Seasonal synchronization of a simple stochastic dynamical model capturing El Niño diversity

Sulian Thual, Andrew Majda, Nan Chen

Research output: Contribution to journalArticlepeer-review

Abstract

Recently, a simple stochastic dynamical model was developed that automatically captures the diversity and intermittency of El Niño-Southern Oscillation (ENSO) in nature, where state-dependent stochastic wind bursts and nonlinear advection of sea surface temperature (SST) are coupled to simple ocean-atmosphere processes that are otherwise deterministic, linear, and stable. In the present article, it is further shown that the model can reproduce qualitatively the ENSO synchronization (or phase locking) to the seasonal cycle in nature. This goal is achieved by incorporating a cloud radiative feedback that is derived naturally from the model's atmosphere dynamics with no ad hoc assumptions and accounts in simple fashion for the marked seasonal variations of convective activity and cloud cover in the eastern Pacific. In particular, the weak convective response to SSTs in boreal fall favors the eastern Pacific warming that triggers El Niño events while the increased convective activity and cloud cover during the following spring contributes to the shutdown of those events by blocking incoming shortwave solar radiations. In addition to simulating the ENSO diversity with realistic non-Gaussian statistics in different Niño regions, the eastern Pacific moderate and super El Niño and the central Pacific El Niño and La Niña show a realistic chronology with a tendency to peak in boreal winter as well as decreased predictability in spring consistent with the persistence barrier in nature. The incorporation of other possible seasonal feedbacks in the model is also documented for completeness.

Original languageEnglish (US)
Pages (from-to)10047-10066
Number of pages20
JournalJournal of Climate
Volume30
Issue number24
DOIs
StatePublished - Dec 1 2017

Keywords

  • ENSO
  • Seasonal cycle
  • Wind bursts

ASJC Scopus subject areas

  • Atmospheric Science

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