Ensemble Postprocessing
Ensemble Postprocessing is a statistical methodology that refines raw ensemble model outputs by correcting systematic biases and quantifying forecast uncertainty to yield calibrated probabilistic forecasts.
158
Publications
12.6K
Citations
371
Authors
180
Institutions
Publications per year
2017–2026
71
158
Using Bayesian Model Averaging to Calibrate Forecast Ensembles
Adrian E. Raftery, Tilmann Gneiting, Fadoua Balabdaoui et al. · Monthly Weather Review · 2005 · 2K citations · Full text
Thordis L. Thorarinsdottir, Tilmann Gneiting · Journal of the Royal Statistical Society Series A (Statistics in Society) · 2009 · 271 citations · Full text
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180
Heidelberg Institute for Theoretical Studies
Heidelberg, Germany
13 h-index
14 publications
816 citations
Heidelberg University
Heidelberg, Germany
11 h-index
19 publications
2.5K citations
Karlsruhe Institute of Technology
Karlsruhe, Germany
11 h-index
28 publications
1.5K citations
NOAA Earth System Research Laboratory
Boulder, United States
11 h-index
15 publications
1.2K citations

Centre National de la Recherche Scientifique
Paris, France
10 h-index
28 publications
1.8K citations

European Centre for Medium-Range Weather Forecasts
Reading, United Kingdom
8 h-index
22 publications
1K citations
Cooperative Institute for Research in Environmental Sciences
Boulder, United States
7 h-index
8 publications
451 citations

Universität Innsbruck
Innsbruck, Austria
7 h-index
23 publications
1.1K citations
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33 publications · 5.4K citations
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22 publications · 1.1K citations
18
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10 publications · 509 citations
10
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8 publications · 398 citations
8
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6 publications · 170 citations
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