Multi-century geological data thins the tail of observationally based extreme sea level return period curves

Estimates of extreme sea-level return periods guide flood hazard mitigation. Return period estimates calculated from tide gauge records, which are relatively short (typically less than 100 years), can fail to capture the rarest and most potentially impactful extreme events. Here, we employ a two-dimensional Poisson point process model to fuse water-level data from tide gauges with data from multi-century geologic records of extreme overwash events. Experiments with synthetic data show that including geologic data reduces the uncertainty of 1% and 0.1% average annual chance water levels by about half, relative to using tide gauge data alone. Similar uncertainty reductions occur with two case studies of geologic data (Mattapoisett Marsh, Massachusetts and Cheesequake, New Jersey) and their neighboring tide gauges (Woods Hole, Massachusetts and the Battery, New York). The analysis also reveals non-stationarity at Cheesequake and The Battery, arising from either climatic changes or changes in the fidelity of the geological record, with substantially higher 1–10% average annual chance water levels since 1900 compared to prior centuries.