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0. Introduction. Severe weather prediction by ensemble prediction tools - it´s a challenge - great variability of weather events Forecaster has to deal with the predictability of the event, the cost-lost-ratio, customer needs, model physics.
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0. Introduction • Severe weather prediction by ensemble prediction tools - • it´s a challenge - great variability of weather events • Forecaster has to deal with the predictability of the event, • the cost-lost-ratio, customer needs, model physics ... 1. First steps - and still favorable used at the DWD • AFREG-MIX: developed during the eighties in Potsdam • low cost system (CPU-time) • Mixing GME and ECMWF and deriving weather parameter • by statistical methods - Metgrams, tables 2. Using an EPS - from the forecasters point of view • EPS: huge amount of information • - NWP model pool • - ECMWF EPS product family • - COSMO-LEPS, SRNWP PEPS • - previous EPS (or model) runs • decision for a certain szenario in a limited time frame - automatically generated fc´s (AFREG, GMOS) - forecasters experience Questions: 1. Is it possible to add value to forecasts by simple mixing of NWP models without of any calibration ? 2. The main szenario provided by the EPS or the majority of the NWP models - is this always the correct one ? 3. Could a NWP model PEPS outperform the ECMWF EPS ? 2nd SRNWP Workshop on Short Range Ensemble, Bologna, 7-8 April 2005
