Understanding Earth’s climate, and how it may change due to the significant human impact on atmospheric composition, is a key scientific challenge of the 21st century. A large fraction of the uncertainty in predictions of climate change is related to how clouds and their impact on global energy balance may change with warming. Much of this problem in turn owes to our inability to resolve cloud-scale motions (~1km in size) in global climate models, which have grid boxes ~100 km in horizontal size. In this talk, Timothy Cronin '06 focuses on the idealized model configuration of radiative-convective equilibrium, and how it is helping us to understand cloud feedbacks on climate change.  

Radiative-convective equilibrium (RCE) is the statistical state of the atmosphere and surface that is set by the overall climatic energy balance between absorbed sunlight and emitted infrared radiation, assuming a horizontally uniform surface and horizontally uniform incident sunlight. Although RCE has been used as an idealization of the climate system for over 50 years, increasing computational power in the last two decades has allowed for simulation of RCE that explicitly represents the atmospheric motions that form clouds. One intriguing finding of these simulations is that under some conditions, clouds can undergo a transition from randomly dispersed to highly aggregated. Aggregation of clouds alters the atmospheric energy balance and dries the atmosphere overall, possibly affecting both cloud and water vapor feedbacks on warming. Cronin discuses simulations and analysis that assess how aggregation of clouds in RCE may affect climate sensitivity, as well as bottom-up theoretical work to understand aggregation of clouds as a linear instability of RCE.