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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 Cloud radiative feedback impacts early tropical cyclone (TC) intensification, but limitations in existing diagnostic frameworks make them unsuitable for studying asymmetric or transient radiative heating. We propose a linear Variational Encoder‐Decoder (VED) framework to learn the hidden relationship between radiative anomalies and the surface intensification of realistic simulated TCs. The uncertainty of the VED model identifies periods when radiation has more importance for intensification. A close examination of the radiative pattern extracted by the VED model from a 20‐member ensemble simulation on Typhoon Haiyan shows that longwave forcing from inner core deep convection and shallow clouds downshear contribute to intensification, with deep convection in the downshear‐left quadrant having the most impact overall on the intensification of that TC. Our work demonstrates that machine learning can aid the discovery of thermodynamic‐kinematic relationships without relying on axisymmetric or deterministic assumptions, paving the way for the objective discovery of processes leading to TC intensification in realistic conditions. 

Abstract Studies have implicated the importance of longwave (LW) cloud‐radiative forcing (CRF) in facilitating or accelerating the upscale development of tropical moist convection. While different cloud types are known to have distinct CRF, their individual roles in driving upscale development through radiative feedback is largely unexplored. Here we examine the hypothesis that CRF from stratiform regions has the greatest positive effect on upscale development of tropical convection. We do so through numerical model experiments using convection‐permitting ensemble WRF (Weather Research and Forecasting) simulations of tropical cyclone formation. Using a new column‐by‐column cloud classification scheme, we identify the contributions of five cloud types (shallow, congestus, and deep convective; and stratiform and anvil clouds). We examine their relative impacts on longwave radiation moist static energy (MSE) variance feedback and test the removal of this forcing in additional mechanism‐denial simulations. Our results indicate the importance stratiform and anvil regions in accelerating convective upscale development.