Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/146125
Authors: 
Dabernig, Markus
Mayr, Georg J.
Messner, Jakob W.
Zeileis, Achim
Year of Publication: 
2016
Series/Report no.: 
Working Papers in Economics and Statistics 2016-08
Abstract: 
To post-process ensemble predictions to a particular location, often statistical methods are used, especially in complex terrain such as the Alps. When expanded to several stations, the post-processing has to be repeated at every station individually thus losing information about spatial coherence and increasing computational cost. Therefore, we transform observations and predictions to standardized anomalies. Site- and seasonspecific characteristics are eliminated by subtracting a climatological mean and dividing by the climatological standard deviation from both observations and numerical forecasts. Then ensemble post-processing can be applied simultaneously at multiple locations. Furthermore, this method allows to forecast even at locations where no observations are available. The skill of these forecasts is comparable to forecasts post-processed individually at every station, and even better on average.
Subjects: 
statistical post-processing
ensemble post-processing
spatial
temperature
standardized anomalies
climatology
generalized additive model
JEL: 
C53
C61
Q50
Document Type: 
Working Paper

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