Drivers of coastal sea level and flooding along the East coast of the United States
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Coastal cities and communities are on the frontline as sea-level rise induced by climate change expands the oceans and re-draws the maps of the coastline. Despite the emerging threats of sea-level rise and flooding, the current water level observational networks and the modeling approaches for the U.S. East Coast are inadequate to resolve the combined effects of watershed loading, the spatiotemporal variations of the extreme water level, and the compound flooding at the scale of rivers, tributaries, creeks, and City’s block during hurricane events. These limitations pose challenges for understanding, predicting, and mitigating the regional and city-scale impacts of climate extremes and flooding on coastal communities. They also imply that coastal decision-makers and planners are not equipped with adequate tools to inform coastal protection and management strategies. The main goals of this thesis are to develop large-scale, three-dimensional, high-resolution coastal models to overcome the limitations of existing technologies and use them to diagnose the role of extreme water level drivers along the East Coast of the United States. Accordingly, in this thesis, I present a new modeling system that has been implemented to deliver a 3-day forecast system in Chatham County (GA). This system that has been operational since 2019 is currently being used by the Chatham Emergency Management Agency and the City of Savannah to design new emergency protocols and advance a city-wide resilience planning process. Using the developed model, I also conduct a series of hurricane hindcast and sensitivity experiments to examine the relative roles of extreme water level drivers during major coastal storms and quantify their contributions to the spatial and temporal patterns of extreme water levels. As a main finding of the study, I reveal the importance of relative peak timing between remote oceanic forcing (e.g., change in Gulf Stream, Ekman transport and coastally trapped waves) and local atmospheric forcing (e.g., wind and pressure forcing) on the U.S. southeast coast. Specifically, I find that the variability of the peak timing can control storm surges by increasing the peak level by up to 30 % for Hurricane Matthew (2016) and 50 % for Hurricane Dorian (2019). In the following study, I expand the numerical modeling capability and domain over the entire U.S. East Coast to examine the shelf-scale high water levels in a post-hurricane period. Numerical experiments reveal that oceanic adjustments to hurricane forcing determine the mean of the shelf-scale high water levels while atmospheric forcing controls the fluctuation of the abnormal water level along the coast. The abnormal water level can pose potential flood damage even after a hurricane event as the water level is twice as high as the sea-level rise in 100 years (≈34 cm) on the Georgia coast. The lessons learned from the studies provide new insights into the multiple drivers of abnormal water levels, both during and after hurricane events, and fill critical knowledge gaps and data needs necessary to inform best practices to scientists, engineers and policymakers.