| Abstract |
- Climate sensitivity is generally studied using two types of models. Atmosphere-ocean general circulation models (AOGCMs) include interactive ocean dynamics and detailed heat uptake. Atmospheric GCMs (AGCMs) with slab ocean models (SOMs) cannot fully simulate the ocean's response to and influence on climate. However, AGCMs are computationally cheaper and thus are often used to quantify and understand climate feedbacks and sensitivity. Here, physical climate feedbacks are compared between AOGCMs and SOM-AGCMs from the Coupled Model Intercomparison Project phase 3 (CMIP3) using the radiative kernel technique. Both the global-average (positive) water vapor and (negative) lapse-rate feedbacks are consistently stronger in AOGCMs. Water vapor feedback differences result from an essentially constant relative humidity and peak in the tropics, where temperature changes are larger for AOGCMs. Differences in lapse-rate feedbacks extend to midlatitudes and correspond to a larger ratio of tropical- to global-average temperature changes. Global-average surface albedo feedbacks are similar between models types because of a near cancellation of Arctic and Antarctic differences. In AOGCMs, the northern high latitudes warm faster than the southern latitudes, resulting in interhemispheric differences in albedo, water vapor, and lapse-rate feedbacks lacking in the SOM-AGCMs. Meridional heat transport changes also depend on the model type, although there is a large intermodel spread. However, there are no consistent global or zonal differences in cloud feedbacks. Effects of the forcing scenario [Special Report on Emissions Scenarios A1B (SRESa1b) or the 1% CO2 increase per year to doubling (1%to2x) experiments] on feedbacks are model dependent and generally of lesser importance than the model type. Care should be taken when using SOM-AGCMs to understand AOGCM feedback behavior.
- Keywords: CO2, General circulation models, Transient responses, State, Carbon dioxide, Mean response, Equilibrium, Sensitivity, Adjustment, Radiative kernel technique
- Keywords: CO2, General circulation models, Transient responses, State, Carbon dioxide, Mean response, Equilibrium, Sensitivity, Adjustment, Radiative kernel technique
- Keywords: CO2, General circulation models, Transient responses, State, Carbon dioxide, Mean response, Equilibrium, Sensitivity, Adjustment, Radiative kernel technique
- Keywords: CO2, General circulation models, Transient responses, State, Carbon dioxide, Mean response, Equilibrium, Sensitivity, Adjustment, Radiative kernel technique
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