Articles | Volume 12, issue 3
https://doi.org/10.5194/cp-12-749-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/cp-12-749-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
23 Mar 2016
Research article |
| 23 Mar 2016
Arctic sea ice simulation in the PlioMIP ensemble
Fergus W. Howell
CORRESPONDING AUTHOR
School of Earth and Environment, University of Leeds, Leeds, UK
Alan M. Haywood
School of Earth and Environment, University of Leeds, Leeds, UK
Bette L. Otto-Bliesner
National Center for Atmospheric Research, Boulder, CO, USA
Fran Bragg
School of Geographical Sciences, University of Bristol, Bristol, UK
Wing-Le Chan
Atmosphere and Ocean Research Institute, University of Tokyo, Kashiwa, Japan
Mark A. Chandler
Columbia University – NASA/GISS-E2-R, New York, NY, USA
Camille Contoux
Aix-Marseille Université, CNRS, IRD, CEREGE UM34, Aix en Provence, France
Youichi Kamae
Graduate School of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Japan
Ayako Abe-Ouchi
Atmosphere and Ocean Research Institute, University of Tokyo, Kashiwa, Japan
Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan
Nan A. Rosenbloom
National Center for Atmospheric Research, Boulder, CO, USA
Christian Stepanek
Alfred Wegener Institute – Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany
Zhongshi Zhang
Bjerknes Centre for Climate Research, Bergen, Norway
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Latest update: 21 Dec 2025
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.
Simulations of pre-industrial and mid-Pliocene Arctic sea ice by eight GCMs are analysed....
