eps: huge amount of information - nwp model pool - ecmwf eps product family
DESCRIPTION
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. - PowerPoint PPT PresentationTRANSCRIPT
DWD 2nd SRNWP Workshop on Short Range Ensemble, Bologna, 7-8 April 2005
Deutscher WetterdienstZentrale Vorhersage
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• 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
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
- 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 ?