GEP  Vol.7 No.6 , June 2019
Research on Thunderstorm Forecasting in Fuxin, China Based on Physical Diagnostic Parameters
Thunderstorms are very spectacular super-long-range discharge processes in the atmosphere, which can cause tremendous damage in an instant, often leading to casualties, resulting in damage to buildings, power supply systems, communication equipment and forest fires, causing major economic losses. In order to successfully predict thunderstorms, and many economic losses can be avoided. Using the observation data of two county stations in Yimeng County and Zhangwu County from June to August 2009-2015, 40 typical thunderstorm weather processes were selected, and 15 convective parameters related to thunderstorm activities were calculated. After statistical analysis, there are seven convective parameters with significant correlation with thunderstorm activity: convective affective potential energy (CAPE), 850 hPa specific humidity, 700 hPa specific humidity, 850 hPa false equivalent temperature, maximum rising speed, strong weather threat index (SWEAT) and zero degree height (ZH), and the correlation is greater than 0.3. We determined the forecast threshold of the above forecasting factors, calculated the fitting rate and conducted a test report. We used the pup product to establish a short-term proximity indicator for thunderstorm warning. Three products with combined reflectivity, vertical integrated liquid water content and echo top height were selected as warning indicators for thunderstorms. The above research results were used to forecast the thunderstorm weather from June to August in the year of 2015 and 2016. The forecast accuracy rate is more than 85%. In summary, the above methods have reference value and indicative significance for the forecast and warning of thunderstorm weather in Fuxin City, China.
Cite this paper: Zhang, X. , Sun, B. , Sun, K. , Liu, J. , Yang, X. , Bai, J. , Shi, H. and Xie, Y. (2019) Research on Thunderstorm Forecasting in Fuxin, China Based on Physical Diagnostic Parameters. Journal of Geoscience and Environment Protection, 7, 106-114. doi: 10.4236/gep.2019.76009.

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