| |
ESD Research Domains
ESD Research Approaches
|
|
One of the most significant environmental challenges
of the 21st century
will be how to address the threat of global climate change. Reductions
in
greenhouse gas emissions from human activities will require the
development
of new technologies and energy sources, at potentially high cost.
This effort is
complicated by the wide range of uncertainty in future climate
projections.
(2090–2100) – (2010–2000)
| |
Probability
distributions of temperature change over the 21st century
under no climate policy, stabilization of CO2 at 750ppm,
and stabilization at 550ppm. The probability of exceeding
4¾C warming under these policies are 80%, 60%, and 5%, respectively.
(click image to see larger size)
From M. Webster, C.
Forest, H. Jacoby, S. Paltsev, R. Prinn, J. Reilly, M. Sarofim,
A. Schlosser, A. Sokolov, P. Stone. “Long-term greenhouse
gas stabilization and the risks of dangerous impacts.”
Working Paper, 2008.
|
A primary focus of the climate change research at
MIT is to characterize the uncertainty in future climate impacts.
Using MIT’s Integrated Global System Model, ESD researchers
have performed a rigorous assessment of the most
critical uncertain assumptions in the model. Using data where
available and techniques to elicit expert judgment, the researchers
have constructed probability density functions for the uncertain
model parameters, and have used Monte Carlo simulation techniques
for uncertainty propagation. Probability distributions of critical
model outcomes, such as the future surface temperature of the
earth, can then be compared between different greenhouse gas concentration
stabilization paths.
The results of this work provide information on
how the risks of extreme climate impacts are reduced by limited
greenhouse gas emissions. These probabilistic results are used
by numerous government agencies, including the Environmental Protection
Agency, the Department of Energy, and the Congressional Budget
Office, as well as parties to international climate negotiations,
to understand the level of mitigation effort needed to achieve
climate objectives with a given level of confidence.
Webster, M.D., C. Forest, J. Reilly, M. Babiker,
D. Kicklighter, M. Mayer, R. Prinn, M. Sarofim, A. Sokolov, P.
Stone, and C. Wang, “Uncertainty Analysis of Climate Change
and Policy Response,” Climatic Change, 61(3), 295–320,
2003.
Congressional Budget Office (2005), “Uncertainty
in Analyzing Climate Change: Policy Implications,” January
2005.
|
|
|
