摘要
Some features associated with Eastern China Precipitation (ECP), in terms of mean climatology, sea-sonal cycle, interannual variability are studied based on monthly rainfall data. The rainfall behavior over Eastern China has fine spatial structure in the seasonal variation and interannual variability. The revealed characteristics of ECP motivate us dividing Eastern China into four sub—regions to quantify significant lag—correlations of the rainfalls with global sea surface temperatures (SSTs) and to study the ocean’s pre-dominant role in forcing the eastern China summer monsoon rainfalls. Lagged correlations between the mid—eastern China summer monsoon rainfalls (MECSMRs) and the global SSTs, with SST leading to rain-fall, are investigated. The most important key SST regions and leading times, in which SSTs are highly corre-lated with the MECSMRs, are selected. Part of the results confirms previous studies that show links between the MECSMRs and SSTs in the eastern equatorial Pacific associated with the El Nino — Southern Oscillation (ENSO) phenomenon. Other findings include the high lag correlations between the MECSMRs and the SSTs in the high and middle latitude Pacific Ocean and the Indian Ocean, even the SSTs over the Atlantic Ocean, with SST leading—time up to 4 years. Based on the selected SST regions, regression equa-tions are developed by using the SSTs in these regions in respective leading time. The correlation coefficient between the observed rainfalls and regressed rainfalls is over 0.85. The root mean square error (RMSE) for regressed rainfall is around 65% of the standard deviation and about 15% of the mean rainfall. The regression equation has also been evaluated in a forecasting mode by using independent data. Discussion on the consistence of the SST—rainfall correlation with circulation field is also presented. Key words Summer monsoon - Rainfall - SST - Regression This work was jointed supported by Chinese Academy of Sciences under Grant “Hundred Talents” for “Validation of Coupled Climate models” and by U.S. Department of Energy under Grant DEFG0285ER 60314 to SUNY at Stony Brook. The authors are grateful to Professor R. D. Cess at SUNY, Stony Brook for his supports.
Some features associated with Eastern China Precipitation (ECP), in terms of mean climatology, sea-sonal cycle, interannual variability are studied based on monthly rainfall data. The rainfall behavior over Eastern China has fine spatial structure in the seasonal variation and interannual variability. The revealed characteristics of ECP motivate us dividing Eastern China into four sub—regions to quantify significant lag—correlations of the rainfalls with global sea surface temperatures (SSTs) and to study the ocean’s pre-dominant role in forcing the eastern China summer monsoon rainfalls. Lagged correlations between the mid—eastern China summer monsoon rainfalls (MECSMRs) and the global SSTs, with SST leading to rain-fall, are investigated. The most important key SST regions and leading times, in which SSTs are highly corre-lated with the MECSMRs, are selected. Part of the results confirms previous studies that show links between the MECSMRs and SSTs in the eastern equatorial Pacific associated with the El Nino — Southern Oscillation (ENSO) phenomenon. Other findings include the high lag correlations between the MECSMRs and the SSTs in the high and middle latitude Pacific Ocean and the Indian Ocean, even the SSTs over the Atlantic Ocean, with SST leading—time up to 4 years. Based on the selected SST regions, regression equa-tions are developed by using the SSTs in these regions in respective leading time. The correlation coefficient between the observed rainfalls and regressed rainfalls is over 0.85. The root mean square error (RMSE) for regressed rainfall is around 65% of the standard deviation and about 15% of the mean rainfall. The regression equation has also been evaluated in a forecasting mode by using independent data. Discussion on the consistence of the SST—rainfall correlation with circulation field is also presented. Key words Summer monsoon - Rainfall - SST - Regression This work was jointed supported by Chinese Academy of Sciences under Grant “Hundred Talents” for “Validation of Coupled Climate models” and by U.S. Department of Energy under Grant DEFG0285ER 60314 to SUNY at Stony Brook. The authors are grateful to Professor R. D. Cess at SUNY, Stony Brook for his supports.
