Uncertainty Analysis of Climate Change and Policy Response

Joint Program Report
Uncertainty Analysis of Climate Change and Policy Response
Webster, M., C. Forest, J. Reilly, M. Babiker, D. Kicklighter, M. Mayer, R. Prinn, M. Sarofim, A. Sokolov, P. Stone and C. Wang (2002)
Joint Program Report Series, 21 pages

Report 95 [Download]

Abstract/Summary:

To aid climate policy decisions, accurate quantitative descriptions of the uncertainty in climate outcomes under various possible policies are needed. Here, we apply an earth systems model to describe the uncertainty in climate projections under two different policy scenarios. This study illustrates an internally consistent uncertainty analysis of one climate assessment modeling framework, propagating uncertainties in both economic and climate components, and constraining climate parameter uncertainties based on observation. We find that in the absence of greenhouse gas emissions restrictions, there is a one in forty chance that global mean surface temperature change will exceed 4.9 °C by the year 2100. A policy case with aggressive emissions reductions over time lowers the temperature change to a one in forty chance of exceeding 3.2°C, thus reducing but not eliminating the chance of substantial warming.

Citation:

Webster, M., C. Forest, J. Reilly, M. Babiker, D. Kicklighter, M. Mayer, R. Prinn, M. Sarofim, A. Sokolov, P. Stone and C. Wang (2002): Uncertainty Analysis of Climate Change and Policy Response. Joint Program Report Series Report 95, 21 pages (http://globalchange.mit.edu/publication/14684)
  • Joint Program Report
Uncertainty Analysis of Climate Change and Policy Response

Webster, M., C. Forest, J. Reilly, M. Babiker, D. Kicklighter, M. Mayer, R. Prinn, M. Sarofim, A. Sokolov, P. Stone and C. Wang

Report 

95
21 pages
2002

Abstract/Summary: 

To aid climate policy decisions, accurate quantitative descriptions of the uncertainty in climate outcomes under various possible policies are needed. Here, we apply an earth systems model to describe the uncertainty in climate projections under two different policy scenarios. This study illustrates an internally consistent uncertainty analysis of one climate assessment modeling framework, propagating uncertainties in both economic and climate components, and constraining climate parameter uncertainties based on observation. We find that in the absence of greenhouse gas emissions restrictions, there is a one in forty chance that global mean surface temperature change will exceed 4.9 °C by the year 2100. A policy case with aggressive emissions reductions over time lowers the temperature change to a one in forty chance of exceeding 3.2°C, thus reducing but not eliminating the chance of substantial warming.

Supersedes: 

Uncertainty Analysis of Global Climate Change Projections