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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.
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Identifying Three‐Dimensional Radiative Patterns Associated With Early Tropical Cyclone Intensification
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.
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- Award ID(s):
- 2331120
- PAR ID:
- 10559282
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Advances in Modeling Earth Systems
- Volume:
- 16
- Issue:
- 12
- ISSN:
- 1942-2466
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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