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

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Abstract

The Sichuan-**zang 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-**zang 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.

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Acknowledgements

This work was supported by the Second Tibetan Plateau Scientific Expedition and Research (STEP) Program (Grant No. 2019QZKK0105), the Key Project of the National Natural Science Foundation of China (Grant No. 42030611), the National Key Research and Development Program of China (Grant No. 2022YFC3003903), the National Natural Science Foundation of China (Grant Nos. 42205072 & 42305083), the Basic Research Fund of Chinese Academy of Meteorological Sciences (Grant No. 2022Y024), and the Key Research and Development Program of Science and Technology Department of Sichuan Province (Grant No. 2022YFS0540).

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Authors and Affiliations

  1. China Meteorological Administration Transportation Meteorology Key Laboratory, Nan**g Joint Institute for Atmospheric Sciences, Nan**g, 210041, China

    **aoqi Xu

  2. Heavy Rain and Drought-Flood Disasters in Plateau and Basin Key Laboratory of Sichuan Province, Institute of Plateau Meteorology, CMA, Chengdu, 610072, China

    Zhiwei Heng, Yueqing Li, Shunjiu Wang & Peiwen Zhang

  3. State Key Laboratory of Disaster Weather, Chinese Academy of Meteorological Sciences, Bei**g, 100081, China

    Jian Li

  4. Collaborative Innovation Center for Western Ecological Safety, Lanzhou University, Lanzhou, 730000, China

    Yuan Wang

  5. China Meteorological Administration Aerosol-Cloud and Precipitation Key Laboratory and Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nan**g University of Information Science and Technology, Nan**g, 210044, China

    **ghua Chen & Chunsong Lu

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  1. **aoqi Xu
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Xu, X., Heng, Z., Li, Y. et al. Improvement of cloud microphysical parameterization and its advantages in simulating precipitation along the Sichuan-**zang Railway. Sci. China Earth Sci. 67, 856–873 (2024). https://doi.org/10.1007/s11430-023-1247-2

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