Asymmetric copula–based distribution models for met-ocean data in offshore wind engineering applications

Abstract

Joint statistical models for long-term wave climate are a key aspect of offshore wind engineering design. However, to find a joint model for sea-state characteristics is often difficult due to the complex nature of the wave climate and the physical constraints of sea-states phenomena. The available records of wave heights and periods are often very asymmetric in their nature. This article presents a copula-based approach to obtain the joint cumulative distribution function of the significant wave heights and the up-crossing mean period. This study is based on 124-month hindcast data concerning Horns Rev 3 offshore wind farm. The extra-parametrization technique of symmetric copulas is implemented to account for the asymmetry present in the data. The analysis of the total sea, the wind-sea and primary swell components is performed separately. The results show that the extra-parametrization technique with pairwise copulas consistently provided a better goodness-of-fit when compared to symmetric copulas. Moreover, it is demonstrated that the separation of the total sea into its components does not always improve the extra-parametrized copula’s performance. Furthermore, this article also discusses copulas application to offshore wind engineering.