Investigating the Brown Ocean Effect on the Re-intensification of Hurricane Florence through CYGNSS and SMAP Soil Moisture Observations Coupled with Numerical Weather Modeling

Hurricane Florence, which made landfall over the Carolinas in September 2018, led to unprecedented rainfall exceeding 30 inches. Despite its wide-reaching impacts, the hurricane's potential re-intensification through antecedently wet soil moisture (SM), a phenomenon known as the Brown Ocean Effect (BOE), remains insufficiently understood within the meteorological community. Utilizing a robust dual-methodology approach, this study serves to bridge this gap by: 1) leveraging state-of-the-art soil moisture observations from Cyclone Global Navigation System (CYGNSS) and Soil Moisture Active Passive (SMAP) satellites at a sub-daily scale, and 2) applying the numerical weather prediction. These SM datasets were temporally averaged to offer nuanced insights into sub-daily land-atmosphere interactions. Both observational and modeled data demonstrated a robust positive feedback mechanism between Antecedent SM (ASM) and storm intensity, characterized by a typical antecedent timescale of approximately 3 days prior to landfall. Soil temperature is found to be a modulator to such feedback, with cool soils indicating negative feedback and warm soils enhancing positive feedback. This research advances meteorological understanding of the intricate land-atmosphere feedback mechanisms that contribute to hurricane intensity modulation. The findings underscore the imperative need for high-resolution, accurate antecedent land surface data in enhancing the reliability and accuracy of hurricane forecasts.