Carbon Mitigation Initiative

Tenth Year Annual Report:
Carbon Policy & Integration: Future Plans

Communicating Uncertainty

A new faculty research initiative addressing carbon issues may begin in the spring of 2011 if a faculty group with many CMI participants wins an internal competition for funding being run by the Princeton Institute for International and Regional Studies. The title of the proposed project is "Communicating uncertainty: science, institutions, ethics." Michael Oppenheimer, Steve Pacala, and Rob Socolow are three of the twelve faculty members who propose to lead this project over a three-year period. Most of the other faculty recruited to this project are leaders in social science and the humanities. An added component is the participation of the Geophysical Fluid Dynamics Laboratory.

This initiative represents a major success for CMI in raising the profile of academic scholarship addressing the carbon and climate problem at the University. The prospects are high that this project will break new ground on topics like the design of effective international institutions and the tradeoff between fairness and feasibility.

Carbon Mitigation in a World with a Low Carbon Price and a High Oil Price

Until recently, the expectation among many energy policymakers has been that over the next decade, energy security and climate change would be policy drivers of comparable strength. The recent struggles to formulate compelling climate change policy within countries and internationally, however, raise the prospect that the world could see a high oil price and a low carbon price, leading perhaps to investments that become stranded assets when climate change policy returns. Examples of such dangerous attractions are synfuels from coal without CCS and high-carbon-intensity primary energy - fossil and biological. Other responses that might emerge and then be regretted are a focus on CCS that is limited to enhanced oil recovery, a shift of all energy-efficiency policy toward fuels and away from electricity (therefore, toward transport and away from buildings) and reduced subsidies for renewable and nuclear power. CMI will seek opportunities to affect this discussion.

Game-Theoretic Modeling of Energy Investment under Innovation

In a new project, CMI researchers are modeling the energy infrastructure investment strategies of nations under different expectations of the future. Learning by doing can lead to cost reductions world-wide, especially in the case of green technologies like wind and solar PV. Is this reason enough for some countries to unilaterally invest in green technologies?

Using techniques from game theory, Shoibal Chakravarty (CMI) and E. Somanathan (Professor, Indian Statistical Institute and PEI Visiting Professor) aim to understand this issue. The researchers contrast strategic national investments with a myopic planning horizon versus a long term horizon that also takes into account global cost reductions due to learning by doing. The project explores the hypothesis that energy investment planning has two stable equilibrium paths: 1. myopic planning horizon with most of the investment going to fossil fuel energy and 2. long term planning with substantial investment in green energy in order to implement cost reduction by learning by doing. It is quite possible that the long term planning path might turn out to be cheaper.

Development of Open Source Software for Climate-Economics Modeling

A continuing aim of CMI has been to provide public-domain tools for analysis in order to encourage wider participation of the global research community seeking to contribute to climate and energy studies. A major effort toward this end is being led by Shoibal Chakravarty (CMI). The goal of this project is to develop a modeling language and software platform for effective modeling of the economic aspects of energy-economics-climate models. These models are numerical optimization models and require a modeling language or platform to convey the model expressed in human readable form to specialized solver programs, and to process the solutions from these solvers. The project will eventually provide a partial open source substitute to current commercial modeling languages like GAMS ( and AMPL ( The modeling platform will make use of similar open source projects for solvers ( Finally, high quality energy-climate models will be developed for use and collaborative development by the policy-making and modeling community.

The eventual goals of the project are:

  • Use the modeling platform to bring down the cost of modeling and policy making tools. This should benefit, especially, users in developing countries and non-governmental organizations.
  • Encourage a culture of verifiability, transparency and inter-model comparability in the modeling and policy-making community.
  • Foster subsequent use of these tools, especially on the web, for public awareness, for education and, most importantly, for effective and transparent policy analysis.

Robust Projections of Sea Level

The holy grail of ice sheet modeling is a physically-based, observationally constrained, robust projection of sea level rise rates, over timescales relevant to decision-making. Yet because of uncertainties and numerical limitations, this is not achievable; there are tradeoffs in model comprehensiveness and scope. We are examining various strategies to improve the robustness of SLR projections, including the assimilation of regional and simplified dynamic models into statistical techniques and the incorporation of paleoclimatic constraints.

In collaboration with GEO faculty and former WWS Postdoctoral Fellow Bob Kopp, Michael Oppenheimer has undertaken a statistical analysis of LIG (last interglacial period) sea level proxies. The next steps involve the development of a statistical transfer function for the LIG that would be informative about the near future. As GFDL's ice sheet modeling advances, such paleoclimatic analyses provide opportunities to test the model. Ultimately, ice sheet modeling and paleo-sea level analysis will be linked to assemble a policy-relevant probabilistic risk assessment for sea level rise. This capability and the credibility of the approach will grow over time as the ice sheet modeling is incorporated through collaboration with GFDL.

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Last update: March 23 2011
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