Characterization of extreme wave fields during Mediterranean tropical-like cyclones - Davison, Silvio; Benetazzo, Alvise; Barbariol, Francesco; Ricchi, Antonio; Ferretti, Rossella (Frontiers in Marine Science, 2024)
The Mediterranean Sea is a primary source of food, ecosystem services and economic activities and one of the most active cyclogenetic regions in the world, where the influence of orographic and morphological features of the relatively small basin plays an important role. Together with the explosive cyclogenesis, tropical-like cyclones (also called Mediterranean Hurricanes or Medicanes) are among the strongest types of storms that can be found in the Mediterranean basin, occurring predominantly in the Ionian, Balearic and Tyrrhenian sub-basins. Similarly to tropical cyclones (Hurricanes or Typhoons), these cyclonic structures are characterized by strong rotating and translating wind fields, which often lead to a combination of remotely generated swell waves and locally generated wind waves, often referred to as crossing sea states. Despite the well-known potential of Medicanes to cause significant damage near islands and coastal zones, which is predicted to intensify as a result of climate change, to date the characterization of maximum individual waves generated during these events is still lacking. In this study, we carry out the first analysis of the large-scale geographical distribution of wave maxima within the wave fields generated during three recent Medicane events using the WAVEWATCH III® spectral wave model forced by ERA5 reanalysis winds, also investigating the influence of crossing sea states on the maximum wave amplitudes with novel statistical formulations developed for such conditions. Our results show that, as in the case of tropical cyclones, several regions of the cyclone field are characterized by crossing sea states, whose role in the formation of the maximum individual waves occurring near the eye of the storm was found to be confined. Furthermore, extreme wave predictions accounting for the local crossing conditions yield differences up to 5% compared to standard statistical distributions.