Intercomparison and interpretation of climate feedback processes in 19 atmospheric general circulation models

Abstract

The need to understand differences among general circulation model projections of CO2-induced climatic change has motivated the present study, which provides an intercomparison and interpretation of climate feedback processes in 19 atmospheric general circulation models. This intercomparison uses sea surface temperature change as a surrogate for climate change. The interpretation of cloud-climate interactions is given special attention. A roughly threefold variation in one measure of global climate sensitivity is found among the 19 models. The important conclusion is that most of this variation is attributable to differences in the models' depiction of cloud feedback, a result that emphasizes the need for improvements in the treatment of clouds in these models if they are ultimately to be used as reliable climate predictors. It is further emphasized that cloud feedback is the consequence of all interacting physical and dynamical processes in a general circulation model. The result of these processes is to produce changes in temperature, moisture distribution, and clouds which are integrated into the radiative response termed cloud feedback. INTRODUCTIONProjected increases in the concentration of atmospheric carbon dioxide and other greenhouse gases are expected to have an important impact on climate. The most comprehensive way to infer future climatic change associated with this perturbation of atmospheric composition is by means of three-dimensional general circulation models (GCMs). Schlesinger and Mitchell [1987] have, however, demonstrated that several existing GCMs simulate climate responses to increasing CO2 that differ considerably. Cess and Potter [1988], following a suggestion by Speltnan and Manabe [1984], indicate that differences in global-mean warming, The global-mean direct radiative forcing G of the surfaceatmosphere system is evaluated by holding all other climate parameters fixed. It is this quantity that induces the ensuing climate change, and physically, it represents a change in the net (solar plus infrared) radiative flux at the top of the atmosphere (TOA). For an increase in the CO2 concentration of the atmosphere, to cite one example, G is the reduction in the emitted TOA infrared flux resulting solely from the CO2 increase, and this reduction results in a heating of the surface-atmosphere system. The response process is the change in climate that is then necessary to restore the TOA radiation balance, such that that is either too warm or too cold, then it will respectively produce a climate sensitivity parameter that is too small or too large, and clearly, the intercomparison simulation had to be designed to eliminate this effect. There was also a practical constraint: the CO2 simulations require large amounts of computer time for equilibration of the rather primitive ocean models that have been used in these numerical experiments.An attractive alternative that eliminated both of the above mentioned difficulties was to adopt +_2øK sea surface temperature ( The perpetual July simulation e...

Simulation of the Global Hydrological Cycle in the CCSM Community Atmosphere Model Version 3 (CAM3): Mean Features

“…The liquid and frozen phases are most common in the form of clouds. Clouds play a dominant role in regulating the energy budget of the planet, and their behavior remains a major source of uncertainty in our ability to project the effects of climate change (e.g., Stephens and Webster 1981;Cess et al 1990;IPCC 2001).…”

Human contribution to climate change remains questionable

“…Their "climate sensitivities" (defined as the temperature increase for a doubling of GHG forcing) vary from as low as 1°C to as high as 5°C; the IPCC reports [1990, 1996a] gives a conventional range of 1.5°C to 4.5°C. An intercomparison of models has established that a major uncertainty relates to how clouds are treated [Cess et al, 1990[Cess et al, , 1996.Since they cannot be spatially resolved, they must be parameterized in some fashion. In many models, clouds add to the warming, but in others, clouds produce a cooling effect.…”

Seasonal variations of upper tropospheric water vapor and high clouds observed from satellites

“…Water vapor plays an important role in regulating the Earth climate system through its greenhouse effect [Manabe and Wetheraid, 1967;Ramanathan, 1981;Cess et al, 1990]. The estimated global warming due to an increase in CO2 depends critically on representations of the water vapor feedback in climate models used for the estimation.…”