Improvement of cloud microphysical parameterization and its advantages in simulating precipitation along the Sichuan-Xizang Railway

The Sichuan-Xizang Railway is an important part of the railway network in China, and geological disasters, such as mountain floods and landslides, frequently occur in this region. Precipitation is an important cause of these disasters; therefore, accurate simulation of the precipitation in this region is highly important. In this study, the descriptions for uncertain processes in the cloud microphysics scheme are improved; these processes include cloud droplet activation, cloud-rain autoconversion, rain accretion by cloud droplets, and the entrainment-mixing process. In the default scheme, the cloud water content of different sizes corresponds to the same cloud droplet concentration, which is inconsistent with the actual content; this results in excessive cloud droplet size, unreasonable related conversion rates of microphysical process (such as cloud-rain autoconversion), and an overestimation of precipitation. Our new scheme overcomes the problem of excessive cloud droplet size. The processes of cloudrain autoconversion and rain accretion by cloud droplets are similar to the stochastic collection equation, and the mixing mechanism of cloud droplets is more consistent with that occurred during the actual physical process in the cloud. Based on the new and old schemes, multiple precipitation processes in the flood season of 2021 along the Sichuan-Xizang Railway are simulated, and the results are evaluated using ground observations and satellite data. Compared to the default scheme, the new scheme is more suitable for the simulation of cloud physics, reducing the simulation deviation of the liquid water path and droplet radius from 2 times to less than 1 time and significantly alleviating the overestimation of precipitation intensity and range of precipitation center. The average root-mean-square error is reduced by 22%. Our results can provide a scientific reference for improving precipitation forecasting and disaster prevention in this region.