IOCAS-IR  > 海洋环流与波动重点实验室
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
Source PublicationADVANCES IN ATMOSPHERIC SCIENCES
ISSN0256-1530
Volume35Issue:7Pages:853-867
Corresponding AuthorZhang, Rong-Hua(rzhang@qdio.ac.cn)
AbstractPrevious 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.
KeywordEl Nino prediction initial condition errors target observations
DOI10.1007/s00376-017-7138-7
Indexed BySCI
Language英语
Funding ProjectStrategic 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 Research AreaMeteorology & Atmospheric Sciences
WOS SubjectMeteorology & Atmospheric Sciences
WOS IDWOS:000432691200009
PublisherSCIENCE PRESS
Citation statistics
Document Type期刊论文
Identifierhttp://ir.qdio.ac.cn/handle/337002/159190
Collection海洋环流与波动重点实验室
Corresponding AuthorZhang, Rong-Hua
Affiliation1.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
First Author AffilicationKey Laboratory of Ocean Circulation and Wave Studies, Institute of Oceanology, Chinese Academy of Sciences
Corresponding Author AffilicationKey Laboratory of Ocean Circulation and Wave Studies, Institute of Oceanology, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
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.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Tao, Ling-Jiang]'s Articles
[Gao, Chuan]'s Articles
[Zhang, Rong-Hua]'s Articles
Baidu academic
Similar articles in Baidu academic
[Tao, Ling-Jiang]'s Articles
[Gao, Chuan]'s Articles
[Zhang, Rong-Hua]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Tao, Ling-Jiang]'s Articles
[Gao, Chuan]'s Articles
[Zhang, Rong-Hua]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.