Application of synthetic weather time series based on four-dimensional copula for modeling of maritime operations

This paper presents an approach to generate synthetic wind speed and wave height series for maritime environments with a four-dimensional copula using the Copulas Python library. The intended use of the approach is to generate weather data for maritime infrastructure operations modeling. For example, the ability to built and maintain offshore wind farms depends on the weather. The paper shows that this approach corrects a wave series discontinuity issue that was observed in an approach that was developed for a similar purpose. Overall, the results show that the proposed approach can produce credible weather time series. The series can be used for modeling so-called weather windows, which determine the times when maritime infrastructure can be accessed.