Radiation, Clouds, and Self‐Aggregation in RCEMIP Simulations

The responses of tropical anvil cloud and low‐level cloud to a warming climate are among the largest sources of uncertainty in our estimates of climate sensitivity. However, most research on cloud feedbacks relies on either global climate models with parameterized convection, which do not explicitly represent small‐scale convective processes, or small‐domain models, which cannot directly simulate large‐scale circulations. We investigate how self‐aggregation, the spontaneous clumping of convection in idealized numerical models, depends on cloud‐radiative interactions with different cloud types, sea surface temperatures (SSTs), and stages of aggregation in simulations that form part of RCEMIP (the Radiative‐Convective Equilibrium Model Intercomparison Project). Analysis shows that the presence of anvil cloud, which tends to enhance aggregation when collocated with anomalously moist environments, is reduced in nearly all models when SSTs are increased, leading to a corresponding reduction in the aggregating influence of cloud‐longwave interactions. We also find that cloud‐longwave radiation interactions are stronger in the majority of General Circulation Models (GCMs), typically resulting in faster aggregation compared to Cloud‐system Resolving Models (CRMs). GCMs that have stronger cloud‐longwave interactions tend to aggregate faster, whereas the influence of circulations is the main factor affecting the aggregation rate in CRMs. Plain Language Summary The spatial organization of tropical rainstorms has major effects on weather and climate. This organization influences the duration and intensity of these convective storms, and alters the amount of radiation absorbed and emitted by the atmosphere. There is great uncertainty in the response of organization to a warming climate, and this results in one of the largest sources of uncertainty in climate predictions. Climate projections rely on either General Circulation Models (GCMs) that can represent the large‐scale motions, or smaller high‐resolution models that represent small‐scale features like cloud formations, but not the large motions. In this study, we compare convective organization in GCMs and Cloud‐system Resolving Models (CRMs) across a range of sea surface temperatures (SSTs). We find that the cloud‐radiation feedbacks that make the convective environment more favorable for further convection, and the non‐convective environment less favorable for convection, are stronger in GCMs than CRMs on average