Spatial models for the variability of the significant wave height on the world oceans

Significant wave height ($H_s$) is a measure of the variability of the ocean surface. Benefits from knowing the spatial and temporal characteristics of this field are multiple: it is useful to dimension offshore structures, to foresee the fatigue of the ship's hull depending on its route and season, to compute probabilities of risks associated with marine operations. In this paper, we describe a method for modeling the $H_s$ in space. The method is based on the Gaussian hypothesis for the logarithms of $H_s$ and consists of estimating the mean and the covariance structure of $\log(H_s)$ using the information provided by the total variation. We then use the estimated parameters of every area in the world to construct maps of the median and the correlation structure. These maps are used to compute the probability the $H_s$ exceeds a pre-defined level, and the distribution of the length of a storm. The data used are that of the TOPEX-Poseidon satellite