Literature DB >> 33712619

Impact of equatorial Atlantic variability on ENSO predictive skill.

Eleftheria Exarchou1, Pablo Ortega2, Belén Rodríguez-Fonseca3,4, Teresa Losada3, Irene Polo3, Chloé Prodhomme2,5,6.   

Abstract

El Niño-Southern Oscillation (ENSO) is a key mode of climate variability with worldwide climate impacts. Recent studies have highlighted the impact of other tropical oceans on its variability. In particular, observations have demonstrated that summer Atlantic Niños (Niñas) favor the development of Pacific Niñas (Niños) the following winter, but it is unclear how well climate models capture this teleconnection and its role in defining the seasonal predictive skill of ENSO. Here we use an ensemble of seasonal forecast systems to demonstrate that a better representation of equatorial Atlantic variability in summer and its lagged teleconnection mechanism with the Pacific relates to enhanced predictive capacity of autumn/winter ENSO. An additional sensitivity study further shows that correcting SST variability in equatorial Atlantic improves different aspects of forecast skill in the Tropical Pacific, boosting ENSO skill. This study thus emphasizes that new efforts to improve the representation of equatorial Atlantic variability, a region with long standing systematic model biases, can foster predictive skill in the region, the Tropical Pacific and beyond, through the global impacts of ENSO.

Entities:  

Year:  2021        PMID: 33712619     DOI: 10.1038/s41467-021-21857-2

Source DB:  PubMed          Journal:  Nat Commun        ISSN: 2041-1723            Impact factor:   14.919


  3 in total

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Authors:  Ping Chang; Yue Fang; R Saravanan; Link Ji; Howard Seidel
Journal:  Nature       Date:  2006-09-21       Impact factor: 49.962

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Authors:  C Wunsch
Journal:  Science       Date:  1990-05-18       Impact factor: 47.728

3.  Deterministic skill of ENSO predictions from the North American Multimodel Ensemble.

Authors:  Anthony G Barnston; Michael K Tippett; Meghana Ranganathan; Michelle L L'Heureux
Journal:  Clim Dyn       Date:  2017-03-13       Impact factor: 4.375

  3 in total

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