Using optimal detection techniques with climate model simulations, most ofthe observed increase of near surface temperatures over the second half of thetwentieth century is attributed to anthropogenic influences. However, thepartitioning of the anthropogenic influence to individual factors, such asgreenhouse gases and aerosols, is much less robust. Differences in how forcingfactors are applied, in their radiative influence and in models' climatesensitivities, substantially influence the response patterns. We find standardoptimal detection methodologies cannot fully reconcile this response diversity.By selecting a set of experiments to enable the diagnosing of greenhouse gasesand the combined influence of other anthropogenic and natural factors, we findrobust detections of well mixed greenhouse gases across a large ensemble ofmodels. Of the observed warming over the 20th century of 0.65K/century we find,using a multi model mean not incorporating pattern uncertainty, a well mixedgreenhouse gas warming of 0.87 to 1.22K/century. This is partially offset bycooling from other anthropogenic and natural influences of -0.54 to-0.22K/century. Although better constrained than recent studies, theattributable trends across climate models are still wide, with implications forobservational constrained estimates of transient climate response. Some of theuncertainties could be reduced in future by having more model data to betterquantify the simulated estimates of the signals and natural variability, bydesigning model experiments more effectively and better quantification of theclimate model radiative influences. Most importantly, how model patternuncertainties are incorporated into the optimal detection methodology should beimproved.
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