Sebastian Scher
PhD student at MISU

Selective Ensemble Mean Technique for Severe Mid-latitude Storms

Sebastian Scher, PhD student at MISU.
Sebastian Scher, PhD student at MISU.

Wind storms are the leading source of insured losses in Europe and can cause severe social and economic damage. Accurately forecasting both their intensity and position is therefore of crucial importance. We show that ensemble forecasts of extreme European wind storms can be improved by sub-selecting ensemble members based on their performance at very short lead times (up to 12h). This applies to both the ensemble mean position of cyclone centers and the ensemble mean windstorm footprint over the continent. Since ensemble forecasts are typically initialized every 12h and disseminated several hours after initialization, our approach has the potential to provide improved forecasts in an operational context. The analysis is performed on GEFS reforecast data.

Time and Place
Thursday March 22th 2018, 14.15
Rossbysalen C609, Arrhenius Laboratory, 6th floor