Articles | Volume 16, issue 11
https://doi.org/10.5194/se-16-1401-2025
https://doi.org/10.5194/se-16-1401-2025
Research article
 | 
13 Nov 2025
Research article |  | 13 Nov 2025

Application of Self-Organizing Maps to characterize subglacial bedrock properties based on gravity, magnetic and radar data – an example for the Wilkes and Aurora Subglacial Basin region, East Antarctica

Jonas Liebsch, Jörg Ebbing, and Kenichi Matsuoka

Download

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Referee Comment on egusphere-2025-1905', Tobias Stål, 18 Jun 2025
  • RC2: 'Comment on egusphere-2025-1905', Fausto Ferraccioli, 19 Jul 2025

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Jörg Ebbing on behalf of the Authors (17 Sep 2025)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (18 Sep 2025) by Nicolas Gillet
RR by Tobias Stål (25 Sep 2025)
ED: Publish subject to minor revisions (review by editor) (25 Sep 2025) by Nicolas Gillet
AR by Jörg Ebbing on behalf of the Authors (02 Oct 2025)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (06 Oct 2025) by Nicolas Gillet
ED: Publish as is (09 Oct 2025) by Susanne Buiter (Executive editor)
AR by Jörg Ebbing on behalf of the Authors (14 Oct 2025)
Download
Short summary
The evolution of the Antarctic ice sheets depends, in addition to factors representing the warming climate, on the earth structure beneath the ice. What’s beneath the ice is largely inaccessible for direct sampling, but can be interpreted with the use of airborne measurements. We apply an unsupervised machine learning method to such data in East Antarctica to test whether this can ease interpretation and hence our understanding of what rocks types are beneath the ice.
Share