Revisiting two-layer energy balance models for climate assessment

Abstract Given the pivotal role of probabilistic approaches with two-layer energy balance models in the latest climate assessment, this study aims to gain deeper insight into their advancement by comparing different approaches for generating constrained posterior ensembles. Several methodological improvements are possible both in the calibration of model parameters to the behavior of comprehensive Earth system models and in constraining the calibrated parameter ensemble with other lines of evidence. The results imply that a conventional single parameter representing evolving climate feedback characteristics is not a requirement for reliable climate projections; rather, there are potential improvements on the forcing side regarding the separation of forcing and feedbacks. Constraining the ensemble based on observational and expert-assessed climate metrics, which critically affects probabilistic climate assessment, needs to appropriately deal with different constraints on a multivariate space in a standardized and flexible way. The method introduced here is an option that fulfills the need.