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

Hamill, Thomas M.; Whitaker, Jeffrey S.; Wei, Xue
June 2004
Monthly Weather Review;Jun2004, Vol. 132 Issue 6, p1434
Academic Journal
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 example, the MOS-based week 2 forecasts were more skillful than operational 6–10-day forecasts. Most of the benefit of the MOS approach could be achieved with 10 years of training data, and since sequential sample days provided correlated training data, the costs of reforecasts could also be reduced by skipping days between forecast samples. MOS approaches will still require a large dataset of retrospective forecasts in order to achieve their full benefit. This forecast model must remain unchanged until reforecasts have been computed for the next model version, a penalty that will slow down the implementation of model updates. Given the substantial improvements noted here, it is argued that reforecast-based MOS techniques should become an integral part of the medium-range forecast process despite this cost. Techniques for computing reforecasts while minimizing the impact to operational weather prediction facilities and model development are discussed.


Related Articles

  • Using Continuous Ground-Based Radar and Lidar Measurements for Evaluating the Representation of Clouds in Four Operational Models. Bouniol, Dominique; Protat, Alain; Delano, Julien; Pelon, Jacques; Piriou, Jean-Marcel; Bouyssel, François; Tompkins, Adrian M.; Wilson, Damian R.; Morille, Yohann; Haeffelin, Martial; O'Connor, Ewan J.; Hogan, Robin J.; Illingworth, Anthony J.; Donovan, David P.; Baltink, Henk-Klein // Journal of Applied Meteorology & Climatology;Sep2010, Vol. 49 Issue 9, p1971 

    The ability of four operational weather forecast models [ECMWF, Action de Recherche Petite Echelle Grande Echelle model (ARPEGE), Regional Atmospheric Climate Model (RACMO), and Met Office] to generate a cloud at the right location and time (the cloud frequency of occurrence) is assessed in the...

  • Sasaki’s Pivotal Contribution: Calculus of Variations Applied to Weather Map Analysis. Lewis, John; Lakshmivarahan, S. // Monthly Weather Review;Sep2008, Vol. 136 Issue 9, p3553 

    Yoshikazu Sasaki developed a variational method of data assimilation, a cornerstone of modern-day analysis and prediction in meteorology. Fundamentally, he formulated data assimilation as a constrained minimization problem with equality constraints. The generation of this idea is tracked by...

  • The impact of channel effect on Asian dust transport dynamics: a case in southeastern Asia. Lin, C.-Y.; Sheng, Y.-F.; Chen, W.-N.; Wang, Z.; Kuo, C.-H.; Chen, W.-C.; Yang, T. // Atmospheric Chemistry & Physics;2012, Vol. 12 Issue 1, p271 

    A super heavy dust event was identified with unprecedented PM10 in terms of speed and concentration in the southeastern Asia. The average concentration was observed exceeding the value of 1000 µgm-3 for the duration lasting more than 10 h, with the highest value reached 1724 µgm-3 in...

  • Verification of surface minimum, mean, and maximum temperature forecasts in Calabria for summer 2008.  // Natural Hazards & Earth System Sciences;2011, Vol. 11 Issue 2, p487 

    No abstract available.

  • A Comparison of Perturbed Initial Conditions and Multiphysics Ensembles in a Severe Weather Episode in Spain. Tapiador, Francisco J.; Tao, Wei-Kuo; Shi, Jainn Jong; Angelis, Carlos F.; Martinez, Miguel A.; Marcos, Cecilia; Rodriguez, Antonio; Hou, Arthur // Journal of Applied Meteorology & Climatology;Mar2012, Vol. 51 Issue 3, p489 

    Ensembles of numerical model forecasts are of interest to operational early warning forecasters as the spread of the ensemble provides an indication of the uncertainty of the alerts, and the mean value is deemed to outperform the forecasts of the individual models. This paper explores two...

  • A Transformed Lagged Ensemble Forecasting Technique for Increasing Ensemble Size. Lawrence, Andrew R.; Hansen, James A. // Monthly Weather Review;Apr2007, Vol. 135 Issue 4, p1424 

    An ensemble-based data assimilation approach is used to transform old ensemble forecast perturbations with more recent observations for the purpose of inexpensively increasing ensemble size. The impact of the transformations are propagated forward in time over the ensemble’s forecast...

  • Model Consensus. Fritsch, J.M.; Hilliker, J.; Ross, J.; Vislocky, R.L. // Weather & Forecasting;Oct2000, Vol. 15 Issue 5, p571 

    Consensus forecasts from the control runs of several operational numerical models are compared to 1) the control-run forecasts of the individual models that compose the consensus and to 2) other consensus forecasts generated by varying the initial conditions of the various individual models. It...

  • Comments on “Statistical Single-Station Short-Term Forecasting of Temperature and Probability of Precipitation: Area Interpolation and NWP Combination”. Leslie, Lance M.; Speer, Milton S. // Weather & Forecasting;Dec2001, Vol. 16 Issue 6, p765 

    Comments on the statistical single-station short-term forecasting of temperature and probability of precipitation. Benefits and disadvantages of RB99 forecasts system; Role of statistical techniques in short-term forecasting; Features of RB99 system.

  • Tubing: An Alternative to Clustering for the Classification of Ensemble Forecasts. Atger, Frederic // Weather & Forecasting;Oct99, Vol. 14 Issue 5, p741 

    Tubing is a method of classification of meteorological forecasts. The method has been designed to facilitate a human interpretation of the distribution of forecasts produced by an ensemble prediction system (EPS). This interpretation aims to complement probabilistic forecasts generated from EPS...


Read the Article


Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics