Preprints
https://doi.org/10.5194/egusphere-2023-2362
https://doi.org/10.5194/egusphere-2023-2362
07 Nov 2023
 | 07 Nov 2023

Weak relationship between remotely detected crevasses and inferred ice rheological parameters on Antarctic ice shelves

Cristina Gerli, Sebastian Rosier, Hilmar Gudmundsson, and Sainan Sun

Abstract. Over the past decade, a wealth of research has been devoted to the detection of crevasses in glaciers and ice sheets via remote sensing and machine learning techniques. It is often argued that remotely sensed damage maps can function as early-warning signals for shifts in ice shelf conditions from intact to damaged states and can serve as an important tool for ice sheet modellers to improve future sea-level rise predictions. Here, we provide evidence for Filchner-Ronne and Pine Island ice shelves that remotely sensed damage maps are only weakly related to the ice rate factor field A derived by an ice-flow model when inverting for surface velocities. This technique is a common procedure in ice flow models, as it guarantees that any inferred changes in A relate to changes in ice flow measured through observations. The weak relationship found is improved when investigating heavily damaged shear margins, as observed on Pine Island Ice Shelf; yet, even in this setting, this association remains modest. Our findings suggest that many features identified as damage through remote sensing methods are not of direct relevance to present-day ice-shelf flow. While damage can clearly play an important role in ice-shelf processes and thus be relevant for ice-sheet behaviour and sea-level rise projections, our results imply that mapping ice damage directly from satellite observations may not directly help improve the representation of these processes in ice-flow models.

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Cristina Gerli, Sebastian Rosier, Hilmar Gudmundsson, and Sainan Sun

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-2362', Anonymous Referee #1, 31 Dec 2023
    • RC2: 'Comment on egusphere-2023-2362', Anonymous Referee #2, 18 Jan 2024
      • AC3: 'Reply on RC2', Cristina Gerli, 07 Mar 2024
    • AC2: 'Reply on RC1', Cristina Gerli, 07 Mar 2024
  • RC3: 'Comment on egusphere-2023-2362', Adrien Gilbert, 09 Feb 2024
    • AC1: 'Reply on RC3', Cristina Gerli, 07 Mar 2024

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-2362', Anonymous Referee #1, 31 Dec 2023
    • RC2: 'Comment on egusphere-2023-2362', Anonymous Referee #2, 18 Jan 2024
      • AC3: 'Reply on RC2', Cristina Gerli, 07 Mar 2024
    • AC2: 'Reply on RC1', Cristina Gerli, 07 Mar 2024
  • RC3: 'Comment on egusphere-2023-2362', Adrien Gilbert, 09 Feb 2024
    • AC1: 'Reply on RC3', Cristina Gerli, 07 Mar 2024
Cristina Gerli, Sebastian Rosier, Hilmar Gudmundsson, and Sainan Sun
Cristina Gerli, Sebastian Rosier, Hilmar Gudmundsson, and Sainan Sun

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Short summary
Recent efforts have focused on using AI and satellite imagery to track crevasses for assessing ice shelf damage and informing ice-flow models. Our study reveals a weak connection between these observed products and damage maps inferred from ice flow models. While there's some improvement in crevasse-dense regions, this association remains limited. Directly mapping ice damage from satellite observations may not significantly improve the representation of these processes within ice-flow models.