The new ECMWF VAREPS (Variable Resolution Ensemble Prediction System)

The European Centre for Medium-Range Weather Forecasts (ECMWF) Variable Resolution Ensemble Prediction System (VAREPS) is a system designed to provide skilful predictions of small-scale, severe-weather events in the early forecast range, and accurate large-scale forecast guidance in the extended forecast range (say beyond forecast day 7). In this work, first the rationale behind VAREPS is presented, and then the performance of VAREPS with a truncation at forecast day 7, i.e. TL399L40(d0–7) and TL255L40(d7–15), is discussed and compared to the performance of two constant resolution systems, a TL255L40 and a TL319L40 (this latter one requires similar computing resources to VAREPS). Average results based on up to 111 cases indicate that VAREPS has a higher forecast-time-integrated skill, and it provides better forecasts in the early forecast range without losing accuracy in the long forecast range. In the early forecast range, the differences in forecast performance can be very large and responsible for substantial improvements in the prediction of weather variables such as surface wind, significant wave height and total precipitation, as was shown in two case-studies. Average results have also shown that the VAREPS extension to 15 days (the old EPS system was run operationally only up to forecast day 10) will provide users with some skilful extended-range forecasts. Copyright © 2007 Royal Meteorological Society

[1]  Roberto Buizza,et al.  Impact of Ensemble Size on Ensemble Prediction , 1998 .

[2]  A. Hollingsworth,et al.  Reply to Comments by Wilson and by Juras , 2000 .

[3]  Istvan Szunyogh,et al.  The Effect of Increased Horizontal Resolution on the NCEP Global Ensemble Mean Forecasts , 2002 .

[4]  R. Buizza,et al.  The 1966 ''century'' flood in Italy: A meteorological and hydrological revisitation , 2006 .

[5]  Rex J. Fleming,et al.  ON STOCHASTIC DYNAMIC PREDICTION , 1971 .

[6]  J A Swets,et al.  Form of empirical ROCs in discrimination and diagnostic tasks: implications for theory and measurement of performance. , 1986, Psychological bulletin.

[7]  M. Ehrendorfer.  The Liouville Equation and Its Potential Usefulness for the Prediction of Forecast Skill. Part I: Theory , 1994 .

[8]  G. Brier.  VERIFICATION OF FORECASTS EXPRESSED IN TERMS OF PROBABILITY , 1950 .

[9]  Eugenia Kalnay,et al.  Operational Ensemble Prediction at the National Meteorological Center: Practical Aspects , 1993 .

[10]  E. Kalnay,et al.  Ensemble Forecasting at NCEP and the Breeding Method , 1997 .

[11]  Roberto Buizza,et al.  Tropical singular vectors computed with linearized diabatic physics , 2001 .

[12]  Jean-Raymond Bidlot,et al.  Potential Benefits of Using Probabilistic Forecasts for Waves and Marine Winds Based on the ECMWF Ensemble Prediction System , 2004 .

[13]  W. Briggs.  Statistical Methods in the Atmospheric Sciences , 2007 .

[14]  Roberto Buizza,et al.  The Singular-Vector Structure of the Atmospheric Global Circulation , 1995 .

[15]  C. Leith.  Theoretical Skill of Monte Carlo Forecasts , 1974 .

[16]  Roberto Buizza,et al.  3D‐Var Hessian singular vectors and their potential use in the ECMWF ensemble prediction system , 1999 .

[17]  E. Epstein,et al.  Stochastic dynamic prediction , 1969 .

[18]  Mats Hamrud,et al.  Impact of model resolution and ensemble size on the performance of an Ensemble Prediction System , 1998 .

[19]  A. Hollingsworth,et al.  Probabilistic Predictions of Precipitation Using the ECMWF Ensemble Prediction System , 1999 .

[20]  Rex J. Fleming,et al.  ON STOCHASTIC DYNAMIC PREDICTION: I. The Energetics of Uncertainty and the Question of Closure , 1971 .

[21]  T. Palmer,et al.  Stochastic representation of model uncertainties in the ECMWF ensemble prediction system , 2007 .

[22]  E. Epstein,et al.  Stochastic dynamic prediction1 , 1969 .

[23]  Thomas A. Gleeson.  Statistical-Dynamical Predictions , 1970 .

[24]  Laurence J. Wilson,et al.  Comments on “Probabilistic Predictions of Precipitation Using the ECMWF Ensemble Prediction System” , 2000 .

[25]  David S. Richardson,et al.  Benefits of increased resolution in the ECMWF ensemble system and comparison with poor‐man's ensembles , 2003 .

[26]  F. Molteni,et al.  The ECMWF Ensemble Prediction System: Methodology and validation , 1996 .