The effect of temporal dependence on the estimation of the frequency of extreme ocean climate events

Abstract

The term ‘extreme ocean climate estimation’ refers to the assessment of the statistical distribution of extreme oceanographical geophysical variables. Components of the ocean climate are variables, such as the storm surge, wind velocity and significant wave height. Important characteristics of extreme ocean climate are the frequencies of the exceedances of ocean climate variables over selected thresholds. Assuming that exceedances are statistically independent of each other, their frequencies can be estimated using non-homogeneous Poisson processes. However, exceedances often exhibit temporal dependency because of the tendency of storms to gather in clusters. We assess the effect of these dependencies on the estimation of the rate of occurrence of extreme events. Using a database built under the HIPOCAS European project, which covers the Western Mediterranean Sea, we compare the performance of the non-homogeneous Poisson process approach versus a new model that allows for temporal dependency. We show that the latter outperforms the former in terms of the resulting goodness of fit and significance of the parameters involved.