Ocean heat content (OHC Leipper and Volgenau 1972) decreased by more than half from the open ocean to the shelf, from 56 to 25 kJ cm −2 ( Stewart and Berg 2019). While the sea surface temperature (SST) across the shelf remained around 29.5☌, the depth of the mixed layer decreased. This weakening was attributed to two factors: an eyewall replacement cycle, and a reduction in the depth of the ocean mixed layer as the storm reached the eastern U.S. The storm reached peak intensity as a category-4 hurricane just 2 days prior, but underwent significant weakening before landfall. Hurricane Florence was a long-track, Cape Verde TC that persisted in the Atlantic Ocean for 2.5 weeks before making landfall on the southeastern coast of North Carolina at 1115 UTC 14 September 2018. dollars) in damage ( Stewart and Berg 2019), through several experiments using numerical models in increasing complexity of uncoupled and coupled states resolving atmosphere, ocean, and wave conditions. In this work, we examine Hurricane Florence (2018), which led to $24 billion (U.S. As people continue to migrate to the coast, damage caused by these intense storms will continue to increase, due to more intense and more frequent events ( Emanuel et al. Within the United States, where approximately 40% of the population lives near a coast, TCs are one of the costliest natural disasters and account for significant damage to infrastructure, injury, and loss of life ( Emanuel 2005). TCs have complex interactions with the ocean environment before, during, and after landfall. Tropical cyclones (TCs) are large-scale, discrete events that can have drastic impacts on coastal communities. The storm characteristics of track, intensity, strength, and precipitation at landfall are crucial to predictability and forecasting of future landfalling hurricanes. Our experiments highlight significant differences in how air–sea processes impact hurricane modeling. Adding ocean and wave features to the model further modified the fluxes due to more realistic cooling beneath the storm, which in turn modified the precipitation field. Further analysis into surface roughness parameterizations added to the atmospheric model revealed differences in the spatial distribution and magnitude of the largest roughness lengths. We found differences in the storm’s intensity and strength, with the best correlation coefficient of intensity ( r = 0.89) and strength ( r = 0.95) coming from the fully coupled simulations. We examined these experiments by comparing track, intensity, strength, SST, storm structure, wave height, surface roughness, heat fluxes, and precipitation in order to determine the impacts of resolving ocean conditions with varying degrees of coupling. In addition to experiments using a fully coupled atmosphere–ocean–wave model, we introduced the capability of the atmospheric model to modulate wind stress and surface fluxes by ocean waves through data from an uncoupled wave model. We conducted a series of numerical modeling experiments in coupled and uncoupled configurations to examine the impact of sea surface temperature (SST) and ocean waves on storm characteristics. Florence was characterized by an abrupt reduction in intensity (Saffir–Simpson category 4 to category 1) just prior to landfall and synoptic-scale interactions that stalled the storm over the Carolinas for several days. Hurricane Florence (2018) devastated the coastal communities of the Carolinas through heavy rainfall that resulted in massive flooding.
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