Advances in Statistical Climatology, Meteorology and Oceanography
Advances in Statistical Climatology, Meteorology and Oceanography
ASCMO
Articles | Volume 11, issue 1
Articles | Volume 11, issue 1
https://doi.org/10.5194/ascmo-11-23-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/ascmo-11-23-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 11, issue 1
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: 4,540 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
3,938 546 56 4,540 54 125
  • HTML: 3,938
  • PDF: 546
  • XML: 56
  • Total: 4,540
  • BibTeX: 54
  • EndNote: 125
Views and downloads (calculated since 13 Mar 2025)
Cumulative views and downloads (calculated since 13 Mar 2025)

Viewed (geographical distribution)

Total article views: 4,585 (including HTML, PDF, and XML) Thereof 4,585 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 16 Apr 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.
Read more
Share