Analysis Of Spatial And Temporal Multiscale Variability Of Daily Precipitation In Yangtze River Basin

Under the background of global warming,knowing the spatio-temporal characteristics of precipitation can provide decision support for regional water resources management and flood disaster prevention.Based on the daily precipitation data of 115 rain gauging stations from 1963 to 2013 in the Yangtze River Basin and the daily data of three large-scale oceanic-atmospheric indices including AO(Arctic Oscillation Index)?NAO(North Atlantic Oscillation)and PNA(Pacific North American Oscillation Index),the multiscale characteristics of spatial-temporal variability of daily precipitation,the spatial-temporal trends of precipitation,and the teleconnection between daily precipitation and large-scale oceanic-atmospheric indices are investigated by using the extreme precipitation indices,the wavelet multiresolution analysis,the information entropy theory and the M-K test in this study.Results show that:(1)Spatially,the variability of daily precipitation series exists obvious local clustering,significant heterogeneity along the latitudinal direction,and quasi uniformity along the longitudinal direction.There exists an obvious dividing line at approximately 103° longitude,and the variability in the west of line is significantly higher than that in the east.The variability of daily precipitation is strongly linear correlative with station elevation,and weakly linear correlative with mean annual precipitation and average number of rain days.Temporally,an obvious dividing line can be observed at approximately 103° longitude from the spectra of the relative contribution of each sub-series to the total variability of the original daily precipitation series.In the west of the line,the contribution of each sub-series under the different time scales is higher than that in the east.And there exists an abruptness at the time scale of 256 days in the mutual information spectra.In addition,the time scale of the precipitation variability can be divided into three distinct scaling regions:(1)synoptic(2-16 days),(2)monthly to annual times(16-256 days)and(3)interannual(more than 256 days).(2)There exists spatial clustering in the trends of extreme precipitation in the Yangtze River Basin.The amount of extreme precipitation show increasing trends in the upper and lower reaches and decreasing trends in the middle reaches.In general,the amount and intensity of extreme precipitation in the Yangtze River Basin are increasing and the precipitation becomes more even over the study period.Remarkable shifts in the probability distributions of the Max 1-day precipitation amount(Rx1DAY),the Simple daily intensity index(SDII)and the Consecutive wet days(CWD)for 1963–1987 and 1988–2013 can be observed,which again confirms the tendencies in the amount and intensity of extreme precipitation are increasing and precipitation becomes more even during the past decades.The variations in extreme precipitation indices exhibit inconstant frequencies in the wavelet power spectrum.Among the 9 indices,4 of them,PRCPTOT(Annual total wet-day precipitation)?CDD(Consecutive dry days)?R10mm(Number of days above 10 mm)and R20mm(Number of days above 20 mm),show significant 1-year periodic oscillation and 3 of them,SDII?Rx1DAY and R95p(Precipitation of very wet days)exhibit significant 4-year cycle during some certain periods,which are mainly found during 1965-1980 and 1990-2010.(3)There exist some certain linear correlation between daily precipitation of the Yangtze River Basin and three selected large-scale oceanic-atmospheric indices.In general,daily precipitation of Yangtze River Basin has positive correlation with both AO and NAO,and negative correlation with PNA.Nearly 50% stations show significant correlation between daily precipitation and AO,and those with significant positive correlation are mainly located in Yunnan,Guizhou and Hubei Province while those having significant negative correlation are mostly situated in the eastern coastal areas.9 stations show significant positive correlation between daily precipitation and NAO while only one station shows significant negative correlation.More than 60% stations show significant correlation between daily precipitation and PNA,and almost all stations located in the east of 105°E show significant negative correlation between daily precipitation and PNA while only 5 stations located in Yunnan Province show significant positive correlation.In addition,the correlation between daily precipitation and large-scale oceanic-atmospheric indices usually have lag effect.The delayed response of daily precipitation to AO is timely,and only a few stations located in the southeastern corner have optimal lag period of more than 15 days.As for the delayed response of daily precipitation to NAO,18% stations have optimal lag period of 1 day.The number of stations with optimal lag period of more than 15 days is more than that of other two indices,which indicates that longer lag period is more obvious in lag response of daily precipitation to NAO.The delayed response of daily precipitation to PNA is also timely.More than 60% stations have optimal lag period of 1 to 5 days,and only a few stations located in Yunnan Province have longer lag period.