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Medicanes, hurricane-like cyclonic systems in the Mediterranean Sea, are becoming an increasingly severe problem for many Mediterranean countries because climate projections suggest a higher risk under anthropogenic forcing even under an intermediate scenario. Due to the small size of these weather systems, high-resolution data are required to better resolve their structure and evolution. Here we investigate medicanes from the perspective of precipitation using the high-resolution (0.25) ERA-5 reanalysis data released by European Centre for Medium-Range Weather Forecasts. Overall, we identify a total of 59 medicanes from ERA-5 data during 1979-2017, with marked year-to-year variability. These storms tend to occur mostly between September and March. Overall, the intensity of medicanes (i.e., maximum wind) is lower than that of tropical cyclones, and this is also true for precipitation. The composite precipitation of medicanes increases from the centre to $0.8 and then decreases. During 1979-2017, many regions along the Mediterranean Sea experienced over 20 extreme precipitation events (i.e., days) which were caused by medicanes, accounting for 2-5% of all the extreme precipitation events.

Abstract. An operative methodology for rainfall thresholds definition is illustrated, in order to provide at critical river section optimal flood warnings. Threshold overcoming could produce a critical situation in river sites exposed to alluvial risk and trigger the prevention and emergency system alert. The procedure for the definition of critical rainfall threshold values is based both on the quantitative precipitation observed and the hydrological response of the basin. Thresholds values specify the precipitation amount for a given duration that generates a critical discharge in a given cross section and are estimated by hydrological modelling for several scenarios (e.g.: modifying the soil moisture conditions). Some preliminary results, in terms of reliability analysis (presence of false alarms and missed alarms, evaluated using indicators like hit rate and false alarm rate) for the case study of Mignone River are presented.

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