Articles | Volume 18, issue 7
https://doi.org/10.5194/tc-18-3033-2024
https://doi.org/10.5194/tc-18-3033-2024
Research article
 | 
03 Jul 2024
Research article |  | 03 Jul 2024

Suitability of the CICE sea ice model for seasonal prediction and positive impact of CryoSat-2 ice thickness initialization

Shan Sun and Amy Solomon

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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 tc-2023-116', Anonymous Referee #1, 06 Oct 2023
  • RC2: 'Comment on tc-2023-116', Anonymous Referee #2, 30 Nov 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
ED: Reconsider after major revisions (further review by editor and referees) (23 Jan 2024) by David Schroeder
AR by Shan Sun on behalf of the Authors (05 Mar 2024)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (18 Mar 2024) by David Schroeder
RR by Anonymous Referee #2 (02 Apr 2024)
ED: Publish subject to minor revisions (review by editor) (17 Apr 2024) by David Schroeder
AR by Shan Sun on behalf of the Authors (28 Apr 2024)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (29 Apr 2024) by David Schroeder
AR by Shan Sun on behalf of the Authors (30 Apr 2024)  Author's response   Manuscript 
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Short summary
The study brings to light the suitability of CICE for seasonal prediction being contingent on several factors, such as initial conditions like sea ice coverage and thickness, as well as atmospheric and oceanic conditions including oceanic currents and sea surface temperature. We show there is potential to improve seasonal forecasting by using a more reliable sea ice thickness initialization. Thus, data assimilation of sea ice thickness is highly relevant for advancing seasonal prediction skills.