Observations and mechanisms of a simple stochastic dynamical model capturing El Niño diversity

Nan Chen, Andrew J. Majda, Sulian Thual

Research output: Contribution to journalArticle

Abstract

El Niño-Southern Oscillation (ENSO) has significant impact on global climate and relevance for seasonal forecasts. Recently, a simple modeling framework was developed that captures the ENSO diversity, where state-dependent stochastic wind bursts and nonlinear advection of sea surface temperature are coupled to a simple ocean-atmosphere model that is otherwise deterministic, linear, and stable. In this article, the coupled model is compared with observations using reanalysis data over the last 34 yr, where the observed non-Gaussian statistics and the overall mechanisms of ENSO are both captured by the model. Then the formation mechanisms of both the central Pacific (CP) and the traditional El Niño in the model are systematically studied. First, ocean Rossby waves induced by easterly trade wind anomalies facilitate the heat content buildup. Then the reflected ocean Kelvin waves and the nonlinear advection lead to positive SST anomalies in the CP region and create a CP El Niño. Second, two formation mechanisms are revealed for the traditional El Niño, including the super (extreme) El Niño. The first mechanism indicates a preferred wind structure with easterly wind bursts (EWBs) leading westerly wind bursts (WWBs), where the EWBs build up heat content and then the WWBs trigger the El Niño. The second mechanism links the two types of El Niño, where a CP El Niño favors a heat content buildup and the advent of a traditional El Niño. This article also highlights the mechanisms of La Niña formation and El Niño termination.

Original languageEnglish (US)
Pages (from-to)449-471
Number of pages23
JournalJournal of Climate
Volume31
Issue number1
DOIs
StatePublished - Jan 1 2018

Keywords

  • Atmosphere-ocean interaction
  • Coupled models
  • ENSO
  • Parameterization
  • Statistics
  • Stochastic models

ASJC Scopus subject areas

  • Atmospheric Science

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