Articles | Volume 29, issue 4
https://doi.org/10.5194/hess-29-1135-2025
https://doi.org/10.5194/hess-29-1135-2025
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

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2024-78', Anonymous Referee #1, 28 May 2024
    • AC1: 'Reply on RC1', Alexis Bédard-Therrien, 01 Aug 2024
  • RC2: 'Comment on hess-2024-78', Anonymous Referee #2, 30 May 2024
    • AC2: 'Reply on RC2', Alexis Bédard-Therrien, 01 Aug 2024
  • RC3: 'Comment on hess-2024-78', James Feiccabrino, 11 Jun 2024
    • AC3: 'Reply on RC3', Alexis Bédard-Therrien, 01 Aug 2024

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
ED: Reconsider after major revisions (further review by editor and referees) (06 Sep 2024) by Shraddhanand Shukla
AR by Alexis Bédard-Therrien on behalf of the Authors (13 Sep 2024)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (28 Sep 2024) by Shraddhanand Shukla
RR by Anonymous Referee #2 (29 Oct 2024)
RR by Anonymous Referee #1 (03 Nov 2024)
ED: Publish subject to technical corrections (21 Dec 2024) by Shraddhanand Shukla
AR by Alexis Bédard-Therrien on behalf of the Authors (08 Jan 2025)  Author's response   Manuscript 
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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.
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