Articles | Volume 19, issue 7
https://doi.org/10.5194/gmd-19-2903-2026
https://doi.org/10.5194/gmd-19-2903-2026
Model description paper
 | 
16 Apr 2026
Model description paper |  | 16 Apr 2026

MinSIA v1: a lightweight and efficient implementation of the shallow ice approximation

Stefan Hergarten

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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 egusphere-2025-2242', Daniel Moreno-Parada, 31 Jul 2025
    • AC1: 'Reply on RC1', Stefan Hergarten, 26 Aug 2025
  • RC2: 'Comment on egusphere-2025-2242', Thomas Zwinger, 29 Aug 2025
    • AC2: 'Reply on RC2', Stefan Hergarten, 03 Sep 2025
      • RC3: 'Reply on AC2', Thomas Zwinger, 05 Sep 2025
        • AC3: 'Reply on RC3', Stefan Hergarten, 10 Sep 2025
  • EC1: 'Comment on egusphere-2025-2242', Ludovic Räss, 08 Sep 2025

Peer review completion

AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload
AR by Stefan Hergarten on behalf of the Authors (07 Oct 2025)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (09 Oct 2025) by Ludovic Räss
RR by Daniel Moreno-Parada (11 Nov 2025)
ED: Reconsider after major revisions (17 Nov 2025) by Ludovic Räss
AR by Stefan Hergarten on behalf of the Authors (26 Dec 2025)  Author's response   Author's tracked changes   Manuscript 
ED: Publish subject to minor revisions (review by editor) (19 Jan 2026) by Ludovic Räss
AR by Stefan Hergarten on behalf of the Authors (19 Feb 2026)  Author's response   Author's tracked changes   Manuscript 
ED: Publish subject to minor revisions (review by editor) (17 Mar 2026) by Ludovic Räss
AR by Stefan Hergarten on behalf of the Authors (18 Mar 2026)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (23 Mar 2026) by Ludovic Räss
AR by Stefan Hergarten on behalf of the Authors (26 Mar 2026)  Manuscript 
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Short summary
Numerical glacier and ice-sheet models have been widely used in the context of climate change and landform evolution. While simulations of ice flow were numerically expensive for a long time, their performance has recently been boosted to an unprecedented level by machine learning techniques. This paper aims at keeping classical numerics competitive by introducing a novel numerical scheme, which allows for simulations at spatial resolutions of 25 m or even finer on standard desktop PCs.
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