Hu Ning, Fu Jiaolan, Sun Jun, Zhang Feng, Hu Yi, Zhang Yani, Li Xiaolan, Tao Yiwei. 2021. Errors in the forecast of precipitation type transition in an extreme winter precipitation event in Beijing. Acta Meteorologica Sinica, 79(2):328-339. DOI: 10.11676/qxxb2021.019
Citation: Hu Ning, Fu Jiaolan, Sun Jun, Zhang Feng, Hu Yi, Zhang Yani, Li Xiaolan, Tao Yiwei. 2021. Errors in the forecast of precipitation type transition in an extreme winter precipitation event in Beijing. Acta Meteorologica Sinica, 79(2):328-339. DOI: 10.11676/qxxb2021.019

Errors in the forecast of precipitation type transition in an extreme winter precipitation event in Beijing

  • Based on both conventional and unconventional observations as well as reanalysis data, a case study of the mixed rain-snow storm that occurred in February 2020 over Beijing was conducted. This study aims to explore the mechanism for the formation of the extreme precipitation event and analyze errors in the forecast of precipitation type and their possible reasons. The result indicates that: (1) the slow moving of the extremely strong and deep low vortex resulted in the persistent precipitation event that lasted for up to 12 h. The anomalous southeasterly jet transported water vapor to the east of the mountainous area in western Beijing, which, combined with strong vertical shear, formed symmetric instability that was conductive to slantwise convective precipitation with high precipitating efficiency rarely occurring in winter night. The above two factors jointly contributed to this extreme rain-snow event; (2) in the early morning, the 0℃ level height and surface temperature decreased slowly. The cold air mass from Northeast Hebei exerted earlier and stronger influence on eastern Beijing, resulting in lower 0℃ level height and thus earlier rain-snow phase transition there; (3) the influence of cold air mass from Northeast Hebei predicted by the model was earlier and stronger than observations, causing a stable stratiform precipitation in the prediction while convection was significantly weaker than observations. The model predicted surface temperature was lower than observations, and the 0℃ level height decreased more rapidly than observations. As a result, the predicted rain-snow transition occurred earlier with higher snowfall and snow depth. Verification of the model predicted temperature profile against unconventional observations provided helpful information for correcting model forecasting errors in precipitation type transition.
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