A Non-Gaussian Stochastic Model for the El Ni\~no Southern Oscillation

TL;DR

This paper introduces a non-Gaussian stochastic model for ENSO that captures its seasonal variability, non-Gaussian statistics, and hidden processes using sea surface temperature data.

Contribution

It develops a novel non-autonomous stochastic model with systematic statistical estimation, effectively reproducing ENSO's complex behaviors and hidden dynamics.

Findings

Successfully reproduces ENSO's seasonal phase locking.

Captures the non-Gaussian statistical features of ENSO.

Recovers hidden process time series like thermocline depth and wind bursts.

Abstract

A non-autonomous stochastic dynamical model approach is developed to describe the seasonal to interannual variability of the El Ni\~no-Southern Oscillation (ENSO). We determine the model coefficients by systematic statistical estimations using partial observations involving only sea surface temperature data. Our approach reproduces the observed seasonal phase locking and its uncertainty, as well as the highly non-Gaussian statistics of ENSO. Finally, we recover the intermittent time series of the hidden processes, including the thermocline depth and the wind bursts.