Season-dependent predictability and error growth dynamics for La Nina predictions

doi:10.1007/s00382-019-04631-5

IOCAS-IR > 海洋环流与波动重点实验室

	Season-dependent predictability and error growth dynamics for La Nina predictions
	Hu, Junya 1; Duan, Wansuo 2,3; Zhou, Qian 4
	2019-07-01
发表期刊	CLIMATE DYNAMICS
ISSN	0930-7575
卷号	53 期号:1-2 页码:1063-1076
通讯作者	Duan, Wansuo([email protected])
摘要	The spring predictability barrier (SPB) is a well-known characteristic of ENSO prediction, which has been widely studied for El Nino events. However, due to the nonlinearity of the coupled ocean-atmosphere system and the asymmetries between El Nino and La Nina, it is worthy to investigate the SPB for La Nina events and reveal their differences with El Nino. This study investigates the season-dependent predictability of sea surface temperature (SST) for La Nina events by exploring initial error growth in a perfect model scenario within the Community Earth System Model. The results show that for the prediction through the spring season, the prediction errors caused by initial errors have a season-dependent evolution and induce an SPB for La Nina events. Two types of initial errors that often yield the SPB phenomenon are identified: the first are type-1 initial errors showing positive SST errors in the central-eastern equatorial Pacific accompanied by a large positive error in the upper layers of the eastern equatorial Pacific. The second are type-2 errors presenting an SST pattern with positive errors in the southeastern equatorial Pacific and a west-east dipole pattern in the subsurface ocean. The type-1 errors exhibit an evolving mode similar to the growth phase of an El Nino-like event, while the type-2 initially experience a La Nina-like decay and then a transition to the growth phase of an El Nino-like event. Both types of initial errors cause positive prediction errors for Nino3 SST and under-predict the corresponding La Nina events. The resultant prediction errors of type-1 errors are owing to the growth of the initial errors in the upper layers of the eastern equatorial Pacific. For the type-2 errors, the prediction errors originate from the initial errors in the subsurface layers of the western equatorial Pacific. These two regions may represent the sensitive areas of targeted observation for La Nina prediction. In addition, the type-2 errors in the equatorial regions are enlarged by the recharge process from 10 degrees N in the central Pacific during the eastward propagation. Therefore, the off-equatorial regions around 10 degrees N in the central Pacific may represent another sensitive area of La Nina prediction. Additional observations may be prioritized in these identified sensitive areas to better predict La Nina events.
关键词	La Nina events Spring predictability barrier Initial errors
DOI	10.1007/s00382-019-04631-5
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[41690124]###2376; National Natural Science Foundation of China[41706016]###2743; National Natural Science Foundation of China[41525017]###2744; National Natural Science Foundation of China[41606019]###2745; National Programme on Global Change and Air-Sea Interaction[GASI-IPOVAI-06]###371; National Natural Science Foundation of China[41690124]; National Natural Science Foundation of China[41706016]; National Natural Science Foundation of China[41525017]; National Natural Science Foundation of China[41606019]; National Programme on Global Change and Air-Sea Interaction[GASI-IPOVAI-06]
WOS研究方向	Meteorology & Atmospheric Sciences
WOS类目	Meteorology & Atmospheric Sciences
WOS记录号	WOS:000471722400061
出版者	SPRINGER
引用统计	被引频次：11[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.qdio.ac.cn/handle/337002/161762
专题	海洋环流与波动重点实验室
通讯作者	Duan, Wansuo
作者单位	1.Chinese Acad Sci, Inst Oceanol, CAS Key Lab Ocean Circulat & Waves, Qingdao 266071, Shandong, Peoples R China 2.Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Numer Modeling Atmospher Sci & Geop, Beijing 100029, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 4.Minist Nat Resources, Natl Marine Environm Forecasting Ctr, Beijing 100081, Peoples R China
第一作者单位	中国科学院海洋研究所
推荐引用方式 GB/T 7714	Hu, Junya,Duan, Wansuo,Zhou, Qian. Season-dependent predictability and error growth dynamics for La Nina predictions[J]. CLIMATE DYNAMICS,2019,53(1-2):1063-1076.
APA	Hu, Junya,Duan, Wansuo,&Zhou, Qian.(2019).Season-dependent predictability and error growth dynamics for La Nina predictions.CLIMATE DYNAMICS,53(1-2),1063-1076.
MLA	Hu, Junya,et al."Season-dependent predictability and error growth dynamics for La Nina predictions".CLIMATE DYNAMICS 53.1-2(2019):1063-1076.

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