Articles | Volume 12, issue 3
Clim. Past, 12, 749–767, 2016
https://doi.org/10.5194/cp-12-749-2016
Clim. Past, 12, 749–767, 2016
https://doi.org/10.5194/cp-12-749-2016

Research article 23 Mar 2016

Research article | 23 Mar 2016

Arctic sea ice simulation in the PlioMIP ensemble

Fergus W. Howell et al.

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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
ED: Reconsider after major revisions (06 Jul 2015) by Uwe Mikolajewicz
AR by Fergus Howell on behalf of the Authors (17 Aug 2015)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (19 Aug 2015) by Uwe Mikolajewicz
RR by Anonymous Referee #2 (14 Sep 2015)
RR by Anonymous Referee #1 (17 Sep 2015)
ED: Reconsider after major revisions (23 Sep 2015) by Uwe Mikolajewicz
AR by Fergus Howell on behalf of the Authors (09 Dec 2015)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (22 Dec 2015) by Uwe Mikolajewicz
RR by Anonymous Referee #2 (18 Jan 2016)
RR by Anonymous Referee #1 (29 Jan 2016)
ED: Publish subject to minor revisions (review by Editor) (11 Feb 2016) by Uwe Mikolajewicz
AR by Fergus Howell on behalf of the Authors (26 Feb 2016)  Author's response    Manuscript
ED: Publish subject to minor revisions (review by Editor) (08 Mar 2016) by Uwe Mikolajewicz
AR by Fergus Howell on behalf of the Authors (09 Mar 2016)  Author's response    Manuscript
ED: Publish as is (10 Mar 2016) by Uwe Mikolajewicz
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Short summary
Simulations of pre-industrial and mid-Pliocene Arctic sea ice by eight GCMs are analysed. Ensemble variability in sea ice extent is greater in the mid-Pliocene summer, when half of the models simulate sea-ice-free conditions. Weaker correlations are seen between sea ice extent and temperatures in the pre-industrial era compared to the mid-Pliocene. The need for more comprehensive sea ice proxy data is highlighted, in order to better compare model performances.