Spatial ensemble post-processing with standardized anomalies

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Working Papers in Economics and Statistics ; No. 2016-08

Classification and Topics

• Classification: Wirtschaft ; Forecasting Models; Simulation Methods ; Optimization Techniques; Programming Models; Dynamic Analysis ; Environmental Economics: General
• Subject: statistical post-processing ; ensemble post-processing ; spatial ; temperature ; standardized anomalies ; climatology ; generalized additive model

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Dabernig, Markus ; Mayr, Georg J. ; Messner, Jakob W. ; Zeileis, Achim
• Event: Veröffentlichung
• (who): University of Innsbruck, Research Platform Empirical and Experimental Economics (eeecon)
• (where): Innsbruck
• (when): 2016

Further information

• Handle: http://hdl.handle.net/10419/146125
• Last update: 10.03.2025, 11:42 AM CET