A database of global storm surge reconstructions

Abstract

Storm surges are among the deadliest coastal hazards and understanding how they have been affected by climate change and variability in the past is crucial to prepare for the future. However, tide gauge records are often too short to assess trends and perform robust statistical analyses. Here we use a data-driven modeling framework to simulate daily maximum surge values at 882 tide gauge locations across the globe. We use five different atmospheric reanalysis products for the storm surge reconstruction, the longest one going as far back as 1836. The data that we generate can be used, for example, for long-term trend analyses of the storm surge climate and identification of regions where changes in the intensity and/or frequency of storms surges have occurred in the past. It also provides a better basis for robust extreme value analysis, especially for tide gauges where observational records are short. The data are made available for public use through an interactive web-map as well as a public data repository.

Long-term trends in storm surge climate derived from an ensemble of global surge reconstructions

“…Based on the model validation results from Tadesse and Wahl 31 and after applying a set of selection criteria in terms of model performance (see “ Methods ”), 310 and 320 tide gauges are selected with G-20CR and G-E20C surge reconstructions, respectively. These tide gauges adequately cover the Northern Hemisphere coastlines and also include several locations in the Southern Hemisphere, while the tropics are under-sampled due to model inaccuracies 47 .…”

“…Figure 2 exemplarily shows the results from the Bayesian change point analysis for Astoria (US) (Fig. 2 e,f), along with the annual variability of the three predictors used in Tadesse and Wahl 31 (Fig. 2 a–c), as well as the annual variability in the surge reconstructions and the observed surge (Fig.…”

“…On average, and after removing suspicious data, GSSR 31 has extended the average storm surge data lengths at the 310 (G-20CR) and 320 (G-E20C) sites from 30 to 111 years (G-20CR) and 16 to 69 years (G-E20C), with significant spatial variability. We find that G-20CR provides at least 100 years of additional surge data (on top of available observed surge information) for 40% of the tide gauges and at least 50 additional years for 68% of the tide gauges; G-E20C provides at least 100 additional years of surge data for 4% of the tide gauges and at least 50 additional years for 46% of the tide gauges (Fig.…”

Thresholds in Road Network Functioning on US Atlantic and Gulf Barrier Islands

“…As empirical and modeled data for constructing annual exceedance probabilities for extreme high‐water levels continue to improve (Muis et al., 2020; Tadesse & Wahl, 2021; Woodworth et al., 2016), so too will analyses of infrastructural robustness to flooding at specific localities—which might involve recalculating probabilities of infrastructural failure under non‐stationary forcing (Cheng & AghaKouchak, 2014) and/or including the mitigating or exacerbating effects of coastal landscape morphodynamics (Anarde et al., 2018; Darestani et al., 2021; Velasquez‐Montoya et al., 2021). Nevertheless, gaining insight into the probability distribution—and non‐stationarity—of multi‐source flood magnitude and frequency will also require a proliferation of accessible, comprehensive, multi‐layer datasets (Habel et al., 2020).…”

Exploring deep learning capabilities for surge predictions in coastal areas

“…Surge levels superimposed on high tides can exceed land thresholds and contribute to nuisance flooding or extreme impacts when caused by tropical or extratropical cyclones. At the global scale, studies have used hydrodynamic modelling 8 or data-driven approaches to reconstruct surge time series 9 – 12 . The advantage of hydrodynamic models is that with adequate model resolution and meteorological forcing, they can resolve physical coastal processes and their interactions.…”