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Hurricane Florence made landfall over the Carolinas 14 September 2018, bringing over 30 inches of rainfall. What remains understudied is the possible storm re‐intensification by wet and warm antecedent soil moisture (ASM), known as the Brown Ocean Effect (BOE). This study investigates this effect with two approaches: (a) two satellite‐based soil moisture (SM) data and (b) model simulation. The averaged Cyclone Global Navigation System and Soil Moisture Active Passive SM enables examination of land‐atmosphere interaction at a sub‐daily scale. Both observations and simulation results manifest positive feedback between ASM and rainfall intensity, with 3 days prior to landfall being the typical antecedent time scale. Wet (dry) ASM lead to intense (light) and concentrated (widespread) rains. We also found that soil temperature can modulate the BOE. This study aims to advance our understanding of land‐atmosphere feedback and calls to acquire accurate antecedent land states to enhance forecast skills. Plain Language Summary: Antecedent wet and warm soil conditions can maintain or re‐intensify storms via vertical mixing of water vapor, a phenomenon called the Brown Ocean Effect (BOE). Previous studies investigating the existence of BOE have considered model simulations by perturbing antecedent soil moisture. Given the uncertainties in weather models, it is important to cross‐validate the soil‐rainfall feedback by both observations and simulations. It is also critical to understand the time scale of such feedback. The growing number of remote sensing soil moisture (SM) and weather radar rainfall products at various resolutions and spatial‐temporal sampling offer unprecedented opportunities to examine this effect. Our results show consistent positive soil‐rainfall feedback from both observations and simulations. Wet antecedent soils promote intense yet concentrated rains, while dry antecedent soils cause light and widespread rains. Meanwhile, soil temperature was also found to play an important role in mediating the feedback, with colder soils even leading to a negative correlation between wet antecedent soils and extreme rainfall rates. We advocate accurate representation of antecedent land surface states combined with assimilation of remote sensing SM products into models to enhance tropical cyclone forecasts. Key Points: We hypothesize the wet antecedent soil moisture re‐intensified Hurricane FlorenceWe found that Hurricane Florence was re‐intensified by wet antecedent soils, leading to intense and concentrated rainfallWe found that cold antecedent soils impair the Brown Ocean effect in Hurricane Florence [ABSTRACT FROM AUTHOR]

Abstract Hurricane Florence made landfall over the Carolinas 14 September 2018, bringing over 30 inches of rainfall. What remains understudied is the possible storm re‐intensification by wet and warm antecedent soil moisture (ASM), known as the Brown Ocean Effect (BOE). This study investigates this effect with two approaches: (a) two satellite‐based soil moisture (SM) data and (b) model simulation. The averaged Cyclone Global Navigation System and Soil Moisture Active Passive SM enables examination of land‐atmosphere interaction at a sub‐daily scale. Both observations and simulation results manifest positive feedback between ASM and rainfall intensity, with 3 days prior to landfall being the typical antecedent time scale. Wet (dry) ASM lead to intense (light) and concentrated (widespread) rains. We also found that soil temperature can modulate the BOE. This study aims to advance our understanding of land‐atmosphere feedback and calls to acquire accurate antecedent land states to enhance forecast skills.