Emulating IPCC AR4 atmosphere-ocean and carbon cycle models for projecting global-mean, hemispheric and land/ocean temperatures: MAGICC 6.0

International audience ; Current scientific knowledge on the future response of the climate system to human-induced perturbations is comprehensively captured by various model intercomparison efforts. In the preparation of the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC), intercomparisons were organized for atmosphere-ocean general circulation models (AOGCMs) and carbon cycle models, named "CMIP3" and "C4MIP", respectively. Despite their tremendous value for the scientific community and policy makers alike, there are some difficulties in interpreting the results. For example, key radiative forcings have not been considered or standardized in the majority of AOGCMs integrations and carbon cycle runs. Furthermore, the AOGCM analysis of plausible emission pathways was restricted to only three SRES scenarios. This study attempts to address these issues. We present an updated version of MAGICC, the simple carbon cycle-climate model used in past IPCC Assessment Reports with enhanced representation of time-varying climate sensitivities, carbon cycle feedbacks, aerosol forcings and ocean heat uptake characteristics. This new version of MAGICC (6.0) is successfully calibrated against the higher complexity AOGCM and carbon cycle models. Parameterizations of MAGICC 6.0 are provided. Previous MAGICC versions and emulations shown in IPCC AR4 (WG1, Fig. 10.26, page 803) yielded, in average, a 10% larger global-mean temperature increase over the 21st century compared to the AOGCMs. The reasons for this difference are discussed. The emulations presented here using MAGICC 6.0 match the mean AOGCM responses to within 2.2% for the SRES scenarios. This enhanced emulation skill is due to: the comparison on a "like-with-like" basis using AOGCM-specific subsets of forcings, a new calibration procedure, as well as the fact that the updated simple climate model can now successfully emulate some of the climate-state dependent effective climate sensitivities of AOGCMs. The mean diagnosed effective ...