The formulation and simulation characteristics of two new global coupled climate models developed at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) are described. The models were designed to simulate atmospheric and oceanic climate and variability from the diurnal time scale through multicentury climate change, given our computational constraints. In particular, an important goal was to use the same model for both experimental seasonal to interannual forecasting and the study of multicentury global climate change, and this goal has been achieved.Two versions of the coupled model are described, called CM2.0 and CM2.1. The versions differ primarily in the dynamical core used in the atmospheric component, along with the cloud tuning and some details of the land and ocean components. For both coupled models, the resolution of the land and atmospheric components is 2°latitude ϫ 2.5°longitude; the atmospheric model has 24 vertical levels. The ocean resolution is 1°in latitude and longitude, with meridional resolution equatorward of 30°becoming progressively finer, such that the meridional resolution is 1/3°at the equator. There are 50 vertical levels in the ocean, with 22 evenly spaced levels within the top 220 m. The ocean component has poles over North America and Eurasia to avoid polar filtering. Neither coupled model employs flux adjustments.The control simulations have stable, realistic climates when integrated over multiple centuries. Both models have simulations of ENSO that are substantially improved relative to previous GFDL coupled models. The CM2.0 model has been further evaluated as an ENSO forecast model and has good skill (CM2.1 has not been evaluated as an ENSO forecast model). Generally reduced temperature and salinity biases exist in CM2.1 relative to CM2.0. These reductions are associated with 1) improved simulations of surface wind stress in CM2.1 and associated changes in oceanic gyre circulations; 2) changes in cloud tuning and the land model, both of which act to increase the net surface shortwave radiation in CM2.1, thereby reducing an overall cold bias present in CM2.0; and 3) a reduction of ocean lateral viscosity in the extratropics in CM2.1, which reduces sea ice biases in the North Atlantic. Both models have been used to conduct a suite of climate change simulations for the 2007 Intergovernmental Panel on Climate Change (IPCC) assessment report and are able to simulate the main features of the observed warming of the twentieth century. The climate sensitivities of the CM2.0 and CM2.1 models are 2.9 and 3.4 K, respectively. These sensitivities are defined by coupling the atmospheric components of CM2.0 and CM2.1 to a slab ocean model and allowing the model to come into equilibrium with a doubling of atmospheric CO 2 . The output from a suite of integrations conducted with these models is freely available online (see http://nomads.gfdl.noaa.gov/).

The current generation of coupled climate models run at the Geophysical Fluid Dynamics Laboratory (GFDL) as part of the Climate Change Science Program contains ocean components that differ in almost every respect from those contained in previous generations of GFDL climate models. This paper summarizes the new physical features of the models and examines the simulations that they produce. Of the two new coupled climate model versions 2.1 (CM2.1) and 2.0 (CM2.0), the CM2.1 model represents a major improvement over CM2.0 in most of the major oceanic features examined, with strikingly lower drifts in hydrographic fields such as temperature and salinity, more realistic ventilation of the deep ocean, and currents that are closer to their observed values. Regional analysis of the differences between the models highlights the importance of wind stress in determining the circulation, particularly in the Southern Ocean. At present, major errors in both models are associated with Northern Hemisphere Mode Waters and outflows from overflows, particularly the Mediterranean Sea and Red Sea.

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Abstract. The relationship between cloudiness and sea ice thickness over the Arctic Ocean is examined using an idealized equilibrium energy budget model and a singlecolumn model (SCM) forced by incoming solar radiation, atmospheric poleward energy flux, oceanic heat flux, and sea ice divergence. The sensitivity of ice thickness to cloud perturbations in the SCM is qualitatively different from previous modeling studies, which did not allow the atmospheric temperature profile to respond to perturbations in cloudiness. It is shown that this restriction implicitly changes the poleward energy flux in model experiments and obscures the intrinsic effect of clouds on the arctic climate. In the present model, equilibrium ice thickness has a strong negative correlation with cloud radiative forcing at the top of the atmosphere and no correlation with cloud radiative forcing at the surface. The results demonstrate how local processes, such as the surface albedo feedback, affect the sensitivity of ice thickness to cloud perturbations and reduce its predictability. Exploratory model experiments suggest that interactions between the Arctic and the lower latitudes (via the poleward energy flux) could strongly influence the dependence of ice thickness on cloudiness. The impact of these interactions in the model was predicted qualitatively by considering how the radiative effect of clouds is partitioned between the atmosphere and the surface. The results demonstrate the importance of using cloud radiative forcing at both the surface and the top of the atmosphere when estimating the climatic effect of perturbation in cloudiness.

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