Impact of SST and Surface Waves on Hurricane Florence (2018): A Coupled Modeling Investigation

Hurricane Florence (2018) devastated the coastal communities of the Carolinas through heavy rainfall that resulted in massive flooding. 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. 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. 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 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. 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. Further analysis into surface roughness parameterizations added to the atmospheric model revealed differences in the spatial distribution and magnitude of the largest roughness lengths. 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. Our experiments highlight significant differences in how air-sea processes impact hurricane modeling. The storm characteristics of track, intensity, strength, and precipitation at landfall are crucial to predictability and forecasting of future landfalling hurricanes. SIGNIFICANCE STATEMENT Hurricane Florence (2018) was a major hurricane that weakened and eventually remained stationary after landfall over the coastal Carolinas, leading to devastating flooding. Atmospheric-only numerical models neglect the impact of sea surface temperature (SST) and surface waves changing beneath these storms and tend to overpredict the intensity in some cases. We conducted experiments that include atmosphere-ocean interaction by tying in realistic coupled SST and surface waves beneath the storm. We employed a novel approach of including surface wave information to the atmospheric model. While examining the underlying features, we found different approaches resulted in drastic differences in the result, including a 27.2% difference in precipitation among our experiments. We found improvement in the numerical models with more advanced coupling to the ocean environment, but further improvement could be achieved through data assimilation.