Improving Hurricane Intensity Forecasts through Vorticity-based Diffusion Adjustments in the Planetary Boundary Layer

Accurately forecasting hurricane wind intensity remains a significant challenge in geophysical fluid dynamics, in part due to the limitations of Planetary Boundary Layer (PBL) parameterizations within numerical weather prediction (NWP) models. These schemes often neglect turbulence suppression due to strong rotational effects, which are significant within the hurricane boundary layer (HBL). Hence, the existing turbulence schemes in NWPS typically produce excessive dissipation, leading to underestimated intensity in real hurricane forecasts. Recent, albeit limited, studies on this topic showed that reducing vertical diffusion can improve intensity forecasts by over 20% in hurricane simulations. However, these studies applied simplified fixed-value reductions to diffusion, ignoring the variability of local rotational features of hurricanes. To address this gap, we developed a vorticity-adjusted PBL scheme that dynamically adjusts vertical diffusion based on local relative vorticity. Using multiple real hurricane cases simulated in Weather Research and Forecasting (WRF), we found that this method substantially improves forecasts of wind intensity (~36% compared to the default scheme), while better capturing hurricane vortex strength and structure (~59%). By introducing rotation-based turbulence adjustments, our new scheme provides a novel physics-oriented, robust framework that could be used in operational models to improve hurricane forecasts.