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

Viewed

Total article views: 5,509 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
4,604 840 65 5,509 66 141
  • HTML: 4,604
  • PDF: 840
  • XML: 65
  • Total: 5,509
  • BibTeX: 66
  • EndNote: 141
Views and downloads (calculated since 13 Mar 2025)
Cumulative views and downloads (calculated since 13 Mar 2025)

Viewed (geographical distribution)

Total article views: 5,562 (including HTML, PDF, and XML) Thereof 5,562 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 17 Jun 2026
Download
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.
Share