A comparison of present and doubled CO2 climates and feedbacks simulated by three general circulation models

The present and doubled CO2 equilibrium climates simulated by slab ocean versions of the atmospheric general circulation models from the Commonwealth Scientific and Industrial Research Organisation (CSIRO, Mark 1 and Mark 2) and from the Bureau of Meteorology Research Centre (BMRC) are examined, with the aim of explaining the large variation in mean warming (4.8°C, 4.3°C, and 2.1°C). The present climates are compared firstly with observations. A graphical display of nondimensional measures of local and mean errors is used. For 15 quantities the models produce broadly similar skill, which indicates that such an evaluation is of limited use as a validation of these models for climate change prediction. Comparison of the two climates indicates that for temperature, snow/ice cover, and water column (but not necessarily other fields) the typical magnitudes of local changes are in rough proportion to the mean warming. For tropical precipitation, however, the BMRC model shows a similar sensitivity to CO2 doubling as do the CSIRO models. A standard diagnostic feedback analysis shows that the Mark 1 model has stronger albedo, water vapor, and cloud feedbacks than the BMRC model. A novel regional net feedback analysis is then applied to all three models. Feedbacks for the snow/ice region and clear-sky and cloud forcing components of the snow-free region indicate similar intermodel differences to those from the diagnostic approach. The feedbacks are examined in relation to the simulated climates and model parameterizations. As the application of the regional method requires only standard climatological fields, it is proposed as a convenient analysis tool in further model comparisons.

[1]  J. Janowiak,et al.  The Global Precipitation Climatology Project (GPCP) combined precipitation dataset , 1997 .

[2]  Donald R. Johnson “General Coldness of Climate Models” and the Second Law: Implications for Modeling the Earth System , 1997 .

[3]  John F. B. Mitchell,et al.  Modeling climate change: An assessment of sea ice and surface albedo feedbacks , 1989 .

[4]  W L Gates,et al.  Uncertainties in Carbon Dioxide Radiative Forcing in Atmospheric General Circulation Models , 1993, Science.

[5]  K. Arpe,et al.  Some results from an intercomparison of the climates simulated by 14 atmospheric general circulation models , 1992 .

[6]  Stephen B. Fels,et al.  The Simplified Exchange Approximation: A New Method for Radiative Transfer Calculations , 1975 .

[7]  Gerald L. Potter,et al.  A methodology for understanding and intercomparing atmospheric climate feedback processes in general circulation models , 1988 .

[8]  I. Watterson,et al.  Non-Dimensional Measures of Climate Model Performance , 1996 .

[9]  G. Louis Smith,et al.  The Earth Radiation Budget Experiment: Science and implementation , 1986 .

[10]  M. Tiedtke A Comprehensive Mass Flux Scheme for Cumulus Parameterization in Large-Scale Models , 1989 .

[11]  H. Treut,et al.  Sensitivity of the LMD General Circulation Model to Greenhouse Forcing Associated with Two Different Cloud Water Parameterizations , 1994 .

[12]  I. Watterson,et al.  Energy and water transport in climates simulated by a general circulation model that includes dynamic sea ice , 1997 .

[13]  M. England,et al.  Global comparison of the regional rainfall results of enhanced greenhouse coupled and mixed layer ocean experiments: Implications for climate change scenario development , 1996 .

[14]  Leon D. Rotstayn,et al.  The CSIRO 9-level atmospheric general circulation model , 1993 .

[15]  Zhanqing Li,et al.  Global climatologies of solar radiation budgets at the surface and in the atmosphere from 5 years of ERBE data , 1993 .

[16]  Donald J. Cavalieri,et al.  NASA Sea Ice Validation Program for the Defense Meteorological Satellite Program Special Sensor Microwave Imager , 1991 .

[17]  N. Grody Classification of snow cover and precipitation using the special sensor microwave imager , 1991 .

[18]  James J. Hack,et al.  Cloud feedback in atmospheric general circulation models: An update , 1996 .

[19]  I. Watterson An analysis of the global water cycle of present and doubled CO2 climates simulated by the CSIRO general circulation model , 1998 .

[20]  G. Stephens,et al.  A new global water vapor dataset , 1996 .

[21]  J. Hack,et al.  Diagnostic study of climate feedback processes in atmospheric general circulation models , 1994 .

[22]  Keith P. Shine,et al.  Sensitivity of the Earth's climate to height-dependent changes in the water vapour mixing ratio , 1991, Nature.

[23]  Jf. Geleyn,et al.  Use of a Modified Richardson Number for Parameterizing the Effect of Shallow Convection , 1986 .

[24]  I. Watterson,et al.  Influences on surface energy fluxes in simulated present and doubled CO2 climates , 1996 .

[25]  S. Manabe,et al.  Cloud Feedback Processes in a General Circulation Model , 1988 .

[26]  J. Hansen,et al.  GCM simulations of volcanic aerosol forcing. I - Climate changes induced by steady-state perturbations , 1993 .

[27]  Yale Mintz,et al.  Climatology of the terrestrial seasonal water cycle , 1985 .

[28]  V. Ramanathan,et al.  Increased atmospheric CO2: Zonal and seasonal estimates of the effect on the radiation energy balance and surface temperature , 1979 .

[29]  M. Tiedtke The effect of penetrative cumulus convection on the large-scale flow in a general circulation model , 1984 .

[30]  B. McAvaney,et al.  Sensitivity of the climate response of an atmospheric general circulation model to changes in convective parameterization and horizontal resolution , 1995 .

[31]  Paul W. Mielke,et al.  34 Meteorological applications of permutation techniques based on distance functions , 1984, Nonparametric Methods.

[32]  D. Legates,et al.  Mean seasonal and spatial variability in global surface air temperature , 1990 .

[33]  B. McAvaney,et al.  A study of general circulation model climate feedbacks determined from perturbed sea surface temperature experiments , 1997 .