Spatial ensemble post-processing with standardized anomalies

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

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review


To post-process ensemble predictions for a particular location, statistical methods are often 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, the ensemble post-processing is modified and applied simultaneously at multiple locations. We transform observations and predictions to standardized anomalies. Seasonal and site-specific characteristics are eliminated by subtracting a climatological mean and dividing by the climatological standard deviation from both observations and numerical forecasts. This method allows us 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 is even better on average.

Original languageEnglish
JournalQuarterly Journal of the Royal Meteorological Society
Issue number703
Pages (from-to)909-916
Number of pages8
Publication statusPublished - 1 Jan 2017
Externally publishedYes


  • climatology
  • ensemble post-processing
  • generalized additive model
  • spatial
  • standardized anomalies
  • statistical post-processing
  • temperature

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