Model parameter-related optimal perturbations and their contributions to El Nino prediction errors
文献类型：期刊论文
| 作者 | Tao, Ling-Jiang1,2 ; Gao, Chuan1,3; Zhang, Rong-Hua1,2,3
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| 刊名 | CLIMATE DYNAMICS
 |
| 出版日期 | 2019-02-01 |
| 卷号 | 52期号:3-4页码:1425-1441 |
| 关键词 | Intermediate coupled model CNOP approach Model parameters El Nino predictability |
| ISSN号 | 0930-7575 |
| DOI | 10.1007/s00382-018-4202-7 |
| 通讯作者 | Zhang, Rong-Hua(rzhang@qdio.ac.cn) |
| 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. |
| 资助项目 | 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 (41690120)] ; CAS Strategic Priority Project ; Western Pacific Ocean System[XDA11010105] ; Western Pacific Ocean System[XDA11020306] ; NSFC-Shandong Joint Fund for Marine Science Research Centers[U1406402] ; National Programme on Global Change and Air-Sea Interaction[GASI-IPOVAI-06] ; National Programme on Global Change and Air-Sea Interaction[GASI-IPOVAI-01-01] ; Taishan Scholarship |
| WOS研究方向 | Meteorology & Atmospheric Sciences |
| 语种 | 英语 |
| WOS记录号 | WOS:000460902200008 |
| 出版者 | SPRINGER |
| 源URL | [http://ir.qdio.ac.cn/handle/337002/155319]  |
| 专题 | 海洋研究所_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 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(3-4):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(3-4),1425-1441. |
| MLA | Tao, Ling-Jiang,et al."Model parameter-related optimal perturbations and their contributions to El Nino prediction errors".CLIMATE DYNAMICS 52.3-4(2019):1425-1441. |
入库方式： OAI收割
来源：海洋研究所
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