Assessing the climate uncertainty over the Social Cost of Carbon

You can find here the report produced following my research internship at the end of my 3rd year at the Ecole Polytechnique. I did this internship at IIASA under the supervision of Thomas Gasser and worked on the links between climate uncertainty and the social cost of carbon.

The Social Cost of Carbon is probably the most important metric when it comes to climate change mitigation. This term represents the economic cost caused by an additional ton of carbon dioxide emissions or its equivalent. Since its creation, the Social Cost ofCarbon has become a central tool used in climate change policy-design, particularly in the case of regulatory policies that involve greenhouse gas emissions. However, the Social Cost of Carbon suffers from an absence of known uncertainties. Which means that it is not possible to ascertain a confidence interval for a given estimate of the Social Cost of Carbon whereas, on the contrary, there is great uncertainty on future global warming. In this study, we aim at estimating the uncertainty of the Social Cost of Carbon with the DICE model, probably the most often used Integrated Assessment Model to compute the Social Cost of Carbon. To this end, we develop a new compact climate model that is designed according to state-of-the-art knowledge in climate physics. Coupled with a Bayesian calibration, we perform an uncertainty analysis with a Monte Carlo setup. With this upgraded DICE framework, we estimate the Social Cost of Carbon and its uncertainty, on a various range of potential future scenarios, the Shared Socioeconomic Pathway. This finally allows us to conclude on the main factors determining the Social Cost of Carbon as well as on some of the questions raised by this study.

Download the paper here.

Recommended citation: Cheritel, C.: Assessing the climate uncertainty over the Social Cost of Carbon, Ecole polytechnique third year research internship report, 2019.