AUTHOR=Xing Nan , Zhang Yingxin , Li Sang , Dai Yi , Hao Cui , Li Jing , Zhi Xiefei 

TITLE=The features and probability forecasting of short–duration heavy rainfall in the Beijing-Tianjin-Hebei region caused by North China cold vortices

JOURNAL=Frontiers in Environmental Science

VOLUME=Volume 10 - 2022

YEAR=2023

URL=https://www.frontiersin.org/journals/environmental-science/articles/10.3389/fenvs.2022.1101602

DOI=10.3389/fenvs.2022.1101602

ISSN=2296-665X

ABSTRACT=Based on hourly station precipitation data and ECMWF ERA5 reanalysis data from 2009 to 2019, this paper explores the temporal variations and spatial distribution of short–duration heavy rainfall (SDHR) induced by North China cold vortices (NCCV) over the Beijing-Tianjin-Hebei (BTH) region, and comparatively analyzes the characteristic of environmental parameters and then choose some predictors to make probability forecasting for SDHR induced by NCCV. Results show that SDHR has obviously interannual, monthly and diurnal variations. Areas of high SDHR frequency caused by NCCV exhibit eastward movement, which generally locate along the mountain areas of the BTH region in the afternoon, and moves to the coastal areas of the BTH region after midnight. In general, SDHR induced by NCCV mainly occurs in 16:00–21:00 and around 02:00–05:00, showing a delayed peak time and a secondary peak time in recent years. Besides, SDHR caused by NCCV occurs fewer but more extremely over the northwestern and southern parts of the BTH region, more frequently and extremely over the border area of the BTH region, and more frequently but with moderate intensity over the coastal area of the BTH region. By comparing the distribution characteristics of some physical parameters for three categories of no precipitation, ordinary precipitation, and SDHR weather induced by NCCV, it is found that moisture and atmospheric instability conditions have great significance for the occurrence of SDHR caused by NCCV. Probability forecast for SDHR caused by NCCV is made based on ingredient method and fuzzy logic algorithms. The result shows the products have good performance, further implying the significance of the environmental parameters for forecasting SDHR caused by NCCV.