Stochastic Analysis of Southern and Pacific Ocean Sea Surface Winds

Abstract

This paper shows that the synoptic variability of zonal and meridional midlatitude Pacific and Southern Ocean sea surface winds can be well described by a univariate stochastic dynamical system directly derived from data. The method used to analyze blended Quick Scatterometer (QuikSCAT)?NCEP winds is a general method to estimate drift and diffusion coefficients of a continuous stationary Markovian system. Almost trivially, the deterministic part consists of a simple, nearly linear damping term. More importantly, the stochastic part appears to be a state-dependent white noise term, that is, multiplicative noise. The need for a multiplicative noise term to describe the variability of midlatitude winds can be interpreted by the fact that the variability of midlatitude winds increases with increasing wind speed. The results indicate that a complete stochastic description of midlatitude winds requires a state-dependent white noise term, that is, multiplicative noise. A simple Ornstein?Uhlenbeck process is not sufficient to describe the wind data within a stochastic framework. The method used fails for tropical regions, suggesting that tropical variability might be non-Markovian.