Abstract
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.