期刊
CLIMATE DYNAMICS
卷 43, 期 5-6, 页码 1311-1325出版社
SPRINGER
DOI: 10.1007/s00382-013-1946-y
关键词
El Nino Southern Oscillation (ENSO); Predictability; Teleconnections
资金
- Institut de Recherche pour le Developpement (IRD)
- Minsitere de l'Enseignement Superieur et de la Recherche
- Institut National des Sciences de l'Univers (INSU) LEFE program
In this paper we seek to identify inter-annual sea surface temperature anomalies (SSTA) patterns outside the tropical Pacific that may influence El Nio/Southern Oscillation (ENSO) through atmospheric teleconnections. We assume that a linear ENSO hindcast based on tropical Pacific warm water volume and Nio3.4 SSTA indices captures tropical Pacific intrinsic predictability inherent to recharge oscillator dynamics. This simple hindcast model displays statistically significant skill at the 95 % confidence level at leads of up to seven seasons ahead of the ENSO peak. Our results reveal that ENSO-independent equatorial wind stress anomalies only significantly improve the skill of that linear hindcast at the 95 % level in boreal spring and summer before the ENSO peak and in boreal fall, five seasons ahead of the ENSO peak. At those seasons, the robust large-scale SST patterns that provide a statistically significant enhancement of ENSO predictability are related to the Atlantic meridional mode and south Pacific subtropical dipole mode in spring, the Indian Ocean Dipole and the south Atlantic subtropical dipole mode in fall. While the first two regions display significant simultaneous correlations with western equatorial Pacific wind stress in three reanalyses (ERA-I, NCEP and NCEP2), the Indian Ocean Dipole and south Atlantic subtropical dipole mode correlation with Pacific winds is less robust amongst re-analyses. We discuss our results in view of other studies that suggest a remote influence of various regions on ENSO. Although modest, the sensitivity of our results to the dataset and to details of the analysis method illustrates that finding regions that influence ENSO from the statistical analysis of observations is a difficult task.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据