Methodology for Characterization of Marine Environment for Offshore Renewables

This paper will present a method of reproduction and characterization of the marine environment for predicting meteorological and oceanographic conditions as part of the analysis of extreme environmental impacts. In this context, the focus is on numerical models, where meteorological and oceanographic data analysis includes characterization of wind, wave, current and combined conditions. The characterization of meteorological and oceanographic data requires applications and several statistical techniques are needed to characterize and analyses time-series data. The method is implemented in a software application to automate the process and to support the assessment of extreme conditions. The application is designed for importing, analyzing and visualizing wind, wave and current resource data. Resource data can be imported from a variety of different formats allowing for quality control and statistical analyses, and the functionality to export data to software commonly used within the offshore renewable energy industry. It can be used to create time series graphs, wind and wave roses, frequency histograms, scatterplots, and more, including formatted reports. The analytical strategy takes into account that joint environmental models are required to assess the different environmental variables under extreme load and response conditions, using two analysis strategies, namely the global initial distribution strategy and the event-based strategy for extreme conditions. The extreme value theory in more than one variable introduces additional problems in which the methods of multivariate extremes are used to track how the dependence between extreme values changes over time and over another covariate. This paper also takes into account sustainable technology development, where there are many well-established techniques for characterizing the marine environment that serve as input for numerical simulations.