Arbeitspapier
Spatial ensemble post-processing with standardized anomalies
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.
- Sprache
-
Englisch
- Erschienen in
-
Series: Working Papers in Economics and Statistics ; No. 2016-08
- Klassifikation
-
Wirtschaft
Forecasting Models; Simulation Methods
Optimization Techniques; Programming Models; Dynamic Analysis
Environmental Economics: General
- Thema
-
statistical post-processing
ensemble post-processing
spatial
temperature
standardized anomalies
climatology
generalized additive model
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Dabernig, Markus
Mayr, Georg J.
Messner, Jakob W.
Zeileis, Achim
- Ereignis
-
Veröffentlichung
- (wer)
-
University of Innsbruck, Research Platform Empirical and Experimental Economics (eeecon)
- (wo)
-
Innsbruck
- (wann)
-
2016
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:42 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Dabernig, Markus
- Mayr, Georg J.
- Messner, Jakob W.
- Zeileis, Achim
- University of Innsbruck, Research Platform Empirical and Experimental Economics (eeecon)
Entstanden
- 2016
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