Flato, G.M. and Participating CMIP Modelling Groups, 2003:
Sea ice and its response to CO2 forcing as simulated by several global climate models
Submitted to Climate Dynamics

Abstract

The simulation of sea-ice in global climate models participating in the Coupled Model Intercomparison Project (CMIP1 and CMIP2) is analyzed. CMIP1 simulations are of the unpertubed "control" climate whereas in CMIP2, all models have been forced with the same 1% yr-1 increase in CO2 concentration, starting from a near equilibrium initial condition. These simulations are not intended as forecasts of climate change, but rather provide a means of evaluating the response of current climate models to the same forcing. The difference in modeled response therefore indicates the range (or uncertainty) in model sensitivity to greenhouse gas and other climatic perturbations.

The results illustrate a wide range in the ability of climate models to reproduce contemporary sea-ice extent and thickness; however, the errors are not obviously related to the manner in which sea-ice processes are represented in the models (e.g. the inclusion or neglect of sea-ice motion). The implication is that errors in the ocean and atmosphere components of the climate model are at least as important. There is also a large range in the simulated sea-ice response to CO2 change, again with no obvious stratification in terms of model attributes. In contrast to results obtained earlier with a particular model, the CMIP ensemble yields rather mixed results in terms of the dependence of high-latitude warming on sea-ice initial conditions. There is an indication that, in the Arctic, models that produce thick ice in their control integration exhibit less warming than those with thin ice. The opposite tendency appears in the Antarctic (albeit with low statistical significance). There is a tendency for models with more extensive ice coverage in the Southern Hemisphere to exhibit greater Antarctic warming. Results for the Arctic indicate the opposite tendency (though with low statistical significance).