Verification and Improvement of the Ability of CFSv2 to Predict the Antarctic Oscillation in Boreal Spring

作     者：Dapeng ZHANG Yanyan HUANG Bo SUN Fei LI Huijun WANG 

作者机构：Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological DisasterMinistry of Education Nanjing University of Information Science and Technology Nansen–Zhu International Research Centre Institute of Atmospheric Physics Chinese Academy of Sciences NILU – Norwegian Institute for Air Research 

出 版 物：《Advances in Atmospheric Sciences》 (大气科学进展（英文版）)

年 卷 期：2019年第36卷第3期

页      面：292-302,340页

核心收录：

学科分类：07[理学] 0702[理学-物理学] 

基　　金：supported by the National Key Research and Development Program of China (Grant No. 2016YFA0600703) the funding of the Jiangsu Innovation & Entrepreneurship Team and the Priority Academic Program Development of Jiangsu Higher Education Institutions 

主　　题：Antarctic Oscillation interannual-increment approach CFSv2 dynamical–statistical model prediction 

摘      要：The boreal spring Antarctic Oscillation(AAO)has a significant impact on the spring and summer climate in *** study evaluates the capability of the NCEP s Climate Forecast System,version 2(CFSv2),in predicting the boreal spring AAO for the period *** results indicate that CFSv2 has poor skill in predicting the spring AAO,failing to predict the zonally symmetric spatial pattern of the AAO,with an insignificant correlation of 0.02 between the predicted and observed AAO Index(AAOI).Considering the interannual increment approach can amplify the prediction signals,we firstly establish a dynamical-statistical model to improve the interannual increment of the AAOI(DY AAOI),with two predictors of CFSv2-forecasted concurrent spring sea surface temperatures and observed preceding autumn sea *** dynamical-statistical model demonstrates good capability in predicting DY AAOI,with a significant correlation coeffcient of 0.58 between the observation and prediction during 1983-2015 in the two-year-out ***,we obtain an improved AAOI by adding the improved DY AAOI to the preceding observed *** improved AAOI shows a significant correlation coeffcient of 0.45 with the observed AAOI during ***,the unrealistic atmospheric response to March-April-May sea ice in CFSv2 may be the possible cause for the failure of CFSv2 to predict the *** study gives new clues regarding AAO prediction and short-term climate prediction.