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Simultaneous Ensemble Post-Processing for Multiple Lead Times with Standardized Anomalies

Author

Listed:
  • Markus Dabernig
  • Georg J. Mayr
  • Jakob W. Messner
  • Achim Zeileis

Abstract

Statistical post-processing of ensemble predictions is usually adjusted to a particular lead time so that several models must be fitted to forecast multiple lead times. To increase the coherence between lead times, we propose to use standardized anomalies instead of direct observations and predictions. By subtracting a climatological mean and dividing by the climatological standard deviation, lead-time-specific characteristics are eliminated and several lead times can be forecasted simultaneously. The results show that forecasts between +12 and +120 h can be fitted together with a comparable forecast skill to a conventional method. Furthermore, forecasts can be produced with a temporal resolution as high as the observation interval e.g., up to ten minutes.

Suggested Citation

  • Markus Dabernig & Georg J. Mayr & Jakob W. Messner & Achim Zeileis, 2016. "Simultaneous Ensemble Post-Processing for Multiple Lead Times with Standardized Anomalies," Working Papers 2016-31, Faculty of Economics and Statistics, Universität Innsbruck.
    • Handle: RePEc:inn:wpaper:2016-31
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    References listed on IDEAS

    as
    1. Reto Stauffer & Jakob W. Messner & Georg J. Mayr & Nikolaus Umlauf & Achim Zeileis, 2016. "Ensemble Post-Processing of Daily Precipitation Sums over Complex Terrain Using Censored High-Resolution Standardized Anomalies," Working Papers 2016-21, Faculty of Economics and Statistics, Universität Innsbruck.
    2. R. A. Rigby & D. M. Stasinopoulos, 2005. "Generalized additive models for location, scale and shape," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(3), pages 507-554, June.
    3. Stasinopoulos, D. Mikis & Rigby, Robert A., 2007. "Generalized Additive Models for Location Scale and Shape (GAMLSS) in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 23(i07).
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    standardized anomalies; non-homogeneous regression; ensemble post-processing; probabilistic temperature forecasts;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • Q50 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - General

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