SLEPS: Short-range limited-area ensemble prediction system

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Presentation transcript:

SLEPS: Short-range limited-area ensemble prediction system André Walser, Marco Arpagaus, Jean Quiby, Christof Appenzeller MeteoSwiss

SLEPS: Short-range adaptation of LEPS

Global ECMWF EPS ensembles with moist singular vectors SLEPS: current setup 50+1 members 5 representative members (RMs) 5 Lokal Modell (limited-area) integrations nested into 5 RMs SLEPS: Short-range limited-area Ensemble Prediction System 5 clusters Hierarchical Cluster Analysis area: Europe fields: 4 variables (U,V,Q,Z) at 3 levels (500, 700, 850) for 3 time-steps (24h, 48h, 72h) number of clusters: fixed to 5 Representative Member Selection one per cluster: member nearest (3D) to the mean of its own cluster AND most distant to the other clusters’ means Global ECMWF EPS ensembles with moist singular vectors

SLEPS: current setup (2) 10 km mesh-size horizontally, 32 vertical levels.

SLEPS: Lothar (26.12.99), wind gusts With moist SVs With dry SVs

SLEPS: Lothar, wind gusts With moist SVs With dry SVs

SLEPS: Martin (27.12.1999), wind gusts With moist SVs With dry SVs

SLEPS: Martin, wind gusts With moist SVs With dry SVs

Plans and questions Simulation of selected extreme events (mainly heavy precipitation cases) in the Alpine region. Is dynamical (SLEPS/LEPS) or statistical (neural network) down-scaling of the ECMWF EPS information superior? Are the down-scaling methods more skilful than the ECMWF EPS itself? Inter-comparison of SLEPS/LEPS dedicated neural network EFI → Objective verification