Emergent Constraints on CMIP6 Climate Warming Projections: Contrasting Cloud- and Surface Temperature-Based Constraints

Abstract

Abstract The latest Sixth Coupled Model Intercomparison Project (CMIP6) multi-model ensemble shows a broader range of projected warming than the previous-generation CMIP5 ensemble. We show that the projected warming is well-correlated with tropical and subtropical low-level cloud properties. These physically-meaningful relations enable us to use observed cloud properties to constrain future climate warming. We develop multivariate-linear-regression models with metrics selected from a set of potential constraints based on a step-wise selection approach. The resulting linear regression model using two low-cloud metrics shows better cross-validated results than regression models which use single metrics as constraints. Application of a regression model using the low-cloud metrics to climate projections results in similar estimates of the mean, but substantially-narrower ranges, of projected 21st century warming when compared with unconstrained simulations. The resulting projected global-mean warming in 2081-2100 relative to 1995-2014 is 2.84-5.12 K (5-95% range) for Shared Socioeconomic Pathway (SSP) 5-8.5, compared with a range of 2.34-5.81 K for unconstrained projections, and 0.60-1.70 K for SSP1-2.6, compared to an unconstrained range of 0.38-2.04 K. We provide evidence for a higher lower-bound of the projected warming range than that obtained from constrained projections based on the past global-mean temperature trend. Consideration of the impact of the sea surface temperature pattern effect on the recent observed warming trend, which is not well-captured in the CMIP6 ensemble, indicates that the relatively-low projected warming resulting from the global-mean temperature trend constraint may not be reliable and provides further justification for the use of climatologically-based cloud metrics to constrain projections.