Coastlines across the united states are already at risk of coastal inundation from episodic extreme events to longer-term sea level changes and rising seas coupled with more frequent and intense…

Coastlines across the united states are already at risk of coastal inundation from episodic extreme events to longer-term sea level changes and rising seas coupled with more frequent and intense storms due to the changing climate continue to increase that risk. Coastal flooding results from a combination of different water level components including mean sea level, tides, storm surges, sea level anomalies, and waves. Waves can contribute as much as 50% to extreme total water levels and often are responsible for spatially variable coastal change. However, analysis and derived products often focus on long-term modulations in tides and still water levels from tide gauges and their relation to flooding, often leaving out wave-induced water level as a contributor to flooding events. Our overall goal is to quantify the spatial variability of seasonal-to-interannual variation of total water levels and its components, still water level and wave runup, along the U.S. Gulf and east coasts. We will develop, for the first time, a total water level dataset using a new national oceanic and atmospheric administration (NOAA)/renaissance computer institute (RENCI) product over 40 years in length. We will calculate the percent contribution of water level components such as storm surge, tides, mean sea level, seasonality, sea level anomalies, and wave runup, to the total water level over seasonal to interannual time scales. This data set will have a spatial resolution that will capture the heterogeneity in local scales important for flood risk assessment and local decision making. We will meet our goal with scientific objectives that 1) identify the dominant water level components contributing to total water levels and how they spatially vary over seasonal-to-interannual time scales and 2) quantify the contributions of uncertainty to total water level estimation. The first objective compares regional patterns in seasonal and interannual total water levels computed using uniform or spatially-varying beach slope and deep-water or nearshore waves to evaluate whether site specific characteristics obscure regional patterns in total water levels. The second objective develops a method for including and characterizing the contribution of uncertainty from morphologic features, the reanalysis data, and a number of empirical wave runup formulations in the total water level predictions. Our proposal directly aligns with the targeted competition by focusing on improving the regional understanding of the contributions to total water levels over seasonal-to-interannual timescales. By determining the most important contributor to the total water level and quantifying the uncertainty in our predictions along the U.S. Gulf and east coasts, our results can be used to inform how future research objectives should be prioritized to improve predictions of total water levels on a national level. Our proposed research also has broader relevance to noaas long-term goals focused on developing a coastal inundation capability framework. Specifically, our work will lead NOAA towards including creating baseline climatologies of total water levels, identifying and quantifying modes of variability of total water level at gridded model output, and creating an integrated monthly-annual outlook of the probabilities of coastal inundation from total water levels.