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Impact of observational MJO forcing on ENSO predictability in the Zebiak-Cane model. Part I: Effect on the maximum prediction error
Received:September 06, 2013  Revised:December 24, 2014
Key words:El Nino–Southern Oscillation (ENSO)  Madden-Jullien Oscillation (MJO)  maximum prediction error  Conditional Nonlinear Optimal Perturbation (CNOP)
中文关键词:  厄尔尼诺-南方涛动  季节内振荡  最大预报误差  条件非线性最优扰动
基金项目:The National Natural Science Foundation of China (Grant No. 41405062)
Author NameAffiliationPostcode
Peng YuehuaDalian Naval Academy 116018
Song JunqiangNational University of Defense Technology 
Xiang Jie* College of Meteorology and Oceangraphy, PLA University of Science and Technology 211101
Sun ChengzhiDalian Naval Academy 
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      With the observational wind stress data in Pacific and the Zebiak-Cane model, the impact of Madden-Jullien Oscillation (MJO) as external forcing on El Ni?o–Southern Oscillation (ENSO) predictability is studied. The observational data are analyzed with Continuous Wavelet Transform (CWT) and then used to extract MJO signals, which are added into the model to get a new model. After using the Conditional Nonlinear Optimal Perturbation (CNOP) method, the initial error which can evolve into maximum prediction error, model error and their join error are gained and then the Ni?o-3 indices and spatial structures of three kinds of errors are investigated. The results mainly show that the observational MJO has little impact on the maximum prediction error of ENSO events and the initial error affects much greater than model error caused by MJO forcing. These demonstrate that the initial error might be the main error source that produces uncertainty in ENSO prediction, which could provide a theoretical foundation for the adaptive data assimilation of the ENSO forecast and contribute to the ENSO target observation.
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