%0 Journal Article
%T Diagnostic Researches and Forecasting Experiments of the Various Regional Sea Surface Temperature Anomaly on Summer Precipitation in China<br>不同区域海温异常对中国夏季旱涝影响的诊断研究和预测试验
%A WANG Lei
%A ZHANG Ren-He
%A <br>王蕾
%A 张人禾
%J 大气科学
%D 2006
%I 
%X Based on a canonical ensemble correlation prediction(CECP) model for seasonal precipitation anomaly,diagnostic analyses and forecast experiments are conducted on JJA(June,July and August) precipitation in China,using various seasons and different regional sea surface temperature anomalies(SSTA) as predictor fields.The results show that the CECP scheme with an area-factor is a useful method for both researches and predictions,which not only can make out some typical spacial patterns in the precipitation and sea surface temperature(SST) fields,but also has high forecast skill on summer precipitation in China.The teleconnection characteristics between global SSTA in various seasons and summer(JJA) precipitation in China are analyzed.The analyses show that the impacts of global SSTA on summer precipitation in China have significant seasonal changes.Particularly,SST anomaly distributions in the southern Indian Ocean,the equatorial eastern Pacific Ocean and the North Atlantic Ocean have good correlation with summer precipitation in China.The special global SSTA distribution pattern might be used as a predictor of JJA precipitation in China. In addition,selecting different regional and various seasonal SSTA as predictor fields,diagnostic analyses and forecast experiments are conducted on JJA precipitation in 1998 and 1999 respectively,and then their individual impacts on JJA precipitation in China are weighted to combine optimally the forecasting results.The series tests show that ensemble prediction of various regional SSTA on summer precipitation in China can not only greatly increase predictability of summer precipitation in China,but also uncover the notable signals of SSTA in different regions and various seasons associated with the regional drought/flood of summer in China.Thus,the ensemble forecast method can reveal the contributions of interannual changes of SST in different areas to summer precipitation in China,optimal combination prediction can efficiently improve forecasting skill.
%K canonical ensemble correlation prediction(CECP) model
%K sea surface temperature anomaly(SSTA)
%K summer drought/flood in China
%K teleconnection
%K ensemble prediction<br>典型集合相关预测模式
%K 海表温度异常
%K 中国夏季旱涝
%K 遥相关
%K 最优集成预测
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=E62459D214FD64A3C8082E4ED1ABABED5711027BBBDDD35B&cid=28A2F569B2458C17&jid=46874A5A102033D774D00D819E91CD68&aid=7DAE59B12C8F4F1B&yid=37904DC365DD7266&vid=340AC2BF8E7AB4FD&iid=B31275AF3241DB2D&sid=008520E0B52E94B3&eid=545EC3172B3789BC&journal_id=1006-9895&journal_name=大气科学&referenced_num=2&reference_num=26