Is model parameter error related to a significant spring predictability barrier for el nio events? results from a theoretical model
文献类型：期刊论文
| 作者 | Duan Wansuo1; Zhang Rui1,2 |
| 刊名 | Advances in atmospheric sciences
 |
| 出版日期 | 2010-09-01 |
| 卷号 | 27期号:5页码:1003-1013 |
| 关键词 | Enso predictability Optimal perturbation Error growth Model parameters |
| ISSN号 | 0256-1530 |
| DOI | 10.1007/s00376-009-9166-4 |
| 通讯作者 | Duan wansuo(duanws@mail.iap.ac.cn) |
| 英文摘要 | Within a theoretical enso model, the authors investigated whether or not the errors superimposed on model parameters could cause a significant "spring predictability barrier" (spb) for el nio events. first, sensitivity experiments were respectively performed to the air-sea coupling parameter, alpha and the thermocline effect coefficient a mu. the results showed that the uncertainties superimposed on each of the two parameters did not exhibit an obvious season-dependent evolution; furthermore, the uncertainties caused a very small prediction error and consequently failed to yield a significant spb. subsequently, the conditional nonlinear optimal perturbation (cnop) approach was used to study the effect of the optimal mode (cnop-p) of the uncertainties of the two parameters on the spb and to demonstrate that the cnop-p errors neither presented a unified season-dependent evolution for different el nio events nor caused a large prediction error, and therefore did not cause a significant spb. the parameter errors played only a trivial role in yielding a significant spb. to further validate this conclusion, the authors investigated the effect of the optimal combined mode (i.e. cnop error) of initial and model errors on spb. the results illustrated that the cnop errors tended to have a significant season-dependent evolution, with the largest error growth rate in the spring, and yielded a large prediction error, inducing a significant spb. the inference, therefore, is that initial errors, rather than model parameter errors, may be the dominant source of uncertainties that cause a significant spb for el nio events. these results indicate that the ability to forecast enso could be greatly increased by improving the initialization of the forecast model. |
| WOS关键词 | NONLINEAR OPTIMAL PERTURBATION ; ENSO ; CLIMATE ; PREDICTION ; GROWTH ; NINO |
| WOS研究方向 | Meteorology & Atmospheric Sciences |
| WOS类目 | Meteorology & Atmospheric Sciences |
| 语种 | 英语 |
| WOS记录号 | WOS:000280971600004 |
| 出版者 | SCIENCE PRESS |
| URI标识 | http://www.irgrid.ac.cn/handle/1471x/2414878 |
| 专题 | 中国科学院大学 |
| 通讯作者 | Duan Wansuo |
| 作者单位 | 1.Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Numer Modelling Atmospher Sci & Geo, Beijing 100029, Peoples R China 2.Chinese Acad Sci, Grad Univ, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Duan Wansuo,Zhang Rui. Is model parameter error related to a significant spring predictability barrier for el nio events? results from a theoretical model[J]. Advances in atmospheric sciences,2010,27(5):1003-1013. |
| APA | Duan Wansuo,&Zhang Rui.(2010).Is model parameter error related to a significant spring predictability barrier for el nio events? results from a theoretical model.Advances in atmospheric sciences,27(5),1003-1013. |
| MLA | Duan Wansuo,et al."Is model parameter error related to a significant spring predictability barrier for el nio events? results from a theoretical model".Advances in atmospheric sciences 27.5(2010):1003-1013. |
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来源：中国科学院大学
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