IPCC Fourth Assessment Report: Climate Change 2007
Climate Change 2007: Working Group I: The Physical Science Basis Implications for Transient Climate Response

Quantification of the likely contributions of greenhouse gases and other forcing factors to past temperature change (Section in turn provides observational constraints on the transient climate response, which determines the rapidity and strength of a global temperature response to external forcing (see Glossary and Sections and for detailed definitions) and therefore helps to constrain likely future rates of warming. Scaling factors derived from detection analyses can be used to scale predictions of future change by assuming that the fractional error in model predictions of global mean temperature change is constant (Allen et al., 2000, 2002; Allen and Stainforth, 2002; Stott and Kettleborough, 2002). This linear relationship between past and future fractional error in temperature change has been found to be sufficiently robust over a number of realistic forcing scenarios to introduce little additional uncertainty (Kettleborough et al., 2007). In this approach based on detection and attribution methods, which is compared with other approaches for producing probabilistic projections in Section, different scaling factors are applied to the greenhouse gases and to the response to other anthropogenic forcings (notably aerosols); these separate scaling factors are used to account for possible errors in the models and aerosol forcing. Uncertainties calculated in this way are likely to be more reliable than uncertainty ranges derived from simulations by coupled AOGCMs that happen to be available. Such ensembles could provide a misleading estimate of forecast uncertainty because they do not systematically explore modelling uncertainty (Allen et al., 2002; Allen and Stainforth, 2002). Stott et al. (2006c) compare observationally constrained predictions from three coupled climate models with a range of sensitivities and show that predictions made in this way are relatively insensitive to the particular choice of model used to produce them. The robustness to choice of model of such observationally constrained predictions was also demonstrated by Stone et al. (2007a) for the MMD ensemble. The observationally constrained transient climate response at the time of doubling of atmospheric CO2 following a 1% per year increase in CO2 was estimated by Stott et al. (2006c) to lie between 1.5°C and 2.8°C (Section 9.6.2, Figure 9.21). Such approaches have also been used to provide observationally constrained predictions of global mean (Stott and Kettleborough, 2002; Stone et al., 2007a) and continental-scale temperatures (Stott et al., 2006a) following the IPCC Special Report on Emission Scenarios (SRES) emissions scenarios, and these are discussed in Sections and 11.10. Studies of Indices of Temperature Change

Another method for identifying fingerprints of climate change in the observational record is to use simple indices of surface air temperature patterns that reflect features of the anticipated response to anthropogenic forcing (Karoly and Braganza, 2001; Braganza et al., 2003). By comparing modelled and observed changes in such indices, which include the global mean surface temperature, the land-ocean temperature contrast, the temperature contrast between the NH and SH, the mean magnitude of the annual cycle in temperature over land and the mean meridional temperature gradient in the NH mid-latitudes, Braganza et al. (2004) estimate that anthropogenic forcing accounts for almost all of the warming observed between 1946 and 1995 whereas warming between 1896 and 1945 is explained by a combination of anthropogenic and natural forcing and internal variability. These results are consistent with the results from studies using space-time detection techniques (Section

Diurnal temperature range (DTR) has decreased over land by about 0.4°C over the last 50 years, with most of that change occurring prior to 1980 (Section This decreasing trend has been shown to be outside the range of natural internal variability estimated from models. Hansen et al. (1995) demonstrate that tropospheric aerosols plus increases in continental cloud cover, possibly associated with aerosols, could account for the observed decrease in DTR. However, although models simulate a decrease in DTR when they include anthropogenic changes in greenhouse gases and aerosols, the observed decrease is larger than the model-simulated decrease (Stone and Weaver, 2002, 2003; Braganza et al., 2004). This discrepancy is associated with simulated increases in daily maximum temperature being larger than observed, and could be associated with simulated increases in cloud cover being smaller than observed (Braganza et al., 2004; see Section for observations), a result supported by other analyses (Dai et al., 1999; Stone and Weaver, 2002, 2003).