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

Abstract

AbstractA high‐resolution ensemble system, based on five runs of a limited‐area model (LAM), is described. The initial and boundary conditions for the LAM integrations are provided by the representative members (RMs) selected from the European Centre for Medium‐Range Weather Forecasts Ensemble Prediction System (EPS). EPS members are grouped in five clusters; then, from each cluster, an RM is selected, according to the methodology described in the companion paper. The ability of the high‐resolution ensemble system to predict the occurrence of heavy rainfall events (either five or six days ahead) is tested 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 highly populated cluster predicts the observed rainfall with a very good degree of time and spatial accuracy. In the other two cases, the extreme events are captured by at least one of the runs nested on the members of the less populated clusters. Probability maps constructed from LAM integrations provide great detail on the location of the regions affected by heavy precipitation and the information gained with respect to EPS probability maps and LAM deterministic forecasts is highlighted. The probabilistic estimates based on the LAM ensembles are also shown to be of valuable assistance to forecasters in issuing early flood alerts, contributing to the definition of a flood‐risk alarm system.