Detection of anthropogenic climate change using an atmospheric GCM

Atmosphere-only general circulation models are shown to be a useful tool fo r detecting an anthropogenic effect on climate and understanding recent cli mate change. Ensembles of atmospheric runs are all forced with the same obs erved changes in sea surface temperatures and sea-ice extents but differ in terms of the combinations of anthropogenic effects included. Therefore, ou r approach aims to detect the 'immediate' anthropogenic impact on the atmos phere as opposed to that which has arisen via oceanic feedbacks. We have ad apted two well-used detection techniques, pattern correlations and fingerpr ints, and both show that near-decadal changes in the patterns of zonal mean upper air temperature are well simulated, and that it is highly unlikely t hat the observed changes could be accounted for by sea surface temperature variations and internal variability alone. Furthermore, we show that for zo nally averaged upper air temperature, internal 'noise' in the atmospheric m odel is small enough that a signal emerges from the data even on interannua l time scales; this would not be possible in a coupled ocean-atmosphere gen eral circulation model. Finally, although anthropogenic forcings have had a significant impact on global mean land surface temperature, we find that t heir influence on the pattern of local deviations about this mean is so far undetectable. In order to achieve this in the future, as the signal grows, it will also be important that the response of the Northern Hemisphere mid -latitude westerly flow to changing sea surface temperatures is well simula ted in climate model detection studies.