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Nonlinear Processes in Geophysics An interactive open-access journal of the European Geosciences Union
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Volume 10, issue 6
Nonlin. Processes Geophys., 10, 463–468, 2003
https://doi.org/10.5194/npg-10-463-2003
© Author(s) 2003. This work is licensed under
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.

Special issue: Quantifying Predictability

Nonlin. Processes Geophys., 10, 463–468, 2003
https://doi.org/10.5194/npg-10-463-2003
© Author(s) 2003. This work is licensed under
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.

  31 Dec 2003

31 Dec 2003

Increasing the horizontal resolution of ensemble forecasts at CMC

G. Pellerin1, L. Lefaivre1, P. Houtekamer2, and C. Girard3 G. Pellerin et al.
  • 1Canadian Meteorological Centre, Montreal, Canada
  • 2Data Assimilation and Satellite Meteorological Division, Montreal, Canada
  • 3Recherche en Prevision Numerique Dorval, Canada

Abstract. Ensemble forecasts are run operationally since February 1998 at the Canadian Meteorological Centre, with outputs up to ten days. The ensemble size was increased from eight to sixteen members in August 1999. The method of producing the perturbed analyses consists of running independent assimilation cycles that use perturbed sets of observations and are driven by eight different models, mainly different in their physical parameterizations. Perturbed analyses are doubled by taking opposite pairs. A multi-model approach is then used to obtain the forecasts. The ensemble output has been used to generate several products. In view of increasing computing facilities, the ensemble prediction system horizontal resolution was increased to TL149 in June 2001. Heights at 500 hPa and mean sea-level pressure maps are regularly used. Charts of precipitation with the probability of precipitation being above various thresholds are also produced at each run. The probabilistic forecast of the 24-h accumulated precipitation has shown skill as demonstrated by the relative operating characteristic (ROC). Verifications of the ensemble forecasts will be presented.

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