Assessments of the veracity of model-generated variability are difficult because variability in observed climate data during the 20th century is composed of natural and anthropogenic (greenhouse gas and sulfate aerosol) factors in addition to internal climate fluctuations. Comparisons should be improved if some of these factors could either be extracted from real world data or additions be made to model-generated variability. Both options involve several assumptions, the most important of which is that the climate system is linear to a first approximation. We discuss this and other assumptions and present results from two different methods of removing variability related to anthropogenic factors using energy balance models (EBMs) and atmosphere/ocean general circulation models (A/OGCMs). At a global scale, the pattern of the trend of surface temperature over the 1966–1995 period, after removing the anthropogenic effect, shows some strong similarities between the two methods, with the strongest residual warming evident over much of northern Asia and northern North America.