Predicting wind power with reforecasts

Markus Dabernig*, Georg J. Mayr, Jakob W. Messner

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review


Energy traders and decision-makers need accurate wind power forecasts. For this purpose, numerical weather predictions (NWPs) are often statistically postprocessed to correct systematic errors. This requires a dataset of past forecasts and observations that is often limited by frequent NWP model enhancements that change the statistical model properties. Reforecasts that recompute past forecasts with a recent model pro- vide considerably longer datasets but usually have weaker setups than operationalmodels. This study tests the reforecasts from the National Oceanic and Atmospheric Administration (NOAA) and the European Centre forMedium-RangeWeather Forecasts (ECMWF) for wind power predictions. The NOAAreforecast clearly performs worse than the ECMWF reforecast, the operational ECMWF deterministic and ensemble forecasts, and a limited-area model of the Austrian weather service [Zentralanstalt fürMeteorologie und Geodynamik (ZAMG)]. On the contrary, the ECMWF reforecast has, of all testedmodels, the smallest squared errors and one of the highest financial values in an energy market.

Original languageEnglish
JournalWeather and Forecasting
Issue number6
Pages (from-to)1655-1662
Number of pages8
Publication statusPublished - 2015
Externally publishedYes


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