Tidally-driven interannual variation in extreme sea level probabilities in the Gulf of Maine

Hannah Elizabeth Baranes, University of Massachusetts Amherst, Geosciences, Amherst, United States, Jonathan D Woodruff, University of Massachusetts Amherst, Amherst, MA, United States, Stefan A Talke, California State Polytechnic University, Civil and Environmental Engineering, San Luis Obispo, California, United States, Robert E Kopp, Rutgers University New Brunswick, Institute of Earth, Ocean, and Atmospheric Sciences, New Brunswick, NJ, United States, Richard Ray, NASA Goddard Space Flight Center, Geodesy & Geophysics Lab, Greenbelt, United States and Robert M Deconto, University of Massachusetts Amherst, Department of Geosciences, Amherst, United States
Abstract:
Extreme sea level (ESL) hazard is often quantified by annual exceedance probability (AEP), or the percent chance of an ESL occurring in a given year. When there is significant interannual variation in the magnitude of mean sea level, tides, or storm surge (the three components that comprise ESLs), statistical methods for assessing ESL hazard must account for these non-stationarities to reliably support decision-making around coastal risk management and infrastructure development. Tidal magnitude strongly modulates the severity of flooding during storms in meso-to-macrotidal regions, and interannual variation in tidal magnitude causing periods of enhanced flood risk is a well-known phenomenon; however, to date, ESL statistical methods have not accounted for tidal non-stationarity. Here, we present a new quasi-nonstationary joint probability method for calculating ESL probabilities in Gulf of Maine, where large tides, ranging from ~3 meters in Boston to ~16 meters in the Bay of Fundy, are a primary control on extreme flooding. Within the Gulf, the annual 90th percentile of daily predicted higher high water (a measure of extreme high tides) both varies decadally with the 18.6-year nodal cycle, and has been increasing (on top of sea level rise) over the past century. Our quasi-nonstationary joint probability method provides separate statistical treatment of tides and surge, assumes stationary storm characteristics, and yields annual flood frequency distributions using each year’s predicted high waters. We find that over each 18.6-year nodal cycle, the 100-year storm tide rises and falls by 13 cm in Eastport, 4 cm in Portland, and 6 cm in Boston. In contrast, sea level rise over the past century has, on average, increased the 100-year storm tide by less than 3 cm every 9.3 years (i.e. half the nodal period) in the Gulf; thus, tidal effects have so far exceeded amplification of the 100-year storm tide by sea level rise. This tidal forcing also translates to dramatic year-to-year variability in the AEP of a given storm tide, which is a key consideration for communicating with the public following major flood events. For example, the AEP of Boston’s event of record, the Blizzard of 1978, was 0.6% in 1978, but has varied between 0.16% (a 1-in-600-year event) and 0.6% (a 1-in-150-year event) over the past century.