Ensemble Reforecasting: Improving Medium-Range Forecast Skill Using Retrospective Forecasts

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Abstract
The value of the model output statistics (MOS) approach to improving 6–10-day and week 2 probabilistic forecasts of surface temperature and precipitation is demonstrated. Retrospective 2-week ensemble “reforecasts” were computed using a version of the NCEP medium-range forecast model with physics operational during 1998. An NCEP–NCAR reanalysis initial condition and bred modes were used to initialize the 15-member ensemble. Probabilistic forecasts of precipitation and temperature were generated by a logistic regression technique with the ensemble mean (precipitation) or ensemble mean anomaly (temperature) as the only predictor. Forecasts were computed and evaluated during 23 winter seasons from 1979 to 2001. Evaluated over the 23 winters, these MOS-based probabilistic forecasts were skillful and highly reliable. When compared against operational NCEP forecasts for a subset of 100 days from the 2001–2002 winters, the MOS-based forecasts were comparatively much more skillful and reliable. For examp... Abstract The value of the model output statistics (MOS) approach to improving 6–10-day and week 2 probabilistic forecasts of surface temperature and precipitation is demonstrated. Retrospective 2-week ensemble “reforecasts” were computed using a version of the NCEP medium-range forecast model with physics operational during 1998. An NCEP–NCAR reanalysis initial condition and bred modes were used to initialize the 15-member ensemble. Probabilistic forecasts of precipitation and temperature were generated by a logistic regression technique with the ensemble mean (precipitation) or ensemble mean anomaly (temperature) as the only predictor. Forecasts were computed and evaluated during 23 winter seasons from 1979 to 2001. Evaluated over the 23 winters, these MOS-based probabilistic forecasts were skillful and highly reliable. When compared against operational NCEP forecasts for a subset of 100 days from the 2001–2002 winters, the MOS-based forecasts were comparatively much more skillful and reliable. For examp...