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ENSO Predictions in an Intermediate Coupled Model Influenced by Removing Initial Condition Errors in Sensitive Areas: A Target Observation Perspective
Tao, Ling-Jiang1,2; Gao, Chuan1,3; Zhang, Rong-Hua1,2,3
2018-07-01
发表期刊ADVANCES IN ATMOSPHERIC SCIENCES
ISSN0256-1530
卷号35期号:7页码:853-867
通讯作者Zhang, Rong-Hua([email protected])
摘要Previous studies indicate that ENSO predictions are particularly sensitive to the initial conditions in some key areas (socalled "sensitive areas"). And yet, few studies have quantified improvements in prediction skill in the context of an optimal observing system. In this study, the impact on prediction skill is explored using an intermediate coupled model in which errors in initial conditions formed to make ENSO predictions are removed in certain areas. Based on ideal observing system simulation experiments, the importance of various observational networks on improvement of El Nio prediction skill is examined. The results indicate that the initial states in the central and eastern equatorial Pacific are important to improve El NiEeno prediction skill effectively. When removing the initial condition errors in the central equatorial Pacific, ENSO prediction errors can be reduced by 25%. Furthermore, combinations of various subregions are considered to demonstrate the efficiency on ENSO prediction skill. Particularly, seasonally varying observational networks are suggested to improve the prediction skill more effectively. For example, in addition to observing in the central equatorial Pacific and its north throughout the year, increasing observations in the eastern equatorial Pacific during April to October is crucially important, which can improve the prediction accuracy by 62%. These results also demonstrate the effectiveness of the conditional nonlinear optimal perturbation approach on detecting sensitive areas for target observations.
关键词El Nino prediction initial condition errors target observations
DOI10.1007/s00376-017-7138-7
收录类别SCI
语种英语
资助项目Strategic Priority Research Program of the Chinese Academy of Sciences[XDA19060102]###367; National Natural Science Foundation of China[41475101]###100; National Natural Science Foundation of China[41690122]###98; National Natural Science Foundation of China[41690120]###99; National Natural Science Foundation of China[41421005]###312; National Programme on Global Change and Air-Sea Interaction Interaction[GASI-IPOVAI-06]###1861; National Programme on Global Change and Air-Sea Interaction Interaction[GASI-IPOVAI-01-01]###1862; Taishan Scholarship###104; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA19060102]; National Natural Science Foundation of China[41475101]; National Natural Science Foundation of China[41690122]; National Natural Science Foundation of China[41690120]; National Natural Science Foundation of China[41421005]; National Programme on Global Change and Air-Sea Interaction Interaction[GASI-IPOVAI-06]; National Programme on Global Change and Air-Sea Interaction Interaction[GASI-IPOVAI-01-01]; Taishan Scholarship
WOS研究方向Meteorology & Atmospheric Sciences
WOS类目Meteorology & Atmospheric Sciences
WOS记录号WOS:000432691200009
出版者SCIENCE PRESS
引用统计
被引频次:16[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/337002/159190
专题海洋环流与波动重点实验室
通讯作者Zhang, Rong-Hua
作者单位1.Chinese Acad Sci, Inst Oceanol, Key Lab Ocean Circulat & Waves, Qingdao 266071, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100029, Peoples R China
3.Qingdao Natl Lab Marine Sci & Technol, Qingdao 266237, Peoples R China
第一作者单位海洋环流与波动重点实验室
通讯作者单位海洋环流与波动重点实验室
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Tao, Ling-Jiang,Gao, Chuan,Zhang, Rong-Hua. ENSO Predictions in an Intermediate Coupled Model Influenced by Removing Initial Condition Errors in Sensitive Areas: A Target Observation Perspective[J]. ADVANCES IN ATMOSPHERIC SCIENCES,2018,35(7):853-867.
APA Tao, Ling-Jiang,Gao, Chuan,&Zhang, Rong-Hua.(2018).ENSO Predictions in an Intermediate Coupled Model Influenced by Removing Initial Condition Errors in Sensitive Areas: A Target Observation Perspective.ADVANCES IN ATMOSPHERIC SCIENCES,35(7),853-867.
MLA Tao, Ling-Jiang,et al."ENSO Predictions in an Intermediate Coupled Model Influenced by Removing Initial Condition Errors in Sensitive Areas: A Target Observation Perspective".ADVANCES IN ATMOSPHERIC SCIENCES 35.7(2018):853-867.
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