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DOI | 10.1007/s00382-018-4202-7 |
Model parameter-related optimal perturbations and their contributions to El Nino prediction errors | |
Tao, Ling-Jiang1,2; Gao, Chuan1,3; Zhang, Rong-Hua1,2,3 | |
2019-02-01 | |
发表期刊 | CLIMATE DYNAMICS |
ISSN | 0930-7575 |
EISSN | 1432-0894 |
出版年 | 2019 |
卷号 | 52页码:1425-1441 |
文章类型 | Article |
语种 | 英语 |
国家 | Peoples R China |
英文摘要 | Errors in initial conditions and model parameters (MPs) are the main sources that limit the accuracy of ENSO predictions. In addition to exploring the initial error-induced prediction errors, model errors are equally important in determining prediction performance. In this paper, the MP-related optimal errors that can cause prominent error growth in ENSO predictions are investigated using an intermediate coupled model (ICM) and a conditional nonlinear optimal perturbation (CNOP) approach. Two MPs related to the Bjerknes feedback are considered in the CNOP analysis: one involves the SST-surface wind coupling (), and the other involves the thermocline effect on the SST (Te). The MP-related optimal perturbations (denoted as CNOP-P) are found uniformly positive and restrained in a small region: the component is mainly concentrated in the central equatorial Pacific, and the Te component is mainly located in the eastern cold tongue region. This kind of CNOP-P enhances the strength of the Bjerknes feedback and induces an El Nino- or La Nina-like error evolution, resulting in an El Nino-like systematic bias in this model. The CNOP-P is also found to play a role in the spring predictability barrier (SPB) for ENSO predictions. Evidently, such error growth is primarily attributed to MP errors in small areas based on the localized distribution of CNOP-P. Further sensitivity experiments firmly indicate that ENSO simulations are sensitive to the representation of SST-surface wind coupling in the central Pacific and tothe thermocline effect in the eastern Pacific in the ICM. These results provide guidance and theoretical support for the future improvement in numerical models to reduce the systematic bias and SPB phenomenon in ENSO predictions. |
英文关键词 | Intermediate coupled model CNOP approach Model parameters El Nino predictability |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000460902200008 |
WOS关键词 | SPRING PREDICTABILITY BARRIER ; INTERMEDIATE COUPLED MODEL ; NONLINEAR OPTIMAL PERTURBATION ; SINGULAR VECTOR ANALYSIS ; SEA-SURFACE TEMPERATURE ; ENTRAINMENT TEMPERATURE ; SOUTHERN-OSCILLATION ; TROPICAL PACIFIC ; ENSO PREDICTIONS ; OPTIMAL-GROWTH |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/36229 |
专题 | 气候变化 |
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 10029, Peoples R China; 3.Qingdao Natl Lab Marine Sci & Technol, Qingdao 266237, Peoples R China |
推荐引用方式 GB/T 7714 | Tao, Ling-Jiang,Gao, Chuan,Zhang, Rong-Hua. Model parameter-related optimal perturbations and their contributions to El Nino prediction errors[J]. CLIMATE DYNAMICS,2019,52:1425-1441. |
APA | Tao, Ling-Jiang,Gao, Chuan,&Zhang, Rong-Hua.(2019).Model parameter-related optimal perturbations and their contributions to El Nino prediction errors.CLIMATE DYNAMICS,52,1425-1441. |
MLA | Tao, Ling-Jiang,et al."Model parameter-related optimal perturbations and their contributions to El Nino prediction errors".CLIMATE DYNAMICS 52(2019):1425-1441. |
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