A BAYESIAN STATISTICAL-ANALYSIS OF THE ENHANCED GREENHOUSE-EFFECT

This paper demonstrates that there is a robust statistical relationshi p between the records of the global mean surface air temperature and t he atmospheric concentration of carbon dioxide over the period 1870-19 91. As such, the enhanced greenhouse effect is a plausible explanation for the observed global warming. Long term natural variability is ano ther prime candidate for explaining the temperature rise of the last c entury. Analysis of natural variability from paleo-reconstructions, ho wever, shows that human activity is so much more likely an explanation that the earlier conclusion is not refuted. But, even if one believes in large natural climatic variability, the odds are invariably in fav our of the enhanced greenhouse effect. The above conclusions hold for a range of statistical models, including one that is capable of descri bing the stabilization of the global mean temperature from the 1940s t o the 1970s onwards. This model is also shown to be otherwise statisti cally adequate. The estimated climate sensitivity is about 3.8 degrees C with a standard deviation of 0.9(degrees) C, but depends slightly o n which model is preferred and how much natural variability is allowed . These estimates neglect, however, the fact that carbon dioxide is bu t one of a number of greenhouse gases and that sulphate aerosols may w ell have dampened warming. Acknowledging the fact that carbon dioxide is used as a proxy for all human induced changes in radiative forcing brings a lot of additional uncertainty. Prior knowledge on both climat e sensitivity and radiative forcing is needed to say anything about th e respective sizes. A fully Bayesian approach is used to combine exper t knowledge with information from the observations. Prior knowledge on the climate sensitivity plays a dominant role. The data largely exclu de climate sensitivity to be small, but cannot exclude climate sensiti vity to be large, because of the possibility of strong negative sulpha te forcing. The posterior of climate sensitivity has a strong positive skewness. Moreover, its mode (again 3.8 degrees C; standard deviation 2.4 degrees C) is higher than the best guess of the TPCC.