Articles | Volume 11, issue 1
https://doi.org/10.5194/ascmo-11-23-2025
https://doi.org/10.5194/ascmo-11-23-2025
13 Mar 2025
 | 13 Mar 2025

Proper scoring rules for multivariate probabilistic forecasts based on aggregation and transformation

Romain Pic, Clément Dombry, Philippe Naveau, and Maxime Taillardat

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Short summary
Correctly forecasting weather is crucial for decision-making in various fields. Standard multivariate verification tools have limitations, and a single tool cannot fully characterize predictive performance. We formalize a framework based on aggregation and transformation to build interpretable verification tools. These tools target specific features of forecasts, improving predictive performance characterization and bridging the gap between theoretical and physics-based tools.
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