Towards a unified framework for maximum wave computation from numerical models: outcomes from the LATEMAR project.

Reliable prediction of oceanic waves during severe marine storms has always been foremost for offshore platform design, coastal activities, and navigation safety. Indeed, many damaging accidents and casualties during storms were ascribed to the impact with abnormal and unexpected waves. However, predicting extreme wave occurrence is a challenging task, at first, because of their inherent randomness, and because the observation of large ocean waves, of primary importance to assess theoretical and numerical models, is limited by the costs and risks of deployment during severe open-ocean sea-state conditions.

In the context of the EU-based Copernicus Marine Environment Monitoring Service (CMEMS) evolution, the LATEMAR project (https://www.mercator-ocean.fr/en/portfolio/latemar/) aimed at improving the modelling of large wave events during marine storms. Indeed, at present, operational systems only provide average and peak wave parameters, with no information on individual waves whatsoever. However, developments of the state-of-the-art third-generation wave models demonstrated that using the directional wave spectrum moments into theoretical statistical models for wave extremes, forecasters are able to accurately infer the expected shape and likelihood of the maximum waves during storms.

The main purpose of the activity is therefore to provide the wave models WAM and WAVEWATCH III with common procedures to explicitly estimate the maximum wave heights for each sea state. LATEMAR achieved this goal by: performing an extensive assessment of the model maximum waves using field observations collected from an oceanographic tower; comparing WAM and WAVEWATCH III maximum wave estimates in the Mediterranean Sea; investigating the sensitivity of the maximum waves on the main sea state parameters. All model developments and evaluations resulting from this research project will be directly applicable to the wave model forecasting systems to expand their catalogue.