Progress in ENSO prediction and predictability study

doi:10.1093/nsr/nwy105

IOCAS-IR > 海洋环流与波动重点实验室

	Progress in ENSO prediction and predictability study
	Tang, Youmin 1,2; Zhang, Rong-Hua3,4 ; Liu, Ting 1,2; Duan, Wansuo 5; Yang, Dejian 6; Zheng, Fei 7; Ren, Hongli 8,9; Lian, Tao 1; Gao, Chuan3,4 ; Chen, Dake 1; Mu, Mu 10
	2018-11-01
发表期刊	NATIONAL SCIENCE REVIEW
ISSN	2095-5138
卷号	5 期号:6 页码:826-839
通讯作者	Tang, Youmin([email protected]) ; Liu, Ting([email protected])
摘要	ENSO is the strongest interannual signal in the global climate system with worldwide climatic, ecological and societal impacts. Over the past decades, the research about ENSO prediction and predictability has attracted broad attention. With the development of coupled models, the improvement in initialization schemes and the progress in theoretical studies, ENSO has become the most predictable climate mode at the time scales from months to seasons. This paper reviews in detail the progress in ENSO predictions and predictability studies achieved in recent years. An emphasis is placed on two fundamental issues: the improvement in practical prediction skills and progress in the theoretical study of the intrinsic predictability limit. The former includes progress in the couple models, data assimilations, ensemble predictions and so on, and the latter focuses on efforts in the study of the optimal error growth and in the estimate of the intrinsic predictability limit.
关键词	ENSO prediction and predictability coupled model ensemble prediction optimal error growth probabilistic prediction
DOI	10.1093/nsr/nwy105
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[41690124]###2376; National Natural Science Foundation of China[41690121]###121; National Natural Science Foundation of China[41690120]###99; National Natural Science Foundation of China[41705049]###2377; National Natural Science Foundation of China[41621064]###122; National Natural Science Foundation of China[41530961]###2378; National Key Research and Development Program[2017YFA0604202]###2379; National Programe on Global Change and Air-Sea Interaction[GASI-IPOVAI-06]###2380; Scientific Research Fund of the Second Institute of Oceanography[JG1810]###2381; National Natural Science Foundation of China[41690124]; National Natural Science Foundation of China[41690121]; National Natural Science Foundation of China[41690120]; National Natural Science Foundation of China[41705049]; National Natural Science Foundation of China[41621064]; National Natural Science Foundation of China[41530961]; National Key Research and Development Program[2017YFA0604202]; National Programe on Global Change and Air-Sea Interaction[GASI-IPOVAI-06]; Scientific Research Fund of the Second Institute of Oceanography[JG1810]
WOS研究方向	Science & Technology - Other Topics
WOS类目	Multidisciplinary Sciences
WOS记录号	WOS:000456418700014
出版者	OXFORD UNIV PRESS
引用统计	被引频次：162[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.qdio.ac.cn/handle/337002/160668
专题	海洋环流与波动重点实验室
通讯作者	Tang, Youmin; Liu, Ting
作者单位	1.Second Inst Oceanog, State Key Lab Satellite Ocean Environm Dynam, Hangzhou 310012, Zhejiang, Peoples R China 2.Univ Northern British Columbia, Environm Sci & Engn, Prince George, BC V2N 4Z9, Canada 3.Chinese Acad Sci, Inst Oceanol, Key Lab Ocean Circulat & Waves, Qingdao 266071, Peoples R China 4.Qingdao Natl Lab Marine Sci & Technol, Qingdao 266237, Peoples R China 5.Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Numer Modeling Atmospher Sci & Geop, Beijing 100029, Peoples R China 6.Hohai Univ, Coll Oceanog, Nanjing 210098, Jiangsu, Peoples R China 7.Chinese Acad Sci, Inst Atmospher Phys, Int Ctr Climate & Environm Sci, Beijing 100029, Peoples R China 8.China Meteorol Adm, Natl Climate Ctr, Lab Climate Studies, Beijing 100081, Peoples R China 9.China Meteorol Adm, Natl Climate Ctr, CMA NJU Joint Lab Climate Predict Studies, Beijing 100081, Peoples R China 10.Fudan Univ, Coll Atmospher & Ocean Sci, Shanghai 200438, Peoples R China
推荐引用方式 GB/T 7714	Tang, Youmin,Zhang, Rong-Hua,Liu, Ting,et al. Progress in ENSO prediction and predictability study[J]. NATIONAL SCIENCE REVIEW,2018,5(6):826-839.
APA	Tang, Youmin.,Zhang, Rong-Hua.,Liu, Ting.,Duan, Wansuo.,Yang, Dejian.,...&Mu, Mu.(2018).Progress in ENSO prediction and predictability study.NATIONAL SCIENCE REVIEW,5(6),826-839.
MLA	Tang, Youmin,et al."Progress in ENSO prediction and predictability study".NATIONAL SCIENCE REVIEW 5.6(2018):826-839.

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