A strategy for high-resolution ensemble prediction. II: Limited-area experiments in four Alpine flood events

A high-resolution ensemble system, based on five runs of a limited-area mod el (LAM), is described. The initial and boundary conditions for the LAM int egrations are provided by the representative members (RMs) selected from th e European Centre for Medium-Range Weather Forecasts Ensemble Prediction Sy stem (EPS). EPS members are grouped in five clusters; then, from each clust er, an RM is selected, according to the methodology described in the compan ion paper. The ability of the high-resolution ensemble system to predict th e occurrence of heavy rainfall events (either five or six days ahead) is te sted for four cases of floods over the Alpine region. Results show that, in two case-studies, the LAM integration corresponding to the RM of the highl y populated cluster predicts the observed rainfall with a very good degree of time and spatial accuracy. In the other two cases, the extreme events ar e captured by at least one of the runs nested on the members of the less po pulated clusters. Probability maps constructed from LAM integrations provid e great detail on the location of the regions affected by heavy precipitati on and the information gained with respect to EPS probability maps and LAM deterministic forecasts is highlighted. The probabilistic estimates based o n the LAM ensembles are also shown to be of valuable assistance to forecast ers in issuing early flood alerts, contributing to the definition of a floo d-risk alarm system.