The main goal of the ECMWF Special Project SPITCAPE is to understand the information content of the current ensemble systems both at global and meso scales in re-forecasting past high-impact weather events. In particular one of the main questions addressed in the project is: what is the added value of running a high-resolution (namely convection-permitting) ensembles for high-impact weather events with respect to global ones? Running operational Ensemble Prediction Systems (EPS) at the convection-permitting (CP) scale is currently on the agenda at a number of European weather forecasting services and research centres: UK Met Office, Météo France and DWD to mention a few. Moreover, in the framework of the activities of the forthcoming ItaliaMeteo agency, it is foreseen the development of a regional EPS at CP scale for the Italian domain. Recently, it has been demonstrated that the baseline approach of dynamical downscaling using CP models nested in a global ensemble with a coarser horizontal resolution (e.g. 20 km) provides valuable information. Since the introduction of the IFS model cycle 41r2 in March 2016, the horizontal resolution of the ECMWF ensemble forecasts (ENS) is about 18 km and it is planned to be further increased up to 10 km in the next future (after the installation of the new supercomputer in the Bologna data center). Thus, these higher-resolution global ENS data allow us to estimate the technical feasibility and value of the simple dynamical downscaling method to initialise limited-area and CP models (the WRF-ARW, MESO-NH and MOLOCH models in the present case) directly nested in the new ECMWF global ensemble. We applied this pragmatic approach in re-forecasting two high-impact weather events occurred in Italy in recent years (the Cinque Terre flooding occurred in October 2011 and the flash flood of Genoa in November 2011) with the ENS global forecasts and the data produced with the WRF-ARW, MESO-NH and MOLOCH models. The skills of the forecasts in the short-range are evaluated in terms of Probability of Precipitation exceeding predefined rainfall thresholds. In the medium-range we report and discuss the forecast uncertainty (i.e. ensemble spread) of ENS at different starting dates. Besides the fact that both global and regional model data under-estimate rainfall maxima in the area of interest, results demonstrate that CP ensemble forecasts provide better predictions regarding the occurrence of extreme precipitations and the area most likely affected. The comparison among results obtained with regional models contribute to the debate regarding the reliability of these models and their strengths and weaknesses with respect to: (I) the accuracy of the results for the two events considered, (II) the integration with ECMWF products, (III) the ease of implementation and (IV) the computational costs in view of a potential use for operational forecasting activities.