 2024 in eastern Gansu Province and the results are verified. It is found that the CMA-LZ model initialized with the CMA-GFS data can successfully predict the spatial coverage and intensity of the precipitation event. The LIU-MA microphysics scheme outperforms WSM6 and Thompson in the forecast of rainfall distribution and intensity. Furthermore, the LIU-MA scheme yields higher TS (Threat Score) and ACC (Accuracy) scores of 24 h precipitation forecast compared to the other two schemes. Although the LIU-MA scheme slightly over predicts the rainstorm, it provides more accurate forecasts for light, moderate, and heavy rain based on verification against observations. Microphysical analysis reveals that the LIU-MA scheme produces higher concentrations of rain water, cloud water, and graupel particles than the other schemes, creating a more favorable condition for precipitation enhancement. In conclusion, the CMA-LZ model initialized with CMA-GFS data at 00: 00 UTC and utilizing the LIU-MA microphysics scheme can accurately predict the summer rainstorm event in eastern Gansu Province.