Addressing partial identification in climate modeling and policy analysis.

Numerical simulations of the global climate system provide inputs to integrated assessment modeling for estimating the impacts of greenhouse gas mitigation and other policies to address global climate change. While essential tools for this purpose, computational climate models are subject to considerable uncertainty, including intermodel "structural" uncertainty. Structural uncertainty analysis has emphasized simple or weighted averaging of the outputs of multimodel ensembles, sometimes with subjective Bayesian assignment of probabilities across models.

Optimizing U.S. mitigation strategies for the light-duty transportation sector: what we learn from a bottom-up model.

Few integrated analysis models examine significant U.S. transportation greenhouse gas emission reductions within an integrated energy system.