Initial error-induced optimal perturbations in ENSO predictions, as derived from an intermediate coupled model
文献类型：期刊论文
| 作者 | Tao, Ling-Jiang1,2 ; Zhang, Rong-Hua1,2,3; Gao, Chuan1,2
|
| 刊名 | ADVANCES IN ATMOSPHERIC SCIENCES
 |
| 出版日期 | 2017-06-01 |
| 卷号 | 34期号:6页码:791-803 |
| 关键词 | El Nino Predictability Initial Errors Intermediate Coupled Model Spring Predictability Barrier |
| DOI | 10.1007/s00376-017-6266-4 |
| 文献子类 | Article |
| 英文摘要 | The initial errors constitute one of the main limiting factors in the ability to predict the El Nio-Southern Oscillation (ENSO) in ocean-atmosphere coupled models. The conditional nonlinear optimal perturbation (CNOP) approach was employed to study the largest initial error growth in the El Nio predictions of an intermediate coupled model (ICM). The optimal initial errors (as represented by CNOPs) in sea surface temperature anomalies (SSTAs) and sea level anomalies (SLAs) were obtained with seasonal variation. The CNOP-induced perturbations, which tend to evolve into the La Nia mode, were found to have the same dynamics as ENSO itself. This indicates that, if CNOP-type errors are present in the initial conditions used to make a prediction of El NiEeno, the El Nio event tends to be under-predicted. In particular, compared with other seasonal CNOPs, the CNOPs in winter can induce the largest error growth, which gives rise to an ENSO amplitude that is hardly ever predicted accurately. Additionally, it was found that the CNOP-induced perturbations exhibit a strong spring predictability barrier (SPB) phenomenon for ENSO prediction. These results offer a way to enhance ICM prediction skill and, particularly, weaken the SPB phenomenon by filtering the CNOP-type errors in the initial state. The characteristic distributions of the CNOPs derived from the ICM also provide useful information for targeted observations through data assimilation. Given the fact that the derived CNOPs are season-dependent, it is suggested that seasonally varying targeted observations should be implemented to accurately predict ENSO events. |
| 语种 | 英语 |
| WOS记录号 | WOS:000400378100009 |
| 版本 | 出版稿 |
| 源URL | [http://ir.qdio.ac.cn/handle/337002/137062]  |
| 专题 | 海洋研究所_海洋环流与波动重点实验室 |
| 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, Lab Ocean & Climate Dynam, Qingdao 266237, Peoples R China |
| 推荐引用方式 GB/T 7714 | Tao, Ling-Jiang,Zhang, Rong-Hua,Gao, Chuan. Initial error-induced optimal perturbations in ENSO predictions, as derived from an intermediate coupled model[J]. ADVANCES IN ATMOSPHERIC SCIENCES,2017,34(6):791-803. |
| APA | Tao, Ling-Jiang,Zhang, Rong-Hua,&Gao, Chuan.(2017).Initial error-induced optimal perturbations in ENSO predictions, as derived from an intermediate coupled model.ADVANCES IN ATMOSPHERIC SCIENCES,34(6),791-803. |
| MLA | Tao, Ling-Jiang,et al."Initial error-induced optimal perturbations in ENSO predictions, as derived from an intermediate coupled model".ADVANCES IN ATMOSPHERIC SCIENCES 34.6(2017):791-803. |
入库方式： OAI收割
来源：海洋研究所
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