An Integrated Assessment Framework for Uncertainty Studies in Global and Regional Climate Change: The IGSM-CAM
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MITJPSPGC_Rpt223.pdf
Description
main article
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6.61 MB
Format
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Author(s)
Monier, Erwan
Scott, Jeffery R.
Sokolov, Andrei P.
Forest, Chris E.
Schlosser, C. Adam
Date Issued
June 18, 2012
Publisher
MIT Joint Program on the Science and Policy of Global Change
Citation
Report no. 223
Series/Report no.
Joint Program Report Series;223
Abstract
This paper describes an integrated assessment framework for uncertainty studies in global and regional climate change. In this framework, the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an earth system model of intermediate complexity to a human activity model, is linked to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). Since the IGSM-CAM incorporates 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. Thus, the IGSM-CAM is a computationally efficient framework to explore the uncertainty in future global and regional climate change due to uncertainty in the climate response and projected emissions. This study further presents 21st century simulations based on two emissions scenarios (unconstrained scenario and stabilization scenario at 660 ppm CO2-equivalent by 2100) and three sets of climate parameters. The chosen climate parameters provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century climate change. As such, this study presents new estimates of the 90% probability interval of regional climate change for different emissions scenarios. These results underscore the large uncertainty in regional climate change resulting from uncertainty in climate parameters and emissions, and the statistical uncertainty due to natural variability.
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http://globalchange.mit.edu/research/publications
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