Initial Error-induced Optimal Perturbations in ENSO Predictions,as Derived from an Intermediate Coupled Model
文献类型：CNKI期刊论文
| 作者 | Ling-Jiang TAO ; Rong-Hua ZHANG; Chuan GAO
|
| 发表日期 | 2017-06-10 |
| 出处 | Advances in Atmospheric Sciences
 |
| 关键词 | El Nio predictability initial errors intermediate coupled model spring predictability barrier |
| 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 Nio, 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. |
| 文献子类 | CNKI期刊论文 |
| 资助机构 | supported by the National Natural Science Foundation of China (NFSC ; Grant Nos. 41690122, 41690120, 41490644, 41490640 and 41475101) ; the Ao Shan Talents Program supported by Qingdao National Laboratory for Marine Science and Technology (Grant No. 2015ASTP) ; a Chinese Academy of Sciences Strategic Priority Project ; the Western Pacific Ocean System (Grant Nos. XDA11010105, XDA11020306) ; the NSFC–Shandong Joint Fund for Marine Science Research Centers (Grant No. U1406401) ; the National Natural Science Foundation of China Innovative Group Grant (Grant No. 41421005) ; the Taishan Scholarship and Qingdao Innovative Program (Grant No. 2014GJJS0101) |
| 卷 | v.34期:06页:109-121 |
| 语种 | 英文; |
| 分类号 | P732 |
| ISSN号 | 0256-1530 |
| 源URL | [http://ir.qdio.ac.cn/handle/337002/189299]  |
| 专题 | 中国科学院海洋研究所 |
| 作者单位 | 1.UniversityofChineseAcademyofSciences 2.KeyLaboratoryofOceanCirculationandWaves,InstituteofOceanology,ChineseAcademyofSciences 3.LaboratoryforOceanandClimateDynamics,QingdaoNationalLaboratoryforMarineScienceandTechnology |
| 推荐引用方式 GB/T 7714 | Ling-Jiang TAO,Rong-Hua ZHANG,Chuan GAO. Initial Error-induced Optimal Perturbations in ENSO Predictions,as Derived from an Intermediate Coupled Model. 2017. |
入库方式： OAI收割
来源：海洋研究所
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