Survey of stochastic models for wind and sea state time series

Abstract

The knowledge of sea state and wind conditions is of central importance for many offshore and nearshore operations. In this paper, we make a complete survey of stochastic models for sea state and wind time series. We begin with methods based on Gaussian processes, then non-parametric resampling methods for time series are introduced followed by various parametric models. We also propose an original statistical method, based on Monte Carlo goodness-of-fit tests, for model validation and comparison and this method is illustrated on an example of multivariate sea state time series.