Towards the detection and attribution of an anthropogenic effect on climate

It has been hypothesized recently that cooling caused by anthropogenic sulfate aerosols may be obscuring a warming signal associated with changes in greenhouse gas concentrations. Here the authors use results from model experiments in which sulfate and carbon dioxide have been varied individually and in combination in order to determine whether the simulated surface temperature change patterns are increasingly evident in observed records of temperature change. They use centered [R(t)] and uncentered [C(t)] pattern correlation statistics in order to compare observed time-evolving surface temperature change patterns with the model-predicted equilibrium signal patterns. They show that in the case of temperature signals from the ``CO{sub 2}-only`` and ``sulfate-only`` experiments, the C(t) statistic essentially reduces to a measure of observed global-mean temperature changes, and cannot be used to uniquely attribute observed climate changes to a specific causal mechanism. For the signal from the experiment with combined CO{sub 2}/sulfate aerosol forcing, C(t) provides information on pattern congruence, but trends in C(t) are difficult to interpret without decomposing the statistic into pattern similarity and global-mean change components. They therefore focus on R(t), which is a more useful statistic for discriminating between forcing mechanisms with different pattern signatures but similar rates of global mean change