Atmosphere Ocean Science Colloquium
Simple Stochastic Dynamical Models Capturing the Statistical Diversity of El Nino Southern Oscillation
Speaker: Nan Chen, Courant
Location: Warren Weaver Hall 1302
Date: Wednesday, March 1, 2017, 3:30 p.m.
The El Nino Southern Oscillation (ENSO) has significant impact on global climate and seasonal prediction. A simple modeling framework is developed here that automatically captures the statistical diversity of ENSO. First, a stochastic parameterization of the wind bursts including both westerly and easterly winds is coupled to a simple ocean-atmosphere model that is otherwise deterministic, linear and stable. Secondly, a simple nonlinear zonal advection with no ad-hoc parameterization of the background sea surface temperature (SST) gradient and a mean easterly trade wind anomaly representing the multidecadal acceleration of the trade wind are both incorporated into the coupled model that enable anomalous warm SST in the central Pacific. Then a three-state stochastic Markov jump process is utilized to drive the wind burst activity that depends on the strength of the western Pacific warm pool in a simple and effective fashion. It allows the coupled model to simulate the quasi-regular moderate traditional El Nino, the super El Nino, the central Pacific (CP) El Nino as well as the La Nina with realistic features. In addition to the anomalous SST, the Walker circulation anomalies at different ENSO phases all resemble those in nature. In particular, the coupled model succeeds in reproducing the observed episode during 1990s, where a series of 5-year CP El Nino is followed by a super El Nino and then a La Nina. Importantly, both the variance and the non-Gaussian statistical features in different Nino regions spanning from the western to the eastern Pacific are captured by the coupled model.