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Effects of Indian Ocean Dipole initialization on the forecasting of La Nina 1 year in advance
Zhang, Shouwen1; Wang, Jing4,5,6; Jiang, Hua2; Wang, Hui2,7; Yuan, Dongliang3,5,6,8
2023-05-19
发表期刊CLIMATE DYNAMICS
ISSN0930-7575
页码17
通讯作者Wang, Hui(wangh@nmefc.cn) ; Yuan, Dongliang(dyuan@fio.org.cn)
摘要The influence of strong Indian Ocean Dipole (IOD) events on the evolution of the following year's La Nina events is investigated using the National Marine Environmental Forecasting Center (NMEFC) operational seasonal forecasting system. The observation results show that when the strong IOD occurs, the tropical Pacific can be in different sea surface temperature states. As such prediction system can well reproduce the air-sea evolution of the 1998/1999 and 2020/2021 La Nina events, the ocean temperature initializations in December during above events were perturbed with the system to assess the role of the oceanic channel and atmospheric bridge across the maritime continent in the forecasting of the La Nina events 1 year later. In the case of the neutral state of the tropical Pacific at the peak of the 2019 positive IOD, pacemaker experiments have demonstrated that the Indian Ocean subsurface temperature initialization in December 2019 is critically important for the successful prediction of the 2020/2021 La Nina. Experiments of sea surface temperature initialization in December 2019, with only the Indo-Pacific atmospheric bridge at work, failed to predict the 2020/2021 La Nina 1 year in advance. The comparison underlined the dominant role of the oceanic channel dynamics in the evolution of the 2020/2021 La Nina. Forecasting experiments beginning from the 1997/98 El Nino with and without the IOD initializations suggest that the delayed feedback of the tropical Pacific coupled system is more important in the forecasting of the 1998/1999 La Nina, with the Indo-Pacific oceanic channel dynamics playing a secondary yet very important role. Our study has underscored the importance of the Indo-Pacific oceanic channel dynamics in ENSO prediction and suggested the effectiveness of IOD subsurface temperature initialization in La Nina predictions at the 1-year lead time.
关键词La Nina forecast Indian Ocean Dipole Oceanic channel Atmospheric bridge
DOI10.1007/s00382-023-06816-5
收录类别SCI
语种英语
资助项目National Key R&D Program of China[2020YFA0608804] ; NSFC[42206029] ; NSFC[41720104008] ; NSFC[91858204] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDB42000000] ; Southern Marine and Engineering Guangdong Laboratory (Zhuhai)[SML2020SP008]
WOS研究方向Meteorology & Atmospheric Sciences
WOS类目Meteorology & Atmospheric Sciences
WOS记录号WOS:000990977300002
出版者SPRINGER
WOS关键词SEA-SURFACE TEMPERATURE ; EARTH SYSTEM MODEL ; CLIMATE VARIABILITY ; EL-NINO ; TROPICAL PACIFIC ; CHANNEL DYNAMICS ; ENSO ; PREDICTABILITY ; PREDICTION ; EVOLUTION
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被引频次:1[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/337002/183233
专题海洋环流与波动重点实验室
通讯作者Wang, Hui; Yuan, Dongliang
作者单位1.Southern Marine Sci & Engn Guangdong Lab Zhuhai, Zhuhai, Peoples R China
2.Natl Marine Environm Forecasting Ctr, Key Lab Res Marine Hazards Forecasting, Beijing, Peoples R China
3.Minist Nat Resources, Inst Oceanog 1, Key Lab Marine Sci & Numer Modeling, Shandong Key Lab Marine Sci & Numer Modeling, Qingdao, Peoples R China
4.Chinese Acad Sci, Inst Oceanol, Ctr Ocean Mega Sci, CAS Key Lab Ocean Circulat & Waves, Qingdao, Peoples R China
5.Laoshan Lab, Qingdao, Peoples R China
6.Univ Chinese Acad Sci, Beijing, Peoples R China
7.Shandong Univ, Inst Marine Sci & Technol, Qingdao, Peoples R China
8.Shandong Key Lab Marine Sci & Numer Modeling, Qingdao, Peoples R China
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Zhang, Shouwen,Wang, Jing,Jiang, Hua,et al. Effects of Indian Ocean Dipole initialization on the forecasting of La Nina 1 year in advance[J]. CLIMATE DYNAMICS,2023:17.
APA Zhang, Shouwen,Wang, Jing,Jiang, Hua,Wang, Hui,&Yuan, Dongliang.(2023).Effects of Indian Ocean Dipole initialization on the forecasting of La Nina 1 year in advance.CLIMATE DYNAMICS,17.
MLA Zhang, Shouwen,et al."Effects of Indian Ocean Dipole initialization on the forecasting of La Nina 1 year in advance".CLIMATE DYNAMICS (2023):17.
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