In this study,we assess the prediction for May rainfall over southern China(SC)by using the NCEP CFSv2 outputs.Results show that the CFSv2 is able to depict the climatology of May rainfall and associated circulations.However,the model has a poor skill in predicting interannual variation due to its poor performance in capturing related anomalous circulations.In observation,the above-normal SC rainfall is associated with two anomalous anticyclones over the western tropical Pacific and northeastern China,respectively,with a low-pressure convergence in between.In the CFSv2,however,the anomalous circulations exhibit the patterns in response to the El Ni?o-Southern Oscillation(ENSO),demonstrating that the model overestimates the relationship between May SC rainfall and ENSO.Because of the onset of the South China Sea monsoon,the atmospheric circulation in May over SC is more complex,so the prediction for May SC rainfall is more challenging.In this study,we establish a dynamic-statistical forecast model for May SC rainfall based on the relationship between the interannual variation of rainfall and large-scale ocean-atmosphere variables in the CFSv2.The sea surface temperature anomalies(SSTAs)in the northeastern Pacific and the central-eastern equatorial Pacific,and the 500-hPa geopotential height anomalies over western Siberia in previous April,which exert great influence on the SC rainfall in May,are chosen as predictors.Furthermore,multiple linear regression is employed between the predictors obtained from the CFSv2 and observed May SC rainfall.Both cross validation and independent test show that the hybrid model significantly improve the model's skill in predicting the interannual variation of May SC rainfall by two months in advance.

LI Chan-zhu;YANG Song;MO Wei-qiang;ZHANG Jin-mei;WEI Wei

Dongguan Meteorological Service,Dongguan,Guangdong 523082 China;School of Atmospheric Sciences,Sun Yat-sen University(Zhuhai),Zhuhai,Guangdong 519082 China;Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies,Sun Yat-sen University,Guangzhou 510275 China;Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai),Zhuhai,Guangdong 519082 China

热带气象学报（英文版）

[1]LI Chan-zhu;YANG Song;MO Wei-qiang;ZHANG Jin-mei;WEI Wei-.Seasonal Prediction for May Rainfall over Southern China Based on the NCEP CFSv2)[J].热带气象学报（英文版）,2022(01):29-44

anticyclones

Seasonal,Prediction,May,Rainfall,Southern,China,Based,NCEP,CFSv2,In,this,study,assess,prediction,rainfall,southern,SC,by,using,outputs,Results,show,that,depict,climatology,associated,circulations,However,model,has,poor,skill,predicting,interannual,variation,due,its,performance,capturing,related,anomalous,observation,above,normal,two,western,tropical,Pacific,northeastern,respectively,low,pressure,convergence,between,however,exhibit,patterns,response,El,Oscillation,ENSO,demonstrating,overestimates,relationship,Because,onset,monsoon,atmospheric,complex,challenging,establish,dynamic,statistical,forecast,large,scale,ocean,atmosphere,variables,sea,surface,temperature,anomalies,SSTAs,central,equatorial,hPa,geopotential,height,Siberia,previous,April,which,exert,great,influence,are,chosen,predictors,Furthermore,multiple,linear,regression,employed,obtained,from,observed,Both,cross,validation,independent,test,hybrid,significantly,improve,months,advance

0.477493