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Abstract Cloud‐radiative forcing (CRF) has been suggested to accelerate tropical cyclone (TC) genesis, but we do not yet understand the role of convective‐scale processes in this cloud‐radiative feedback. We use a convection‐permitting ensemble Weather Research and Forecasting model framework to examine the hypothesis that CRF within stratiform cloud regions weakens downdrafts, allowing the environment to moisten more easily. We specifically compare our control simulations (CTL) of TC development to sensitivity tests that exclude cloud‐radiative forcing (NCRF) either everywhere or just within specific cloud types. Our experiment and analysis indicate that CRF leads to fewer and weaker stratiform downdrafts and greater humidity and moist entropy in the developing TC core, implying suppressed ventilation, with stratiform and anvil CRF dominating this effect. This cloud‐radiative feedback accelerates TC development by promoting faster intensification of both the mid‐level vortex and surface cyclone. 

Abstract The Radiative‐Convective Equilibrium Model Intercomparison Project (RCEMIP) is an intercomparison of multiple types of numerical models configured in radiative‐convective equilibrium (RCE). RCE is an idealization of the tropical atmosphere that has long been used to study basic questions in climate science. Here, we employ RCE to investigate the role that clouds and convective activity play in determining cloud feedbacks, climate sensitivity, the state of convective aggregation, and the equilibrium climate. RCEMIP is unique among intercomparisons in its inclusion of a wide range of model types, including atmospheric general circulation models (GCMs), single column models (SCMs), cloud‐resolving models (CRMs), large eddy simulations (LES), and global cloud‐resolving models (GCRMs). The first results are presented from the RCEMIP ensemble of more than 30 models. While there are large differences across the RCEMIP ensemble in the representation of mean profiles of temperature, humidity, and cloudiness, in a majority of models anvil clouds rise, warm, and decrease in area coverage in response to an increase in sea surface temperature (SST). Nearly all models exhibit self‐aggregation in large domains and agree that self‐aggregation acts to dry and warm the troposphere, reduce high cloudiness, and increase cooling to space. The degree of self‐aggregation exhibits no clear tendency with warming. There is a wide range of climate sensitivities, but models with parameterized convection tend to have lower climate sensitivities than models with explicit convection. In models with parameterized convection, aggregated simulations have lower climate sensitivities than unaggregated simulations.