Predicting Zonal-Mean Climate Change with a Moist Energy Balance Model

How will the pole-to-equator temperature gradient, or large-scale patterns of precipitation, change under global warming? Answering such questions typically involves numerical simulations with comprehensive general circulation models (GCMs) that represent the full complexities of climate forcing, radiative feedbacks, and atmosphere and ocean dynamics. Yet, our understanding of these predictions hinges on our ability to explain them through the lens of simple models and physical theories.

Here we present evidence that zonal-mean climate and its changes can be understood in terms of a moist energy balance model (MEBM) that represents atmospheric heat transport as a simple diffusion of latent and sensible heat – as a down-gradient transport of moist static energy, with a diffusivity coefficient that is nearly constant with latitude as supported by comprehensive models and atmospheric reanalyses. As an example of the power of this framework, we show that, given patterns of local radiative feedbacks and climate forcing, the MEBM accurately predicts the evolution of zonal-mean temperature, atmospheric heat transport and precipitation as simulated by the ensemble of CMIP5 GCMs. It further provides insights into (i) the mechanisms of polar amplification and (ii) how uncertainty in the spatial pattern of radiative feedbacks projects onto the uncertainty in the pattern of climate response.

These results suggest that, despite all of its dynamical complexity, the atmosphere essentially responds to energy imbalances by simply diffusing latent and sensible heat down-gradient. This principle appears to explain much of zonal-mean climate and its changes under global warming.