Seasonal Variability of Wave Contribution to the Mean and Extreme Sea Level in Coastal Waters of U.S. East and Gulf Coasts

Wind-generated waves influence coastal water levels, e.g., through wave setup, which can consequently influence the mean and extreme coastal water levels and coastal inundations. Generally, wave conditions show a strong variability in space and time, which can result in spatially and temporally varying levels of wave contribution to the water level. Therefore, understanding the seasonal variability of wave conditions and how they affect the total water level on a regional scale is important for managing the coasts, especially with the projected changes in the sea level and waves due to climate change. Hindcast and reanalysis datasets, such as the ERA5, provide temporally/spatially continuous sources of data for water level and wave climate studies. However, the resolution of these datasets, having a resolution of 30 km in the horizontal space, is insufficient to adequately resolve the complex physical processes in coastal waters, e.g., wave refraction and breaking and wave-current interactions, which influence both total water levels and wave characteristics. Therefore, a high-resolution regional-scale coupled circulation-wave model (ADCIRC+SWAN) is used to dynamically downscale the total water level and waves in the Western North Atlantic Ocean. Here, using a multi-year record from the ERA5 dataset, we dynamically reconstruct the total water level, wave, and wave contribution to the water level near the coast of Western North Atlantic Ocean. The ADCIRC+SWAN model is forced with hourly surface pressure and wind fields at its water surface boundary, and at its open boundary using hourly water level time series and direction-frequency wave spectrum data from the ERA5 reanalysis dataset. Model results are statistically analyzed to demonstrate the seasonal variability in the contribution of waves to the mean and extreme total water levels along the U.S. East and Gulf Coasts.