Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 29, issue 4
Articles | Volume 29, issue 4
https://doi.org/10.5194/hess-29-1135-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-29-1135-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 29, issue 4
Research article
 | 
28 Feb 2025
Research article |  | 28 Feb 2025

Leveraging a radar-based disdrometer network to develop a probabilistic precipitation phase model in eastern Canada

Alexis Bédard-Therrien, François Anctil, Julie M. Thériault, Olivier Chalifour, Fanny Payette, Alexandre Vidal, and Daniel F. Nadeau

Viewed

Total article views: 1,563 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,034 373 156 1,563 49 102
  • HTML: 1,034
  • PDF: 373
  • XML: 156
  • Total: 1,563
  • BibTeX: 49
  • EndNote: 102
Views and downloads (calculated since 29 Apr 2024)
Cumulative views and downloads (calculated since 29 Apr 2024)

Viewed (geographical distribution)

Total article views: 1,563 (including HTML, PDF, and XML) Thereof 1,550 with geography defined and 13 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 18 Nov 2025
Download
Short summary
Precipitation data from an automated observational network in eastern Canada showed a temperature interval where rain and snow could coexist. Random forest models were developed to classify the precipitation phase using meteorological data to evaluate operational applications. The models demonstrated significantly improved phase classification and reduced error compared to benchmark operational models. However, accurate prediction of mixed-phase precipitation remains challenging.
Read more
Share