Comparative Analysis of Potential Thunderstorm Forecast Methods Based on the Convective Parameters
Rui Chai · Anhui nongye kexue · 2009
This article distinguished thunderstorms and non-thunderstorms on the basis of the lightning location information within a range of 50 km around Nanjing City and filtrated forecasting parameters during the 552 radio sound observations during June-August from 2006 to 2008 by the means of gradual selection,stepwise regression and correlation analysis.The convective parameters,which were closely related to thunderstorms,were selected as the forecasting parameters and for the potential prediction of thunderstorms,Bayes discriminant analysis,Logistic regression discriminant and Neural network were deployed to forecast thunderstorms.The results of comparative analysis of the forecasting results by the three methods showed that the forecast accuracy of logistic regression discriminant was the highest with 78%,the false alarm rate of Bayes discriminant analysis is the least with 7.6%,logistic regression discriminant is the most appropriate method to forecast thunderstorms of Nanjing considered both forecast accuracy and false alarm rate.Finally the forecasting parameters were used for principal component analysis so that an explanation on the relationship between the factors and thunderstorms was given.