On the Physics of Three Integrated Assessment Models

Raphael Calel McCourt School of Public Policy, Georgetown University, Washington, D.C., and Grantham Research Institute on Climate Change and the Environment, London School of Economics, London, United Kingdom

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David A. Stainforth Grantham Research Institute on Climate Change and the Environment, and Centre for the Analysis of Time Series, London School of Economics, London, and Department of Physics, University of Warwick, Coventry, United Kingdom

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Abstract

Integrated assessment models (IAMs) are the main tools for combining physical and economic analyses to develop and assess climate change policy. Policy makers have relied heavily on three IAMs in particular—Dynamic Integrated model of Climate and the Economy (DICE), The Climate Framework for Uncertainty, Negotiation and Distribution (FUND), and Policy Analysis for the Greenhouse Effect (PAGE)—when trying to balance the benefits and costs of climate action. Unpacking the physics of these IAMs accomplishes four things. First, it reveals how the physics of these IAMs differ and the extent to which those differences give rise to different visions of the human and economic costs of climate change. Second, it makes these IAMs more accessible to the scientific community and thereby invites further physical expertise into the IAM community so that economic assessments of climate change can better reflect the latest physical understanding of the climate system. Third, it increases the visibility of the link between the physical sciences and the outcomes of policy assessments so that the scientific community can focus more sharply on those unresolved questions that loom largest in policy assessments. And finally, in making explicit the link between these IAMs and the underlying physical models, one gains the ability to translate between IAMs using a common physical language. This translation key will allow multimodel policy assessments to run all three models with physically comparable baseline scenarios, enabling the economic sources of uncertainty to be isolated and facilitating a more informed debate about the most appropriate mitigation pathway.

© 2017 American Meteorological Society.

CORRESPONDING AUTHOR: Raphael Calel, raphael.calel@georgetown.edu

A supplement to this article is available online (10.1175/BAMS-D-16-0034.2)

Abstract

Integrated assessment models (IAMs) are the main tools for combining physical and economic analyses to develop and assess climate change policy. Policy makers have relied heavily on three IAMs in particular—Dynamic Integrated model of Climate and the Economy (DICE), The Climate Framework for Uncertainty, Negotiation and Distribution (FUND), and Policy Analysis for the Greenhouse Effect (PAGE)—when trying to balance the benefits and costs of climate action. Unpacking the physics of these IAMs accomplishes four things. First, it reveals how the physics of these IAMs differ and the extent to which those differences give rise to different visions of the human and economic costs of climate change. Second, it makes these IAMs more accessible to the scientific community and thereby invites further physical expertise into the IAM community so that economic assessments of climate change can better reflect the latest physical understanding of the climate system. Third, it increases the visibility of the link between the physical sciences and the outcomes of policy assessments so that the scientific community can focus more sharply on those unresolved questions that loom largest in policy assessments. And finally, in making explicit the link between these IAMs and the underlying physical models, one gains the ability to translate between IAMs using a common physical language. This translation key will allow multimodel policy assessments to run all three models with physically comparable baseline scenarios, enabling the economic sources of uncertainty to be isolated and facilitating a more informed debate about the most appropriate mitigation pathway.

© 2017 American Meteorological Society.

CORRESPONDING AUTHOR: Raphael Calel, raphael.calel@georgetown.edu

A supplement to this article is available online (10.1175/BAMS-D-16-0034.2)

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