Evaluating wind datasets for wave hindcasting in the NW Iberian Peninsula coast

Abstract

ABSTRACT The available wind datasets can be exploited to support the setup of accurate wave models, able to reproduce and forecast extreme event scenarios. It is of utmost importance in the actual context of climate change. This study focuses on evaluating the performance of a numerical wave model, using different wind datasets, helping to create a tool to assess coastal risks, and further on to support the future implementation of reliable warning systems based on numerical models. The numerical model SWAN was implemented, configured and validated for the NW Iberian Peninsula coast, as a test case region. A period of two months, from December 2013 to January 2014, was simulated due to the winter storms that crossed the area. Six distinct wind datasets were selected to test their suitability in regional wave modelling. The results were validated against several sets of wave buoy data, considering wave parameters such as significant wave height, mean wave period and peak direction. The implemented wave model configuration allowed the representation of the wave evolution with relatively good accuracy. All the wind datasets were able to produce reasonably good wave condition estimates. The dataset that best represented the wave properties varied from one wave parameter to another, but the most reliable for the selected region was the reanalysis product generated at the European Centre for Medium-Range Weather Forecasts.