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Global Atmospheric Oscillation: An Integrity of ENSO and Extratropical Teleconnections

  • I. V. SerykhEmail author
  • D. M. Sonechkin
  • V. I. Byshev
  • V. G. Neiman
  • Yu. A. Romanov
Article
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Abstract

Many researchers have recognized the long distance teleconnections between El Niño–Southern Oscillation (ENSO) events and some other processes in the global climate system happening in areas often very far from the equatorial zone of the Pacific Ocean. In this paper we investigate similar links between ENSO and extratropical processes taken in their whole set. For this goal we compute differences between the sea-level pressure and the near-surface air (sea surface) temperature global fields which correspond to either El Niño or La Niña events observed since the end of the XIX century and up to the beginning of the XXI century. As a result, we establish that an integrity exists of ENSO and the extratropical teleconnections such as North Atlantic Oscillation (NAO), Arctic Oscillation (AO), the Northern Hemisphere annular (NHA) mode as well as the Pacific–North American (PNA) pattern, and their analogs in the Southern Hemisphere in the interannual timescale. Named this integrity the Global Atmospheric Oscillation (GAO), we define two representative indices of GAO, and investigate the temporal dynamics of these indices. This investigation reveals that GAO’s extratropical components may be real irrespective of ENSO while the latter accompanies GAO in all cases. Moreover, in view of a general eastward propagation of the GAO as a spatial structure, some its extratropical components show changes of their features prior the El Niño (La Niña) begins to form. Using these features as fingerprints of the forthcoming evolution of ENSO, we define another GAO index for the El Niño prediction with the lead-time of about 1 year. At last, we establish that some of the CMIP5-models reproduce GAO reasonably well.

Keywords

El Niño La Niña ENSO extratropical atmospheric teleconnections Global Atmospheric Oscillation (GAO) long-term El Niño prediction GAO in the CMIP5-models 

Notes

Acknowledgements

This work was supported by the Russian Science Foundation (Grant no. 14-50-00095), the Ministry of Science and Higher Education of the Russian Federation (Grant no. 0149-2018-0002).

Supplementary material

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Supplementary material 1 (PDF 3920 kb)
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Supplementary material 2 (AVI 9518 kb)

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Shirshov Institute of OceanologyRussian Academy of SciencesMoscowRussia

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