Downscaling of ECMWF Ensemble Forecasts for Cases of Severe Weather: Ensemble Statistics and Cluster Analysis

Abstract

Dynamical downscaling has been applied to global ensemble forecasts to assess its impact for four cases of severe weather (precipitation and wind) over various parts of Croatia. It was performed with the Croatian 12.2-km version of the Aire Limitée Adaptation Dynamique Développement International (ALADIN) limited-area model, nested in the ECMWF TL255 (approximately 80 km) global ensemble prediction system (EPS). The 3-hourly EPS output was used to force the ALADIN model over the central European/northern Mediterranean domain. Results indicate that the identical clustering algorithm may yield differing results when applied to either global or to downscaled ensembles. It is argued that this is linked to the fact that a downscaled, higher-resolution ensemble resolves more explicitly small-scale features, in particular those strongly influenced by orographic forcing. This result has important implications in limited-area ensemble prediction, since it implies that downscaling may affect the interpretation or relevance of the global ensemble forecasts; that is, it may not always be feasible to make a selection (or a subset) of global lower-resolution ensemble members that might be representative of all possible higher-resolution evolution scenarios.