Simultaneous Ensemble Post-Processing for Multiple Lead Times with Standardized Anomalies
Markus Dabernig (),
Georg J. Mayr (),
Jakob W. Messner () and
Achim Zeileis ()
Working Papers from Faculty of Economics and Statistics, University of Innsbruck
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.
Keywords: standardized anomalies; non-homogeneous regression; ensemble post-processing; probabilistic temperature forecasts (search for similar items in EconPapers)
JEL-codes: C53 C61 Q50 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:inn:wpaper:2016-31
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