气象2017，Vol.43Issue(3)：294-304,11.DOI:10.7519/j.issn.1000-0526.2017.03.005
基于逐步回归模态投影方法的BCC气候系统模式ENSO预报订正
Statistical Correction of ENSO Prediction in BCC CSM1.1m Based on Stepwise Pattern Proj ection Method
摘要
Abstract
Using the sea surface temperature (SST)hindcast datasets produced by the climate system model of Beijing Climate Center (BCC CSM1.1m)from 1991 to 2014,the Stepwise Pattern Projection Method (SPPM)is employed to statistically correct El Ni?no-South Oscillation (ENSO)prediction.The main idea of the SPPM is to produce a prediction at the predictand grid by projecting the predictor field onto its co-variance pattern with the one-point predictand after selecting the predictor domain.The SPPM significant-ly improves the performance of the prediction over the equatorial Pacific and Indian Ocean.The temporal correlation score has increased 8%-10% in terms of Ni?o3.4 SST anomaly index with a 6-month lead in the cross validation.The spatial anomaly correlation coefficients for El Ni?o event predictions also increase obviously by the SPPM at most lead months,particularly in autumn.Besides,the prediction for the location of warming center also can be improved,compared with that of the original BCC CSM1.1m.关键词
BCC_CSM1.1m/ENSO/统计订正/逐步回归模态投影方法Key words
BCC_CSM1.1m (Beijing Climate Center System Model)/ENSO/statistical correction/SPPM (Stepwise Pattern Proj ection Method)分类
天文与地球科学引用本文复制引用
王琳,任宏利,陈权亮,田奔,刘颖..基于逐步回归模态投影方法的BCC气候系统模式ENSO预报订正[J].气象,2017,43(3):294-304,11.基金项目
公益性行业(气象)科研专项(GYHY201506013)、国家重点基础研究发展计划(973计划)(2015CB453203)、国家自然科学基金项目(41375062、41405080和41606019)共同资助 （气象）
