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 seastate phenomena. The available records of wave heights and periods are often very asymmetric in their nature. This paper presents a copula-based approach to obtain the joint cumulative distribution function of significant wave heights and the mean up-crossing periods. This study is based on 124 months 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 extraparametrization technique with pairwise copulas consistently provided a better goodnessof-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 extraparametrized copula's performance. Furthermore, this paper also discusses copula application to offshore wind engineering.