Statistical occurrence and mechanisms of the 2014–2016 delayed super El Niño captured by a simple dynamical model

  • Sulian Thual
  • Andrew J. Majda
  • Nan Chen


The recent 2014–2016 period was marked by a failed El Niño favoring a subsequent extreme El Niño with dramatic worldwide impacts. Here this new type of major event so-called the delayed super El Niño is realistically captured by a simple dynamical model for the equatorial Pacific with emphasis on the role of state-dependent stochastic wind bursts. We analyze qualitative analogues for this event compared and contrasted with the 1997–1998 super El Niño in ensemble experiments based on the simple model. In agreement with recent studies, the timing and intensity of such an event is strongly controlled by atmospheric wind bursts, both easterly and westerly. In particular, the early stalling by easterly wind bursts and subsequent development by westerly wind bursts as observed during 2014–2016 is consistently retrieved. We show in addition that individual wind bursts may control the main characteristics of the event only during its early development while sequences of consecutive wind bursts have more important cumulative effects. Another important result from the present analysis is the significant statistical occurence of the delayed super El Niño (around 20–30%) compared with the one of directly formed super events as that of 1997–1998. Such a high occurence is directly linked to the random evolution of wind bursts and is retrieved here for all phases of the El Niño–Southern Oscillation used for the initiation of the ensemble experiments. These results suggest that the delayed super El Niño is not an unusual type of super event and could reoccur in the future.


Delayed super El Niño Simple dynamical models Stochastic wind bursts Ensemble experiments 



The research of A. J. M. is partially supported by the Office of Naval Research grant ONR MURI N00014-12-1-0912 and the center for Prototype Climate Modeling at the NYU Abu Dhabi Research Institute. S.T. and N.C. are supported as postdoctoral fellows through A.J.M.’s ONR MURI Grant. Reanalysis data in supplementary information is provided by NOAA/OAR/ESRL PSD, Boulder, Colorado, USA from their website ( The code and data of the experiments are available on application to the corresponding author.

Supplementary material

382_2018_4265_MOESM1_ESM.pdf (12 mb)
Supplementary material 1 (PDF 12258 KB)


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Mathematics, and Center for Atmosphere Ocean Science, Courant Institute of Mathematical SciencesNew York UniversityNew YorkUSA
  2. 2.Center for Prototype Climate ModelingNew York University Abu DhabiAbu DhabiUnited Arab Emirates

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