Research
Our research group focuses on several topics of tropical cyclones that are connected through boundary layer processes. We pursue novel approaches to understand boundary-layer turbulence characteristics in high-wind conditions and to improve boundary-layer parameterizations in numerical prediction models, which further contribute to a better understanding of boundary-layer dynamics/thermodynamics in tropical cyclone intensification under vertical wind shear, tornadogenesis, and boundary-layer roll formation.
The chaotic, swirling winds above the ocean as a tropical cyclone develops play a key role in how strong a storm might be when it reaches land; however, our understanding toward the turbulence characteristics in high-wind conditions is limited, mostly due to very scarce in-situ observations under such extreme conditions. To address this issue, this project uses turbulence-resolving large-eddy simulations to develop better boundary layer parameterizations for hurricane forecasts.
Predicting the behaviors of early-stage tropical cyclones under moderate-to-high vertical wind shear remains challenging around the world. It is challenging, sometimes, to predict whether a storm is going to rapidly intensify or not with the existence of shear. This project aims to understand the interplay between boundary-layer and vortex-scale processes that contribute to those "surprising" (rapid) intensification events.
Observations of TC landfalls (TBD)
In-situ field campaign for hurricane landfalls. Instruments include several mobile platforms from UAH MAPNet, the NEXRAD network, and airborne Doppler radars. The goal is to collect crucial boundary-layer turbulence information for better PBL parameterizations over land, and to understand the formation of boundary layer rolls.
TC tornadoes (TBD)
Tropical cyclone tornadoes can cause devastating damages prior to and during TC landfalls [Image above gives an example of Hurricane Ian (2022)]. This project will investigate how boundary layer dynamics contribute to TC tornadogenesis by analyzing VORTEX-SE observations and high-resolution numerical modeling output.