Abstract
Climate policies should account for our limited understanding of the Earth system’s behaviour. This is overwhelmingly done by designing climate policies first and estimating the system’s probabilistic response afterwards (ex-post), whereas ensuring the policies’ robustness requires incorporating physical uncertainty during their design (ex-ante). Usage of the latter approach, however, has been confined to stylized studies and hypothetical setups. Here, we implement a robust decision-making algorithm in a global climate-economy model that embeds a state-of-the-art estimate of physical uncertainties, obtained through Bayesian fusion of the latest data from Earth system models and observations. Using this new integrated assessment framework, we derive robust global climate policies under a variety of cost-benefit and cost-effective experiments.
In robust policies, net-zero CO2 emissions must be reached up to 55 years earlier, and the carbon price must be up to 270% higher, than in non-robust ones derived from Monte Carlo methods. On the long term, robust temperature pathways significantly depart from their all-time maximum, which entails developing and sustaining negative emission technologies for centuries. On the long term, robust temperature pathways significantly depart from their all-time maximum, which entails developing and sustaining negative emission technologies for centuries.
Invited by: Emanuele Campiglio
Local Organizer: Alessandro Tavoni