Articles | Volume 15, issue 12
Model description paper
27 Jun 2022
Model description paper |  | 27 Jun 2022

Snow Multidata Mapping and Modeling (S3M) 5.1: a distributed cryospheric model with dry and wet snow, data assimilation, glacier mass balance, and debris-driven melt

Francesco Avanzi, Simone Gabellani, Fabio Delogu, Francesco Silvestro, Edoardo Cremonese, Umberto Morra di Cella, Sara Ratto, and Hervé Stevenin


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2021-92', Anonymous Referee #1, 10 May 2021
    • AC1: 'Reply on RC1', Francesco Avanzi, 15 May 2021
  • RC2: 'Comment on gmd-2021-92', Anonymous Referee #2, 25 Oct 2021
    • AC2: 'Reply on RC2', Francesco Avanzi, 09 Dec 2021
  • EC1: 'Proceeding with manuscript revisions', Andrew Wickert, 09 Dec 2021

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Francesco Avanzi on behalf of the Authors (14 Jan 2022)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (19 Feb 2022) by Andrew Wickert
RR by Anonymous Referee #3 (16 May 2022)
ED: Publish subject to technical corrections (02 Jun 2022) by Andrew Wickert
AR by Francesco Avanzi on behalf of the Authors (07 Jun 2022)  Author's response    Manuscript
Short summary
Knowing in real time how much snow and glacier ice has accumulated across the landscape has significant implications for water-resource management and flood control. This paper presents a computer model – S3M – allowing scientists and decision makers to predict snow and ice accumulation during winter and the subsequent melt during spring and summer. S3M has been employed for real-world flood forecasting since the early 2000s but is here being made open source for the first time.