Quantifying global and sub-global socioeconomic transition uncertainty for climate management and risk analyses

There is a general absence of quantitative information regarding socioeconomic transformation uncertainty and risk relevant to policymakers and planning. To address this need, we develop a probabilistic multi-sector coupled human-natural system model to quantify global and sub-global uncertainty about future socioeconomic possibilities and structure, exploring both parametric uncertainty and deep uncertainty about climate policy. Specifically, using the framework, we sample from probability distributions for socioeconomic parameters to derive distributions for potential global and sub-global outcomes without and with additional climate policy. For the latter, we evaluate a range of increasingly stringent global policies, as well as “optimistic” and “more pessimistic” greenhouse gas management conditions that represent deep uncertainties for climate strategy: international emissions cooperation, coverage of land use related emissions and carbon stocks, and the availability of carbon dioxide removal (CDR) technologies. We find uncertainty in socioeconomic structure to be significant, globally and nationally, as well as at the sector and consumer level, with broad ranges of potential societies consistent with any single global emissions pathway. We find both climate policy and non-policy uncertainties to be substantive risks that countries need to consider and manage. Such findings highlight that planning for a single future (globally or sub-globally) is risky. We find that sets of distributions—more optimistic and more pessimistic, as well as across policy stringency—are relevant to risk assessment and planning, with distribution overlaps indicating that the same condition can be consistent with different global futures and climates—useful information for risk management. The results also suggest that uncertainty about the size of economies and their make-up is relevant and important to consider in climate risk assessment (transition and physical), social cost of greenhouse gas estimation, and GHG goal setting. In addition to informing risk assessments, our results might also help inform the weighting of development pathways in the literature.