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...

The Atmospheric Model Intercomparison Project (AMIP) is an international effort to determine the systematic climate errors of atmospheric models under realistic conditions, and calls for the simulation of the climate of the decade 1979-1988 using the observed monthly averaged distributions of sea surface temperature and sea ice as boundary conditions. Organized by the Working Group on Numerical Experimentation as a contribution to the World Climate Research Programme, AMIP involves the international atmospheric modeling community in a major test and intercomparison of model performance; in addition to an agreed-to set of monthly averaged output variables, each of the participating models will generate a daily history of state. These data will be stored and made available in standard format by the Program for Climate Model Diagnosis and Intercomparison at the Lawrence Livermore National Laboratory. Following completion of the computational phase of AMIP in 1993, emphasis will shift to a series of diagnostic subprojects, now being planned, for the detailed examination of model performance and the simulation of specific physical processes and phenomena. AMIP offers an unprecedented opportunity for the comprehensive evaluation and validation of current atmospheric models, and is expected to provide valuable information for model improvement.

The Atmospheric Model Intercomparison Project (AMIP), initiated in 1989 under the auspices of the World Climate Research Programme, undertook the systematic validation, diagnosis, and intercomparison of the performance of atmospheric general circulation models. For this purpose all models were required to simulate the evolution of the climate during the decade 1979-88, subject to the observed monthly average temperature and sea ice and a common prescribed atmospheric C02 concentration and solar constant. By 1995, 31 modeling groups, representing virtually the entire international atmospheric modeling community, had contributed the required standard output of the monthly means of selected statistics. These data have been analyzed by the participating modeling groups, by the Program for Climate Model Diagnosis and Intercomparison, and by the more than two dozen AMIP diagnostic subprojects that have been established to examine specific aspects of the models' performance. Here the analysis and validation of the AMIP results as a whole are summarized in order to document the overall performance of atmospheric general circulation-climate models as of the early 1990s. The infrastructure and plans for continuation of the AMIP project are also reported on.Although there are apparent model outliers in each simulated variable examined, validation of the AMIP models' ensemble mean shows that the average large-scale seasonal distributions of pressure, temperature, and circulation are reasonably close to what are believed to be the best observational estimates available. The large-scale structure of the ensemble mean precipitation and ocean surface heat flux also resemble the observed estimates but show particularly large intermodel differences in low latitudes. The total cloudiness, on the other hand, is rather poorly simulated, especially in the Southern Hemisphere. The models' simulation of the seasonal cycle (as represented by the amplitude and phase of the first annual harmonic of sea level pressure) closely resembles the observed variation in almost all regions. The ensemble's simulation of the interannual variability of sea level pressure in the tropical Pacific is reasonably close to that observed (except for its underestimate of the amplitude of major El Ninos), while the interannual variability is less well simulated in midlatitudes. When analyzed in terms of the variability of the evolution of their combined spacetime patterns in comparison to observations, the AMIP models are seen to exhibit a wide range of accuracy, with no single model performing best in all respects considered.Analysis of the subset of the original AMIP models for which revised versions have subsequently been used to revisit the experiment shows a substantial reduction of the models' systematic errors in simulating cloudiness but only a slight reduction of the mean seasonal errors of most other variables. In order to understand better the nature of these errors and to accelerate the rate of model improvement, an expanded and continuing project (...

Six years ago, we compared the climate sensitivity of 19 atmospheric general circulation models and found a roughly threefold variation among the models; most of this variation was attributed to differences in the models' depictions of cloud feedback. In an update of this comparison, current models showed considerably smaller differences in net cloud feedback, with most producing modest values. There are, however, substantial differences in the feedback components, indicating that the models still have physical disagreements

There has been a long history of unexplained anomalous absorption of solar radiation by clouds. Collocated satellite and surface measurements of solar radiation at five geographically diverse locations showed significant solar absorption by clouds, resulting in about 25 watts per square meter more global-mean absorption by the cloudy atmosphere than predicted by theoretical models. It has often been suggested that tropospheric aerosols could increase cloud absorption. But these aerosols are temporally and spatially heterogeneous, whereas the observed cloud absorption is remarkably invariant with respect to season and location. Although its physical cause is unknown, enhanced cloud absorption substantially alters our understanding of the atmosphere's energy budget.