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 Australian Community Climate and Earth-System Simulator (ACCESS) is a coupled climate and earth system simulator being developed as a joint initiative of the Bureau of Meteorology and CSIRO in cooperation with the university community in Australia. The main aim of ACCESS is to develop a national approach to climate and weather prediction model development. Planning for ACCESS development commenced in 2005 and significant progress has been made subsequently. ACCESS-based numerical weather prediction (NWP) systems were implemented operationally by the Bureau in September 2009 and were marked by significantly increased forecast skill of close to one day for three-day forecasts over the previously operational systems. The fully-coupled ACCESS earth system model has been assembled and tested, and core runs have been completed and submitted for the Intergovernmental Panel for Climate Change (IPCC) Fifth Assessment Report. Significant progress has been made with ACCESS infrastructure including successful porting to both Solar and Vayu (National Computational Infrastructure (NCI)) machines and development of infrastructure to allow usage by university researchers. This paper provides a description of the NWP component of ACCESS and presents results from detailed verification of the system.

Snow feedback is expected to amplify global warming caused by increasing concentrations of atmospheric greenhouse gases. The conventional explanation is that a warmer Earth will have less snow cover, resulting in a darker planet that absorbs more solar radiation. An intercomparison of 17 general circulation models, for which perturbations of sea surface temperature were used as a surrogate climate change, suggests that this explanation is overly simplistic. The results instead indicate that additional amplification or moderation may be caused both by cloud interactions and longwave radiation. One measure of this net effect of snow feedback was found to differ markedly among the 17 climate models, ranging from weak negative feedback in some models to strong positive feedback in others.

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This study uses shipborne cloud radar and surface radiation measurements collected over the Southern Ocean to characterize the cloud frequency, cloud fraction, and cloud radiative effects on the ocean surface. These cloud and radiative properties are also used to evaluate a regional forecast model. Low‐level clouds, either alone or cooccurring with cloud layers aloft, are present ~ 77% of the time in this data set. These clouds either had a very low or a very high cloud fraction at 12 km horizontal resolution, with about half of the clouds characterized by a cloud fraction higher than 80%. Overall, shortwave surface cooling effect dominates longwave heating, with an estimate net radiative cooling of −22 W m−2, resulting from a −71 W m−2 shortwave cooling and a +49 W m−2 longwave heating. A strong relationship between daily surface cloud radiative effect and daily low‐level cloud fraction is found, which, if confirmed with a larger data set, could be exploited in satellite retrievals or model parameterizations for the Southern Ocean. The regional model underestimates the frequency of low‐level clouds but largely overestimates the frequency of multilayer situations. The associated radiative errors are large and complex, including reduced surface radiative cooling due to low‐level clouds compensated by enhanced surface cooling in multilayer situations.