Tidally Driven Interannual Variation in Extreme Sea Level Frequencies in the Gulf of Maine

Abstract

Astronomical variations in tidal magnitude can strongly modulate the severity of coastal flooding on daily, monthly, and interannual timescales. Here we present a new quasi-nonstationary skew surge joint probability method (qn-SSJPM) that estimates interannual fluctuations in flood hazard caused by the 18.6-and quasi 4.4-year modulations of tides. We demonstrate that qn-SSJPM-derived storm tide frequency estimates are more precise and stable compared with the standard practice of fitting an extreme value distribution to measured storm tides, which is often biased by the largest few events within the observational period. Applying the qn-SSJPM in the Gulf of Maine, we find significant tidal forcing of winter storm season flood hazard by the 18.6-year nodal cycle, whereas 4.4-year modulations and a secular trend in tides are small compared to interannual variation and long-term trends in sea-level. The nodal cycle forces decadal oscillations in the 1% annual chance storm tide at an average rate of ±13.5 mm/year in Eastport, ME; ±4.0 mm/year in Portland, ME; and ±5.9 mm/year in Boston, MA. Currently (in 2020), nodal forcing is counteracting the sea-level rise-induced increase in flood hazard; however, in 2025, the nodal cycle will reach a minimum and then begin to accelerate flood hazard increase as it moves toward its maximum phase over the subsequent decade. Along the world's meso-to-macrotidal coastlines, it is therefore critical to consider both sea-level rise and tidal nonstationarity in planning for the transition to chronic flooding that will be driven by sea-level rise in many regions over the next century. Plain Language Summary Coastal management practices around flood risk often rely on estimates of the percent chance of a particular flood height occurring within a year. For example, U.S. flood insurance requires designating areas with a 100-year flood recurrence interval (the "100-year flood zone"). When storms hit regions with large tides, the height and timing of high tide often determine flood severity. Thus, the relationship between flood height and annual frequency can be altered by natural, daily-to-decadal cyclical variation in tide heights. Here we present a new method for calculating annually varying flood height-frequency relationships based on known tidal cycles. Applying the new method in the Gulf of Maine, we find an 18.6-year-long tidal cycle (the nodal cycle) has forced decadal variation in the 1% annual chance flood at a faster rate than the historical average rate of sea-level rise over the past century. Currently, nodal cycle forcing is counteracting the sea-level rise-induced increase in flood hazard; however, in 2025, the nodal cycle will reach a minimum in the Gulf and then begin to accelerate flood hazard as it moves toward its maximum over the subsequent decade. It is therefore critical to consider sea-level rise and tidal variation in medium-term flood hazard planning.

Predictable Changes in Extreme Sea Levels and Coastal Flood Risk Due To Long‐Term Tidal Cycles

“…The probability distribution function is obtained separately for extreme and non‐extreme skew surge events. In the present study, we define extreme events as those above the 0.997th percentile calculated at each station (similar thresholds were chosen in past studies: Arns et al., 2013; Baranes et al., 2020; Menéndez & Woodworth, 2010). We derive the empirical probability for the non‐extreme skew surge values through the Weibull formula: $$${\tilde{F}}_{SS}\left({x}_{i}\right)=\,\frac{i}{n+1}$$$ where $${x}_{i}$$ is the i th‐largest skew surge and n the total number of skew surges.…”

“…The probability distribution of sea levels ( 𝐴𝐴 𝐴𝐴𝑆𝑆𝑆𝑆 ) is calculated by computing the joint probability of the resulting skew surge distribution function and the ATNodal. Thus, we assume that the skew surge is independent of the 10.1029/2021JC018157 5 of 13 tidal cycle, which has been shown to be statistically supported at most (though not all) coastal locations in past studies (Baranes et al, 2020;Batstone et al, 2013;Santamaria-Aguilar & Vafeidis, 2018;Williams et al, 2016). The distribution function for the maximum sea level within a tidal cycle is,…”

“…As pointed out in Batstone et al (2013), if this dependence between high sea levels is not accounted for, the return period of extreme events could be overestimated. Following Ferro and Segers (2003) and Baranes et al (2020), the extremal index is the inverse of the mean cluster size:…”

“…Here, we assess the impact of long-term tidally induced variations in flood hazard by studying the 4.4 and 18.6year cycles in low-frequency extreme sea levels (100-year return period) using global tide gauge observations. To do so, we use the quasi-nonstationary skew surge joint-probability method (qn-SSJPM) of Baranes et al (2020). No studies, to our knowledge, have assessed how tidally induced modulations in extreme sea levels can change the potentially flooded area under given extreme sea level events, and thus, the consequences for inundation go unaddressed.…”

An Analysis of the 8.85- and 4.42-Year Cycles in the Gulf of Maine

“…Additionally, some nuclear power stations are built there, e.g., the Seabrook Station Nuclear Power Plant and the Point Lepreau Nuclear Generating Station. These major cities and hazardous infrastructures desire a more meticulous extreme sea-level risk assessment [18]. Moreover, the complex geography brings about one of the world's most dynamic environments [19] and the striking tidal resonance [20].…”