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Forecast verification is a long-standing issue of the whole meteorologists' community. A common definition of a truly satisfying prediction skill has not been achieved so far. Even the definition of "event", due to its spatio-temporal discontinuity, is highly affected by uncertainty. Moreover, decision-making demands numerical weather prediction modellers to provide information about the "in- ner" uncertainty, i.e. the degree of uncertainty related to the choice of a specific setting of the model (microphysics, tur- bulence scheme, convective closure, etc.). Most European Mediterranean countries, due to dense de- velopment, steep coastal orography and short hydrological response time of the drainage basins, have to deal very fre- quently with flash floods and sudden shallow land sliding im- pacting on urban areas. Civil protection organizations are in place to issue early warnings in order to allow local author- ities and population to take precautionary measures. To do so in Mediterranean catchments, hydrologists are required to use numerical rainfall predictions in place of rainfall obser- vations on large European catchments. Estimating the measure of uncertainty is for this reason crucial. The goal of this work is to propose an objective evaluation of the performance of the currently operational weather pre- diction model COSMO-I7 over quite a long time period and to check forecast verification at different space-time scales by the comparison of predictions with observations. Due to large investments in the last years, in fact, Italy has built up one of the most dense hourly-reporting network of rain gauges. The network has a mean space density of about 1/100 km 2 , very similar to the horizontal resolution of

Dealing with uncertainty: an analysis of the severe weather events over Italy in 2006