Understanding the links between climate feedbacks, variability and change using a two-layer energy balance model

Abstract

A simple, two-layer energy balance model (EBM) is used to investigate climate variability in Coupled Model Intercomparison Project Phase 5 (CMIP5) models and examine possible links between variability and climate sensitivity, and the roles of stochastic variability, radiative feedbacks and ocean mixing. The EBM represents global variability that, while somewhat stronger than the CMIP5 models, simulates reasonable ratios between shorter and longer timescales. Variability in the EBM to the range of parameters from the Global Climate Models is found to be particularly sensitive to stochastic variability, especially on interannual time-scales. Radiative feedbacks and ocean mixing parameters are also important, particularly for decadal timescales. A modest amount of the model-to-model spread in the variance of global temperature in the CMIP5 models is explained by the EBM. The EBM exhibits a stronger link between equilibrium climate sensitivity and the magnitude of the variability than it does for transient climate response, especially on decadal and longer timescales. The EBM results suggests that spread in stochastic forcing across the CMIP5 models is the single greatest factor degrading the correlation between variability and climate sensitivity, although model to model differences in radiative forcing and mixing into the deep ocean are also important. The findings suggest that from a theoretical point of view investigating constraints from variability may be a fruitful exercise. However, they also suggest that normalizing variability in general circulation models by stochastic forcing, uptake into the deep ocean and radiative forcing are all important first steps to reduce factors that will otherwise confound the correlations.