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.
Abstract. Many phenomena (such as attenuation and range degradation) can influence the accuracy of rainfall radar estimates. They introduce errors that increase as the distance from radar increases, thereby decreasing the reliability of radar estimates for applications that require quantitative precipitation estimation. The present paper evaluates radar error as a function of the range, in order to correct the rainfall radar estimates. The radar is calibrated utilizing data from the rain gauges. Then, the G/R ratio between the yearly rainfall amount measured in each rain gauge position during 2008 and the corresponding radar rainfall amount is calculated against the slant range. The trend of the G/R ratio shows two behaviours: a concave part due to the melting layer effect close to the radar location and an almost linear, increasing trend at greater distances. A best fitting line is used to find an adjustment factor, which estimates the radar error at a given range. The effectiveness of the methodology is verified by comparing pairs of rainfall time series that are observed simultaneously by collocated rain gauges and radar. Furthermore, the variability of the adjustment factor is investigated at the scale of event, both for convective and stratiform events. The main result is that there is not a univocal range error pattern, as it also depends on the characteristics of the considered event. On the other hand, the adjustment factor tends to stabilize itself for time aggregations of the order of one year or greater.
Abstract. Flash flood events are floods characterised by a very rapid response of basins to storms, often resulting in loss of life and property damage. Due to the specific spacetime scale of this type of flood, the lead time available for triggering civil protection measures is typically short. Rainfall threshold values specify the amount of precipitation for a given duration that generates a critical discharge in a given river cross section. If the threshold values are exceeded, it can produce a critical situation in river sites exposed to alluvial risk. It is therefore possible to directly compare the observed or forecasted precipitation with critical reference values, without running online real-time forecasting systems. The focus of this study is the Mignone River basin, located in Central Italy. The critical rainfall threshold values are evaluated by minimising a utility function based on the informative entropy concept and by using a simulation approach based on radar data. The study concludes with a system performance analysis, in terms of correctly issued warnings, false alarms and missed alarms.
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