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The Mediterranean Sea is a basin with intense cyclonic activity. The multidimensional impact of such weather events on human life enhances the need and highlights the importance for further research. In this framework, there is a great interest for the development, evolution and impacts of tropical-like cyclones in the basin (medicanes). Besides their scientifically appealing features, their extremity and presence in a populated region with intense coastal activities can lead to social, natural and financial implications. The purpose of this work is the characterization of the risk exposed areas by this type of cyclones alongside their intensity and recurrence interval in terms of wind and wave parameters. In order to consider more than the strict and direct effects of

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Air–sea interface processes are highly associated with the evolution and intensity of marine-developed storms. Specifically, in the Mediterranean Sea, the air–ocean temperature deviations have a profound role during the several stages of Mediterranean cyclonic events. Subsequently, this enhances the need for better knowledge and representation of the sea surface temperature (SST). In this work, an analysis of the impact and uncertainty of the SST from different well-known datasets on the life-cycle of Mediterranean cyclones is attempted. Daily SST from the Real Time Global SST (RTG_SST) and hourly SST fields from the Operational SST and Sea Ice Ocean Analysis (OSTIA) and the NEMO ocean circulation model are implemented in the RAMS/ICLAMS-WAM coupled modeling system. For the needs of the study, the Mediterranean cyclones Trixi, Numa, and Zorbas were selected. Numerical experiments covered all stages of their life-cycles (five to seven days). Model results have been analyzed in terms of storm tracks and intensities, cyclonic structural characteristics, and derived heat fluxes. Remote sensing data from the Integrated Multi-satellitE Retrievals (IMERG) for Global Precipitation Measurements (GPM), Blended Sea Winds, and JASON altimetry missions were employed for a qualitative and quantitative comparison of modeled results in precipitation, maximum surface wind speed, and wave height. Spatiotemporal deviations in the SST forcing rather than significant differences in the maximum/minimum SST values, seem to mainly contribute to the differences between the model results. Considerable deviations emerged in the resulting heat fluxes, while the most important differences were found in precipitation exhibiting spatial and intensity variations reaching 100 mm. The employment of widely used products is shown to result in different outcomes and this point should be taken into consideration in forecasting and early warning systems.

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