Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/156185
Authors: 
Dabernig, Markus
Mayr, Georg J.
Messner, Jakob W.
Zeileis, Achim
Year of Publication: 
2016
Series/Report no.: 
Working Papers in Economics and Statistics 2016-31
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.
Subjects: 
standardized anomalies
non-homogeneous regression
ensemble post-processing
probabilistic temperature forecasts
Document Type: 
Working Paper

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