Estimating the Likelihood of GHG Concentration Scenarios From Probabilistic Integrated Assessment Model Simulations

The climate scenarios that form the basis for current risk assessments have no assigned probabilities, and this impedes analysis of future risks. This paper proposes an approach to estimate probability carbon dioxide (CO2) concentration used in key change modeling experiments. It computes CO2 emissions compatible with concentrations prescribed by Coupled Model Intercomparison Project Phase 5 (CMIP5) CMIP6 distribution these cumulative is interpreted as likelihood given a pathway. Using Bayesian analysis, each pathway can be estimated from probabilistic sample emissions. demonstrated five emission simulation ensembles four Integrated Assessment Models (IAM), leading independent estimates Representative Concentration Pathways (RCP) Shared Socioeconomic (SSP). Results suggest SSP5-8.5 unlikely second half 21st century, but offer clear consensus on which remaining most likely. Estimates likelihoods associated RCP SSP are affected sampling errors, differences sources simulated IAMs, lack common experimental framework IAM simulations. These shortcomings, along small ensemble size, limit applicability results presented here. Novel joint Earth System experiments needed deliver actionable assessments.