IPCC climate models do not capture Arctic sea ice drift acceleration: Consequences in terms of projected sea ice thinning and decline
Article first published online: 29 SEP 2011
Copyright 2011 by the American Geophysical Union.
Journal of Geophysical Research: Oceans (1978–2012)
Volume 116, Issue C8, August 2011
How to Cite
2011), IPCC climate models do not capture Arctic sea ice drift acceleration: Consequences in terms of projected sea ice thinning and decline, J. Geophys. Res., 116, C00D07, doi:10.1029/2011JC007110., , , and (
- Issue published online: 29 SEP 2011
- Article first published online: 29 SEP 2011
- Manuscript Accepted: 30 JUN 2011
- Manuscript Revised: 22 JUN 2011
- Manuscript Received: 7 MAR 2011
- IPCC climate models;
 IPCC climate models underestimate the decrease of the Arctic sea ice extent. The recent Arctic sea ice decline is also characterized by a rapid thinning and by an increase of sea ice kinematics (velocities and deformation rates), with both processes being coupled through positive feedbacks. In this study we show that IPCC climate models underestimate the observed thinning trend by a factor of almost 4 on average and fail to capture the associated accelerated motion. The coupling between the ice state (thickness and concentration) and ice velocity is unexpectedly weak in most models. In particular, sea ice drifts faster during the months when it is thick and packed than when it is thin, contrary to what is observed; also models with larger long-term thinning trends do not show higher drift acceleration. This weak coupling behavior (1) suggests that the positive feedbacks mentioned above are underestimated and (2) can partly explain the models' underestimation of the recent sea ice area, thickness, and velocity trends. Due partly to this weak coupling, ice export does not play an important role in the simulated negative balance of Arctic sea ice mass between 1950 and 2050. If we assume a positive trend on ice speeds at straits equivalent to the one observed since 1979 within the Arctic basin, first-order estimations give shrinking and thinning trends that become significantly closer to the observations.