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Warm Season Ensembles


Bill Bua



Archived Training





Last Updated:



Objectives: Help forecasters make use of newly available (in AWIPS) ensemble information from the medium- and short-range ensemble forecasts (MREF and SREF, respectively) in the forecast process.


  • Review of science behind ensemble prediction systems (EPS), post-processing of EPS data, and structure of the NCEP SREF and MREF.
  • Uses of MREF in the forecast process.
  • Uses of the SREF in the forecast process.

This training will emphasize the SREF.

Training Session Options

NOAA/NWS students – to begin the training, use the web-based video, YouTube video, or audio playback options below (if present for this session). Certificates of completion for NOAA/NWS employees can be obtained by accessing the session via the Commerce Learn Center

  1. Audio playback (recommended for low-bandwidth users) – This is an audio playback version in the form of a downloadable VISITview and can be taken at anytime.

    Create a directory to download the audio playback file (91 MB) from the following link:

    After extracting the files into that directory click on either the visitplay.bat or visitauto.bat file to start the lesson. If both files are present, use visitauto.bat

References/Additional Links

  • Kalnay, Eugenia, 2005. Atmospheric Modeling, Data Assimilation and Predictability. Cambridge University Press, New York, 364 pp.
  • Molteni, F., Buizza, R., Palmer, T. N., & Petroliagis, T., 1996: The new ECMWF ensemble prediction system: methodology and validation. Q. J. R. Meteorol. Soc., 122, 73-119.
  • Toth, Z, & Kalnay, E., 1993: Ensemble Forecasting at NMC: the generation of perturbations. Bull. Amer. Meteorol. Soc., 74, 2317-2330.
  • Tracton, M S, & Kalnay, E, 1993: Operational ensemble prediction at the National Meteorological Center. Weather & Forecasting, 8, 379-398.
  • Zhu, Yuejian, Zoltan Toth, Richard Wobus, David Richardson, and Kenneth Mylne, 2002. The Economic Value Of Ensemble-Based Weather Forecasts. Bull. Am. Meteorol. Soc., 83, 73-83.
This course is Basic

Students are encouraged to take at least one of the ensemble prediction modules:


Bill Bua

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Bernie Connell


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