简介：TheLS-SVM(Leastsquaressupportvectormachine)methodispresentedtosetupamodeltoforecasttheoccurrenceofthunderstormsintheNanjingareabycombiningNCEPFNLOperationalGlobalAnalysisdataon1.0°×1.0°gridsandcloud-to-groundlightningdataobservedwithalightninglocationsysteminJiangsuprovinceduring2007-2008.Adatasetwith642samples,including195thunderstormsamplesand447non-thunderstormsamples,arerandomlydividedintotwogroups,one(having386samples)formodelingandtherestforindependentverification.ThepredictorsareatmosphericinstabilityparameterswhichcanbeobtainedfromtheNCEPdataandthepredictandistheoccurrenceofthunderstormsobservedbythelightninglocationsystem.Preliminaryapplicationstotheindependentsamplesfora6-hourforecastofthunderstormeventsshowthatthepredictioncorrectionrateofthismodelis78.26%,falsealarmrateis21.74%,andforecastingtechnicalscoreis0.61,allbetterthanthosefromeitherlinearregressionorartificialneuralnetwork.