A Thunderstorm Gale Forecast Method Based on the Objective Classification and Continuous Probability
Yinglian Guo; Min Zhong; Xuan Chen; Zhimin Zhou; Guirong Xu; Guanyu Xu; Liangpeng Dong
Potential prediction is an important research content of thunderstorm gale weather forecast, and it is still a challenge because the environmental field of thunderstorm gale presents different characteristics under different weather conditions. Using the 12-year thunderstorm gale data of Hubei province in central China and the reanalysis data of National Center for Environmental Prediction (NCEP), this study analyzed the percentile distribution of environmental physical quantities of thunderstorm gale, and the continuous probability method was adopted to establish the probability forecast models of thunderstorm gale in four different types of weather situation, which are in the rear of trough type, in front of trough type, in the periphery of the western Pacific subtropical high type and easterly airflow type. Finally, probability prediction was realized by objective classification criterion in operation. The results show that the method based on objective classification and continuous probability can significantly improve the probability of thunderstorm gale detection, and also reduce the missing alarm rate of thunderstorm gale. Moreover, the quantitative test of 16 weather processes under four types of weather situations also shows that the continuous probability method has a higher probability of detection than the bisection method, and significantly reduces the missing alarm of extreme wind by the bisection method.
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