IOCAS-IR  > 海洋环流与波动重点实验室
The Optimal Precursors for ENSO Events Depicted Using the Gradient-definition-based Method in an Intermediate Coupled Model
Mu, Bin1; Ren, Juhui1; Yuan, Shijin1; Zhang, Rong-Hua2,3,4; Chen, Lei5; Gao, Chuan2,3,4
2019-12-01
发表期刊ADVANCES IN ATMOSPHERIC SCIENCES
ISSN0256-1530
卷号36期号:12页码:1381-1392
通讯作者Yuan, Shijin(yuanshijin2003@163.com)
摘要The predictability of El Nino-Southern Oscillation (ENSO) has been an important area of study for years. Searching for the optimal precursor (OPR) of ENSO occurrence is an effective way to understand its predictability. The CNOP (conditional nonlinear optimal perturbation), one of the most effective ways to depict the predictability of ENSO, is adopted to study the optimal sea surface temperature (SST) precursors (SST-OPRs) of ENSO in the IOCAS ICM (intermediate coupled model developed at the Institute of Oceanology, Chinese Academy of Sciences). To seek the SST-OPRs of ENSO in the ICM, non-ENSO events simulated by the ICM are chosen as the basic state. Then, the gradient-definition-based method (GD method) is employed to solve the CNOP for different initial months of the basic years to obtain the SST-OPRs. The experimental results show that the obtained SST-OPRs present a positive anomaly signal in the western-central equatorial Pacific, and obvious differences exist in the patterns between the different seasonal SST-OPRs along the equatorial western-central Pacific, showing seasonal dependence to some extent. Furthermore, the non-El Nino events can eventually evolve into El Nino events when the SST-OPRs are superimposed on the corresponding seasons; the peaks of the Nino3.4 index occur at the ends of the years, which is consistent with the evolution of the real El Nino. These results show that the GD method is an effective way to obtain SST-OPRs for ENSO events in the ICM. Moreover, the OPRs for ENSO depicted using the GD method provide useful information for finding the early signal of ENSO in the ICM.
关键词optimal precursor ENSO gradient-definition-based method conditional nonlinear optimal perturbation intermediate coupled model
DOI10.1007/s00376-019-9040-y
收录类别SCI
语种英语
资助项目Fundamental Research Funds for the Central Universities[22120190 207] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA19060102] ; National Key Research and Development Program of China[2017YFC1404102(2017YFC1404100)] ; National Programme on Global Change and Air-Sea Interaction[GASI-IPOVAI-06] ; National Natural Science Foundation of China[41690122(41690120)] ; National Natural Science Foundation of China[41490644(41490640)] ; National Natural Science Foundation of China[414210 05] ; Taishan Scholarship
WOS研究方向Meteorology & Atmospheric Sciences
WOS类目Meteorology & Atmospheric Sciences
WOS记录号WOS:000495292800007
出版者SCIENCE PRESS
引用统计
被引频次:7[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/337002/164875
专题海洋环流与波动重点实验室
通讯作者Yuan, Shijin
作者单位1.Tongji Univ, Sch Software Engn, Shanghai 201804, Peoples R China
2.Chinese Acad Sci, Inst Oceanol, Key Lab Ocean Circulat & Waves, Qingdao 266071, Shandong, Peoples R China
3.Qingdao Natl Lab Marine Sci & Technol, Qingdao 266237, Shandong, Peoples R China
4.Univ Chinese Acad Sci, Beijing 100029, Peoples R China
5.Shanghai Cent Meteorol Observ, Shanghai 200030, Peoples R China
推荐引用方式
GB/T 7714
Mu, Bin,Ren, Juhui,Yuan, Shijin,et al. The Optimal Precursors for ENSO Events Depicted Using the Gradient-definition-based Method in an Intermediate Coupled Model[J]. ADVANCES IN ATMOSPHERIC SCIENCES,2019,36(12):1381-1392.
APA Mu, Bin,Ren, Juhui,Yuan, Shijin,Zhang, Rong-Hua,Chen, Lei,&Gao, Chuan.(2019).The Optimal Precursors for ENSO Events Depicted Using the Gradient-definition-based Method in an Intermediate Coupled Model.ADVANCES IN ATMOSPHERIC SCIENCES,36(12),1381-1392.
MLA Mu, Bin,et al."The Optimal Precursors for ENSO Events Depicted Using the Gradient-definition-based Method in an Intermediate Coupled Model".ADVANCES IN ATMOSPHERIC SCIENCES 36.12(2019):1381-1392.
条目包含的文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
Mu2019_Article_TheOp(1429KB)期刊论文出版稿限制开放CC BY-NC-SA浏览
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Mu, Bin]的文章
[Ren, Juhui]的文章
[Yuan, Shijin]的文章
百度学术
百度学术中相似的文章
[Mu, Bin]的文章
[Ren, Juhui]的文章
[Yuan, Shijin]的文章
必应学术
必应学术中相似的文章
[Mu, Bin]的文章
[Ren, Juhui]的文章
[Yuan, Shijin]的文章
相关权益政策
暂无数据
收藏/分享
文件名: Mu2019_Article_TheOptimalPrecursorsForENSOEve.pdf
格式: Adobe PDF
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。