Institutional Repository of Key Laboratory of Ocean Circulation and Wave Studies, Institute of Oceanology, Chinese Academy of Sciences
Sea Surface Salinity Strongly Weakens ENSO Spring Predictability Barrier | |
Pang, Yiqun1,2; Jin, Yishuai1,2,3; Zhao, Yingying3; Chen, Xianyao1,2,3; Li, Xueqi4; Liu, Ting4,5; Hu, Junya6 | |
2023-12-16 | |
发表期刊 | GEOPHYSICAL RESEARCH LETTERS |
ISSN | 0094-8276 |
卷号 | 50期号:23页码:11 |
通讯作者 | Jin, Yishuai([email protected]) ; Zhao, Yingying([email protected]) |
摘要 | Previous studies suggested that tropical sea surface salinity (SSS) can influence tropical Pacific sea surface temperature (SST) through mixing and entrainment and thus it may be a signal for El Nino-Southern Oscillation (ENSO) prediction. This paper explores the influence of SSS on ENSO spring predictability barrier (SPB) using an empirical dynamic model - Linear Inverse Model (LIM). By coupling and decoupling SSS in the LIM, we find that tropical Pacific SSS plays a significant role in weakening both Central-Pacific and Eastern-Pacific ENSO SPB. The evolution of optimal initial structure also shows the importance of SSS dynamics in ENSO. We found an SSS mode that plays the dominant role in SSS impacting ENSO prediction. By the analysis of lead-lag correlation, we find that this mode can induce easterlies during the spring, which finally leads to a La Nina-like SST pattern in the winter through zonal advective and thermocline feedbacks. The spring predictability barrier (SPB) is a phenomenon of forecast skill reduction of the El Nino-Southern Oscillation (ENSO) when it comes to the boreal spring, regardless of the initial month. Sea surface salinity (SSS) can influence sea surface temperature by altering sea surface density and thus it may be a signal for ENSO prediction. Using a linear dynamical model, we find that SSS plays an important role in improving the forecast skill of ENSO and weakening SPB. We further find that SSS can induce the easterlies during the spring, which finally leads to a La Nina-like SST pattern. Our study suggests that SSS can be used to predict ENSO about 1 year later. A linear dynamical model suggests that taking sea surface salinity (SSS) into consideration can strongly weaken Central-Pacific and Eastern-Pacific El Nino-Southern Oscillation (ENSO) spring predictability barrier (SPB)A new SSS mode is found to be important for weakening ENSO SPBThe SSS mode can predict ENSO events about 1 year earlier by inducing sea surface temperature and wind anomalies in the early spring |
关键词 | ENSO spring predictability barrier sea surface salinity optimal initial structure |
DOI | 10.1029/2023GL106673 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | Chinese NSFC[NSFC41825012]; Chinese NSFC[42206013]; Shandong Provincial Natural Science Foundation, China[ZR202102240275]; Shandong Provincial Natural Science Foundation, China[NSFC42206025]; Taishan Scholars Program[tsqn202306299] |
WOS研究方向 | Geology |
WOS类目 | Geosciences, Multidisciplinary |
WOS记录号 | WOS:001111672900001 |
出版者 | AMER GEOPHYSICAL UNION |
WOS关键词 | INTERMEDIATE COUPLED MODEL ; FRESH-WATER FLUX ; EL-NINO ; SOUTHERN-OSCILLATION ; PERSISTENCE BARRIER ; EQUATORIAL PACIFIC ; OCEAN ; VARIABILITY ; PREDICTIONS ; REANALYSIS |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.qdio.ac.cn/handle/337002/183967 |
专题 | 海洋环流与波动重点实验室 |
通讯作者 | Jin, Yishuai; Zhao, Yingying |
作者单位 | 1.Ocean Univ China, Frontier Sci Ctr Deep Ocean Multispheres & Earth S, Qingdao, Peoples R China 2.Ocean Univ China, Phys Oceanog Lab, Qingdao, Peoples R China 3.Laoshan Lab, Qingdao, Peoples R China 4.Second Inst Oceanog, Minist Nat Resources, State Key Lab Satellite Ocean Environm Dynam, Hangzhou, Peoples R China 5.Southern Marine Sci & Engn Guangdong Lab, Zhuhai, Peoples R China 6.Chinese Acad Sci, Inst Oceanol, Key Lab Ocean Circulat & Waves, Qingdao, Peoples R China |
推荐引用方式 GB/T 7714 | Pang, Yiqun,Jin, Yishuai,Zhao, Yingying,et al. Sea Surface Salinity Strongly Weakens ENSO Spring Predictability Barrier[J]. GEOPHYSICAL RESEARCH LETTERS,2023,50(23):11. |
APA | Pang, Yiqun.,Jin, Yishuai.,Zhao, Yingying.,Chen, Xianyao.,Li, Xueqi.,...&Hu, Junya.(2023).Sea Surface Salinity Strongly Weakens ENSO Spring Predictability Barrier.GEOPHYSICAL RESEARCH LETTERS,50(23),11. |
MLA | Pang, Yiqun,et al."Sea Surface Salinity Strongly Weakens ENSO Spring Predictability Barrier".GEOPHYSICAL RESEARCH LETTERS 50.23(2023):11. |
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