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Stochastic representation of model uncertainties in the ECMWF ensemble prediction system

Quarterly Journal of the Royal Meteorological Society · 1999 · Vol. 125(560) · pp. 2887–2908
Roberto BuizzaM. MilleerT. N. Palmer

Abstract

Abstract A stochastic representation of random error associated with parametrized physical processes (‘stochastic physics’) is described, and its impact in the European Centre for Medium‐Range Weather Forecasts Ensemble Prediction System (ECMWF EPS) is discussed. Model random errors associated with physical parametrizations are simulated by multiplying the total parametrized tendencies by a random number sampled from a uniform distribution between 0.5 and 1.5. A number of diagnostics are described and a choice of parameters is made. It is shown how the scheme increases the spread of the ensemble, and improves the skill of the probabilistic prediction of weather parameters such as precipitation. A choice of stochastic parameters is made for operational implementation. the scheme was implemented successfully in the operational ECMWF EPS on 21 October 1998.

Meteorological Phenomena and SimulationsClimate variability and modelsPrecipitation Measurement and AnalysisProbabilistic logicRepresentation (politics)Range (aeronautics)Ensemble forecastingStochastic processStochastic modellingNumerical weather predictionPrecipitationEnsemble averageComputer science
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References
Ensemble Forecasting at NMC: The Generation of Perturbations
Bulletin of the American Meteorological Society · 1993 · 1,239 citations
The ECMWF Ensemble Prediction System: Methodology and validation
Quarterly Journal of the Royal Meteorological Society · 1996 · 1,617 citations
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