MJO potential predictability and predictive skill in IAP AGCM 4.1

作     者：WANG Kun LIN Zhao-Hui LING Jian YU Yue WU Cheng-Lai WANG Kun;LIN Zhao-Hui;LING Jian;YU Yue;WU Cheng-Lai

作者机构：International Center for Climate and Environment Sciences(ICCES)Institute of Atmospheric Physics(lAP)Chinese Academy of Sciences(CAS)BeijingChina College of Earth ScienceUniversity of Chinese Academy of SciencesBeijingChina Collaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNanjing University of Information Science&TechnologyNanjingChina State Key Laboratory of Numerical Modeling for Atmospheric Science and Geophysical Fluid Dynamics(LASG)IAPCASBeijingChina 

出 版 物：《Atmospheric and Oceanic Science Letters》 (大气和海洋科学快报（英文版）)

年 卷 期：2016年第9卷第5期

页      面：388-393页

核心收录：

学科分类：07[理学] 070601[理学-气象学] 0706[理学-大气科学] 

基　　金：supported by the Strategic Priority Research Program of the Chinese Academy of Sciences[grant number XDA05110200] the Special Scientific Research Fund of the Meteorological Public Welfare Profession of China[grant number GYHY201406021] the National Natural Science Foundation of China[grant numbers 41575095,41175073,41575062,41520104008] 

主　　题：MJO IAP AGCM 4.1 predictability prediction skill 

摘      要：A 30-year hindcast was performed using version 4.1 of the IAP AGCM（IAP AGCM4.1）, and its potential predictability of the MJO was then evaluated. The results showed that the potential predictability of the MJO is 13 and 24 days, evaluated using the signal-to-error ratio method based on a single member and the ensemble mean, respectively. However, the MJO prediction skill is only9 and 10 days using the two methods mentioned above. It was further found that the potential predictability and prediction skill depend on the MJO amplitude in the initial conditions. Prediction initiated from conditions with a strong MJO amplitude tends to be more skillful. Together with the results of other measures, the current MJO prediction ability of IAP AGCM4.1 is around 10 days, which is much lower than other climate prediction systems. Furthermore, the smaller difference between the MJO predictability and prediction skill evaluated by a single member and the ensemble mean methods could be ascribed to the relatively smaller size of the ensemble member of the ***, considerable effort should be made to improve MJO prediction in IAP AGCM4.1 through application of a reasonable model initialization and ensemble forecast strategy.