Articles | Volume 12, issue 10
https://doi.org/10.5194/tc-12-3187-2018
https://doi.org/10.5194/tc-12-3187-2018
Research article
 | 
05 Oct 2018
Research article |  | 05 Oct 2018

A statistical fracture model for Antarctic ice shelves and glaciers

Veronika Emetc, Paul Tregoning, Mathieu Morlighem, Chris Borstad, and Malcolm Sambridge

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Veronika Emetc on behalf of the Authors (25 Jun 2018)  Author's response   Manuscript 
ED: Referee Nomination & Report Request started (26 Jun 2018) by Olivier Gagliardini
RR by Jeremy Bassis (13 Jul 2018)
ED: Reconsider after major revisions (20 Jul 2018) by Olivier Gagliardini
AR by Veronika Emetc on behalf of the Authors (04 Aug 2018)  Author's response   Manuscript 
ED: Reconsider after major revisions (25 Aug 2018) by Olivier Gagliardini
AR by Veronika Emetc on behalf of the Authors (30 Aug 2018)  Author's response   Manuscript 
ED: Publish subject to minor revisions (review by editor) (04 Sep 2018) by Olivier Gagliardini
AR by Veronika Emetc on behalf of the Authors (07 Sep 2018)  Manuscript 
ED: Publish subject to minor revisions (review by editor) (07 Sep 2018) by Olivier Gagliardini
AR by Veronika Emetc on behalf of the Authors (11 Sep 2018)  Author's response   Manuscript 
ED: Publish subject to technical corrections (18 Sep 2018) by Olivier Gagliardini
AR by Veronika Emetc on behalf of the Authors (19 Sep 2018)  Author's response   Manuscript 
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Short summary
The paper includes a model that can be used to predict zones of fracture formation in both floating and grounded ice in Antarctica. We used observations and a statistics-based model to predict fractures in most ice shelves in Antarctica as an alternative to the damage-based approach. We can predict the location of observed fractures with an average success rate of 84% for grounded ice and 61% for floating ice and mean overestimation error of 26% and 20%, respectively.