2.8.4 Linearity of the Forcing-Response Relationship

Reporting findings from several studies, the TAR concluded that responses to individual RFs could be linearly added to gauge the global mean response, but not necessarily the regional response (Ramaswamy et al., 2001). Since then, studies with several equilibrium and/or transient integrations of several different GCMs have found no evidence of any nonlinearity for changes in greenhouse gases and sulphate aerosol (Boer and Yu, 2003b; Gillett et al., 2004; Matthews et al., 2004; Meehl et al., 2004). Two of these studies also examined realistic changes in many other forcing agents without finding evidence of a nonlinear response (Meehl et al., 2004; Matthews et al., 2004). In all four studies, even the regional changes typically added linearly. However, Meehl et al. (2004) observed that neither precipitation changes nor all regional temperature changes were linearly additive. This linear relationship also breaks down for global mean temperatures when aerosol-cloud interactions beyond the cloud albedo RF are included in GCMs (Feichter et al., 2004; see also Rotstayn and Penner, 2001; Lohmann and Feichter, 2005). Studies that include these effects modify clouds in their models, producing an additional radiative imbalance. Rotstayn and Penner (2001) found that if these aerosol-cloud effects are accounted for as additional forcing terms, the inference of linearity can be restored (see Sections 2.8.3 and 2.8.5). Studies also find nonlinearities for large negative RFs, where static stability changes in the upper troposphere affect the climate feedback (e.g., Hansen et al., 2005). For the magnitude and range of realistic RFs discussed in this chapter, and excluding cloud-aerosol interaction effects, there is high confidence in a linear relationship between global mean RF and global mean surface temperature response.