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The pattern of global mean temperature (GMT) change is calculated by regressing local surface air temperature (SAT) to GMT for an ensemble of CMIP5 models and for observations over the last 132 years. Calculations are based on the historical period and climate change scenarios. As in the observations the warming pattern contains a warming hole over the subpolar North Atlantic. Using a bivariate regression of SAT to GMT and an index of the Atlantic meridional overturning circulation (AMOC), the warming pattern is decomposed in a radiatively forced part and an AMOC fingerprint. The North Atlantic warming hole is associated with a decline of the AMOC. The AMOC fingerprint resembles Atlantic multidecadal variability (AMV), but details of the pattern change when the AMOC decline increases, underscoring the nonlinearity in the response.The warming hole is situated south of deep convection sites, indicating that it involves an adjustment of the gyre circulation, although it should be noted that some models feature deep convection in the middle of the subpolar gyre. The warming hole is already prominent in historical runs, where the response of the AMOC to GMT is weak, which suggests that it is involved in an ocean adjustment that precedes the AMOC decline. In the more strongly forced scenario runs, the warming hole over the subpolar gyre becomes weaker, while cooling over the Nordic seas increases, consistent with previous findings that deep convection in the Labrador and Irminger Seas is more vulnerable to changes in external forcing than convection in the Nordic seas, which only reacts after a threshold is passed.

Both historical and idealized climate model experiments are performed with a variety of Earth system models of intermediate complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO₂, additional greenhouse gases, land use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20th century trends in surface air temperature and carbon uptake are reasonably well simulated when compared to observed trends. Land carbon fluxes show much more variation between models than ocean carbon fluxes, and recent land fluxes appear to be slightly underestimated. It is possible that recent modelled climate trends or climate–carbon feedbacks are overestimated resulting in too much land carbon loss or that carbon uptake due to CO₂ and/or nitrogen fertilization is underestimated. Several one thousand year long, idealized, 2 × and 4 × CO₂ experiments are used to quantify standard model characteristics, including transient and equilibrium climate sensitivities, and climate–carbon feedbacks. The values from EMICs generally fall within the range given by general circulation models. Seven additional historical simulations, each including a single specified forcing, are used to assess the contributions of different climate forcings to the overall climate and carbon cycle response. The response of surface air temperature is the linear sum of the individual forcings, while the carbon cycle response shows a non-linear interaction between land-use change and CO₂ forcings for some models. Finally, the preindustrial portions of the last millennium simulations are used to assess historical model carbon-climate feedbacks. Given the specified forcing, there is a tendency for the EMICs to underestimate the drop in surface air temperature and CO₂ between the Medieval Climate Anomaly and the Little Ice Age estimated from palaeoclimate reconstructions. This in turn could be a result of unforced variability within the climate system, uncertainty in the reconstructions of temperature and CO₂, errors in the reconstructions of forcing used to drive the models, or the incomplete representation of certain processes within the models. Given the forcing datasets used in this study, the models calculate significant land-use emissions over the pre-industrial period. This implies that land-use emissions might need to be taken into account, when making estimates of climate–carbon feedbacks from palaeoclimate reconstructions