Does Model Parameter Error Cause a Significant "Spring Predictability Barrier" for El Nino Events in the Zebiak-Cane Model?

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	Does Model Parameter Error Cause a Significant "Spring Predictability Barrier" for El Nino Events in the Zebiak-Cane Model?
	Yu, Yanshan 2; Mu, Mu 2; Duan, Wansuo 1
刊名	JOURNAL OF CLIMATE
	2012-02-01
卷号	25 期号:4 页码:1263-1277
关键词	NONLINEAR OPTIMAL PERTURBATION OCEAN-ATMOSPHERE MODEL GENERAL-CIRCULATION MODEL SEA-SURFACE TEMPERATURE SOUTHERN OSCILLATION COUPLED MODEL THERMOHALINE CIRCULATION ENSO PREDICTABILITY INITIAL CONDITIONS DATA ASSIMILATION
ISSN号	0894-8755
通讯作者	Duan, WS (reprint author), Chinese Acad Sci, Inst Atmospher Phys, LASG, POB 9804, Beijing 100029, Peoples R China.
英文摘要	Within the framework of the Zebiak-Cane model, the approach of conditional nonlinear optimal perturbation (CNOP) is used to study the effect of model parameter errors on El Nino-Southern Oscillation (ENSO) predictability. The optimal model parameter errors are obtained within a reasonable error bound (i.e., CNOP-P errors), which have the largest effect on the results of El Nino predictions. The resultant prediction errors were investigated in depth. The CNOP-P errors do not cause a noticeable prediction error of the sea surface temperature anomaly averaged over the Nino-3 region and do not show an obvious season-dependent evolution of the prediction errors. Consequently, the CNOP-P errors do not cause a significant spring predictability barrier (SPB) for El Nino events. In contrast, the initial errors that have the largest effect on the results of the predictions (i.e., the CNOP-I errors) show a season-dependent evolution, with the largest error increase in spring, and also cause a large prediction error, thereby generating a significant SPB. The initial errors play a more important role than the parameter errors in generating a significant SPB for El Nino events. To further validate this result, the authors investigated the situation in which CNOP-I and CNOP-P errors are simultaneously superimposed in the model, which may be a more credible approach because the initial errors and model parameter errors coexist under realistic predictions. The combined mode of CNOP-I and CNOP-P errors shows a similar season-dependent evolution to that of CNOP-I errors and yields a large prediction error, thereby inducing a significant SPB. The inference, therefore, is that initial errors play a more important role than model parameter errors in generating a significant SPB for El Nino predictions of the Zebiak-Cane model. This result helps to clarify the roles of the initial error and parameter error in the development of an SPB, and highlights the role of initial errors, which demonstrates that the SPB could be markedly reduced by improving the initial conditions. The results provide a theoretical basis for improving data assimilation in ENSO predictions.
学科主题	Meteorology & Atmospheric Sciences
收录类别	SCI
原文出处	10.1175/2011JCLI4022.1
语种	英语
WOS记录号	WOS:000300418500012
公开日期	2013-09-24
内容类型	期刊论文
源URL	[http://ir.qdio.ac.cn/handle/337002/12138]
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 Atmospher Phys, LASG, Beijing 100029, Peoples R China 2.Chinese Acad Sci, Inst Oceanol, Key Lab Ocean Circulat & Waves, Qingdao, Peoples R China
推荐引用方式 GB/T 7714	Yu, Yanshan,Mu, Mu,Duan, Wansuo. Does Model Parameter Error Cause a Significant "Spring Predictability Barrier" for El Nino Events in the Zebiak-Cane Model?[J]. JOURNAL OF CLIMATE,2012,25(4):1263-1277.
APA	Yu, Yanshan,Mu, Mu,&Duan, Wansuo.(2012).Does Model Parameter Error Cause a Significant "Spring Predictability Barrier" for El Nino Events in the Zebiak-Cane Model?.JOURNAL OF CLIMATE,25(4),1263-1277.
MLA	Yu, Yanshan,et al."Does Model Parameter Error Cause a Significant "Spring Predictability Barrier" for El Nino Events in the Zebiak-Cane Model?".JOURNAL OF CLIMATE 25.4(2012):1263-1277.