| Summary: | Hourly precipitation data of 91 meteorological stations in Jiangxi Province during 1954—2012 were selected to analyze the variation of maximum precipitation in consecutive 1 h,3 h,6 h,12 h and 24 h using hydrologic variation diagnostic system (HDMS) .Firstly,in the detailed diagnosis,linear trend,Kendall and Spearman methods were used for trend test,and M-K,cumulative anomaly,ordered clustering,sliding F,sliding rank sum and other test methods were adopted for jump diagnosis.Secondly,the efficiency coefficient R 2 was employed to determine the final diagnosis results and conduct the spatio-temporal analysis.Finally,the spatial characteristics of the occurrence frequency of maximum precipitation greater than or equal to 16 mm,30 mm and 50 mm were analyzed.The results show the followings:① The spatial distribution characteristics of maximum precipitation in Max1 h,Max3 h,Max6 h,Max12 h and Max24 h were similar in Jiangxi Province.With the increase in duration,most stations with variations witnessed a jumping increase.Those with significant variations were more in the northern plain than in the southern mountain area,namely that the spatial distribution was dense in the north and sparse in the south.② The degree of precipitation series variation was positively and negatively correlated with elevation in the southern mountain area and the northern plain area,respectively.Studies have shown that atmospheric circulation indexes AO (Arctic oscillation),NAO (North Atlantic oscillation) and PNA (Pacific-North American oscillation) had negative,positive and negative correlations with precipitation at stations in the study area,respectively.Therefore,the atmospheric circulation indexes have correlations with the change of precipitation series in Jiangxi Province,which are one of the causes of the maximum precipitation variation in the period.③ The frequency of regional rainstorms gradually decreased with the increase in duration,and rainstorm events in the northern plain area were less than those in other mountain areas ...
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