The contribution of hurricane remote ocean forcing to storm surge along the Southeastern U.S. coast

The dynamics controlling the spatial and temporal expressions of storm surges over the coastal wetlands and communities of the South Atlantic Bight (SAB) is complex and not well understood. Leveraging a newly developed high-density hyper-local network of water level sensors in the North Georgia coast, we implement and test an unstructured numerical coastal ocean model (up to 10-m horizontal resolution) that can resolve and diagnose the storm-induced sea-level rise during the two Hurricanes Matthew (2016) and Dorian (2019) that have shore-parallel tracks. Using a set of model sensitivity analyses we decompose the drivers of the storm surge into a component that is associated with direct surface forcing by the hurricanes over the targeted area (e.g., local atmospheric wind and pressure condition in the nested model domain) and remote ocean forcing that is connected to hurricane-induced sea level anomalies and baroclinic effect through the open boundary of the model. For both hurricanes, we find that local surface atmospheric forcing leads to a uniform alongshore response in water level along the entire North Georgia coast with amplitudes that are proportional to how close to shore are the hurricane tracks (e.g., stronger in Matthew and weaker in Dorian). However, the alongshore structure and location of maximum storm surge are determined entirely by the arrival timing of ocean remote forcing. In the case of Matthew, the remote forcing arrives within 2 h of the direct passage of the hurricane over North Georgia and drives peak surges in the northern region of the domain (e.g., the City of Savannah and Tybee Island). In contrast, during Dorian, there is a 14-h difference between the remote and local forcing, and maximum storm surges are found in the southern region around Sapelo Island. We estimate that if local and remote forcing were to be simultaneous, the peak storm surge and the water level would be amplified by up to 30% for Matthew and 50% for Dorian. While this sensitivity analysis only includes two hurricanes and is focused on a case study around North Georgia, it is clear that predicting and understanding the regional expressions and timing of the hurricanes' coastal-wide remote ocean forcing in the SAB is important for estimating worst-case scenarios for coastal communities as they face emergency and management decisions.