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
Source PublicationADVANCES IN ATMOSPHERIC SCIENCES
ISSN0256-1530
Volume36Issue:12Pages:1381-1392
Corresponding AuthorYuan, Shijin(yuanshijin2003@163.com)
AbstractThe 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.
Keywordoptimal precursor ENSO gradient-definition-based method conditional nonlinear optimal perturbation intermediate coupled model
DOI10.1007/s00376-019-9040-y
Indexed BySCI
Language英语
Funding ProjectFundamental 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 Research AreaMeteorology & Atmospheric Sciences
WOS SubjectMeteorology & Atmospheric Sciences
WOS IDWOS:000495292800007
PublisherSCIENCE PRESS
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.qdio.ac.cn/handle/337002/164875
Collection海洋环流与波动重点实验室
Corresponding AuthorYuan, Shijin
Affiliation1.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
Recommended Citation
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.
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