For several decades, the Massachusetts Institute of Technology (MIT) Joint Program on the Science and Policy of Global Change has been investigating uncertainty in climate change using the MIT Integrated Global System Model (IGSM) framework, an integrated assessment model that couples an earth system model of intermediate complexity (with a 2D zonal-mean atmosphere) to a human activity model. Since the IGSM includes a human activity model, it is possible to analyze uncertainties in emissions resulting from uncertainties intrinsic to the economic model, from parametric uncertainty to uncertainty in future climate policies. Another major feature is the flexibility to vary key climate parameters controlling the climate response: climate sensitivity, net aerosol forcing and ocean heat uptake rate. The IGSM has long been used to perform probabilistic forecasts based on estimates of probability density functions of climate parameters. In this study, we use a two-pronged approach centered on the IGSM.
On the one hand, the MIT IGSM-CAM framework links the IGSM to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM), with new modules developed and implemented in CAM to allow climate parameters to be changed to match those of the IGSM. On the other hand, a pattern scaling method extends the latitudinal projections of the IGSM 2D zonal-mean atmosphere by applying longitudinally resolved patterns from observations, and from climate model projections archived from exercises carried out for the 4th Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC). The IGSM-CAM physically simulates changes in both mean climate and extreme events, but relies on one particular model, while the pattern scaling approach allows spatial patterns of different climate models to be considered, but cannot physically simulate changes in extreme events.
The simulations presented in this paper were carried out for two emission scenarios, a business as usual scenario and a 660 ppm of CO2-equivalent stabilization, which are similar to, respectively, the Representative Concentration Pathways RCP8.5 and RCP4.5 scenarios. Values of climate sensitivity and net aerosol forcing used in the simulations within the IGSM-CAM framework provide a good approximation for the median, and the lower and upper bound of 90% probability distribution of 21st century climate change. Meanwhile, the pattern scaling approach produces a meta-ensemble that can be treated as a hybrid frequency distribution (HFD) that integrates the uncertainty in the IGSM ensemble and in the regional patterns of climate change of 17 IPCC climate models. Together, the two approaches provide a comprehensive analysis of possible climate change over Northern Eurasia and its potential impacts.