Abstract

This paper presents a stochastic model in space and time for significant wave height, a Bayesian hierarchical space-time model. The model consists of different components in a hierarchical manner including a component to model the contribution from long-term trends in the wave climate. As far as the authors are aware, no such model of significant wave height to date exploits the flexible framework of Bayesian hierarchical space-time models, which allow modelling of complex dependence structures in space and time and incorporation of physical features and prior knowledge, yet at the same time remains intuitive and easily interpreted. Furthermore, including a trend component in the model is a novel feature.The model presented in this paper has been fitted to significant wave height data for monthly maxima over an area in the North Atlantic ocean, and aims at describing the temporal and spatial variability of the data over a period of more than 44 years for the chosen area. In particular, the model identifies long-term trends present in the data. Subsequently, it will be explored how the results from the model can be linked to structural loads and response calculations. The proposed approach is illustrated by an example showing the potential impact of the estimated long-term trends of significant wave height on the wave-induced structural loads of an oil tanker.

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