Modeling Uncertainty in Climate Change: A Multi-Model Comparison
Kenneth Gillingham (Yale University); William Nordhaus (Yale University); David Anthoff (University of California); Valentina Bosetti (Bocconi University); Haewon McJeon (PNNL – College Park); Geoffrey Blanford (EPRI); Peter Christensen (Aarhus University); John Reilly (MIT) Paul Sztorc (Yale University)
Climate Change, Integrated Assessment Models
Mitigation, Innovation and Transformation Pathways
Journal of the Association of Environmental and Resource Economists
This FEEM working paper by researcher Valentina Bosetti et al. presents the results of the first comprehensive study on the key uncertainty drivers for climate change when looking at 2100 temperatures and 2100 emissions.
“The study shows that uncertainty surrounding parameters may be more important than uncertainty in model structure. The resulting distributions also provide insights on tail events, i.e. low probability and extreme consequences scenarios.”
Suggested citation: Gillingham, K., W. Nordhaus, D. Anthoff, V. Bosetti, H. McJeon, G. Blanford, P. Christensen, J. Reilly, P. Sztorc, (2018), ‘Modeling Uncertainty in Integrated Assessment of Climate Change: A Multimodel Comparison’, Journal of the Association of Environmental and Resource Economists 5, no. 4 (October 2018): 791-826. https://doi.org/10.1086/698910