Discriminant analysis applied to the forecasting of thunderstorms

The combination of several thermodynamic variables based upon the data prov ided by a radiosounding can be useful for the forecasting of thunderstorms. As a matter of fact, there are many indices that allow the establishment o f a storm risk prediction once they have been gauged. The problem comes whe n not all indices lead to the same prediction. In these cases, it is necess ary to establish one single function based on the information provided by a ll the variables employed, which should be able to determine a two-fold pre diction: risk or no risk. This article presents a statistic model for the s hort term prediction of thunderstorms in the region of Leon (Spain). To rea ch this aim 15 meteorological variables were selected. These variables were easy to handle by non-expert staff, and they allowed the characterisation of the preconvective environment early in the morning on thunderstorm days. The variables have been properly combined and gauged with the help of a de nse network of meteorological observers. The result has led to the construc tion of a reliable model. The discriminant quadratic model has been easily applied to determine in an objective and binary way the risk/no risk for th e occurrence of thunderstorms.