Storm surge events are a key driver of widespread flooding, particularly when combined with astronomical tides superimposed on mean sea level (MSL). Coastal storms exhibit seasonal variability which translates into a seasonal cycle in storm surge activity. It has been demonstrated before that the seasonal cycle shows significant interannual variations including possible long-term trends. Understanding these changes is critical as both changes in the amplitude and the phase of their seasonal cycle may alter the compound flood potential. Changes in the seasonal storm surge cycle and the compounding with the MSL cycle remain largely unknown. A comprehensive analysis of the storm surge seasonal cycle and its links to the MSL seasonal cycle is performed using tide gauge observations from a quasi-global dataset. Harmonic analysis is used to assess the mean and changing storm surge seasonal cycles over time. Extreme value analysis is applied to explore the effect of seasonal changes on storm surge return levels. We also quantify the influence of large-scale climate modes, and we compare how the seasonalities of storm surge and MSL have changed relative to each other. The peak of the storm surge cycle typically occurs during winter for tide gauges outside of tropical cyclone regions, where there is greater variability in the phase of the storm surge cycle. The timing of the peak varied by more than a month at 21% of the tide gauges analyzed. The MSL and storm surge cycles peaked at least once within 30 days at 74% of tide gauges.

Changes in the seasonal sea level cycle (SSLC) can modulate the flooding risk along coastlines. Here, we use harmonic analysis to quantify changes in the amplitude and phase of the annual component of the sea level cycle at 663 tide gauge locations along the global coastline where long records are available. We identify coastal hotspots by applying clustering methods revealing coherent regions with similar patterns of variability in the annual sea level cycle (ASLC). Results show that for most tide gauges the annual amplitude reached its maximum after 1970 and its peak typically occurs during the fall season of the respective hemisphere. Many tide gauges exhibit non-stationarity in the annual cycle in terms of amplitude and/or phase. For example, at 125 tide gauges we find significant trends in the amplitude (either increasing or decreasing) while several sites (36 in total), mostly in the Mediterranean and around Pacific islands, experienced phase changes leading to shifts in the timing of the peak of the annual cycle by more than a month. Our results highlight the importance of accounting for potential non-stationarity in seasonal mean sea level (MSL) cycles along coastlines.

High-tide flooding—minor, disruptive coastal inundation—is expected to become more frequent as sea levels rise. However, quantifying just how quickly high-tide flooding rates are changing, and whether some places experience more high-tide flooding than others, is challenging. To quantify trends in high-tide flooding from tide-gauge observations, flood thresholds—elevations above which flooding begins—must be specified. Past studies of high-tide flooding in the United States have used different datasets and approaches for specifying flood thresholds, only some of which directly relate to coastal impacts, which has lead to sometimes conflicting and ambiguous results. Here we present a novel method for quantifying, with uncertainty, high-tide flooding thresholds along the United States coast based on sparsely available impacts-based flood thresholds. We use those newly modeled thresholds to make an updated assessment of changes in high-tide flooding across the United States over the past few decades. From 1990–2000 to 2010–2020, high-tide flooding rates almost certainly (probability $P>99\%$) increased along the United States East Coast, Gulf Coast, California, and Pacific Islands, while they very likely ($P=93\%$) decreased along Alaska during that time; significant changes in high-tide flooding rates between the two decades were not detected in Oregon, Washington, and the Caribbean. Averaging spatially, we find that high-tide flooding rates probably ($P=85\%$) more than doubled nationally between 1990–2000 and 2010–2020. Our approach lays a foundation for future studies to more accurately model high-tide flood thresholds and trends along the global coastline.

Recent advances in modeling 21st-century sea level rise (SLR) and its associated societal outcomes have demonstrated that the spatial pattern of SLR combined with highly variable population density along global coastlines exert a strong control on its impacts. Here, we extend this research by examining differential costs arising from two sources of SLR that exhibit distinct spatial ”fingerprints” - mass flux from the Antarctic (AIS) and Greenland (GrIS) Ice Sheets. To do this, we employ the DSCIM-Coastal data and modeling platform to quantify flood extents and population exposure to inundation from sea level changes associated with an ensemble of Ice Sheet Model Intercomparison Product projections between 2015 and 2100 CE. We also introduce the Social Cost of Ice Sheet Melt (SC-ISM) metric and calculate this for both AIS and GrIS melt scenarios. Due to the distinct sea level fingerprints of the two ice sheets, we find that mass flux from the AIS floods a larger area and would inundate a greater (present-day) population than an equivalent mass flux from the GrIS and yields a substantially higher SC-ISM. Across a suite of future climate scenarios, the SC-ISM associated with AIS melt is ~30% higher than that of GrIS, driven largely by differential SLR rates along the North Atlantic coastline. However, for either source, SC-ISM normalized by local GDP shows strongly disproportionate impacts, with low-income regions experiencing a significantly greater economic burden than high-income regions.

We investigate trends in the magnitude and frequency of extreme storm surge events at 320 tide gauges across the globe from 1930, 1950, and 1980 to present. We use two centennial and three satellite-era daily storm surge time series from the Global Storm Surge Reconstructions (GSSR) database. Before calculating trends, we perform change point analysis to identify and remove data where inhomogeneities in atmospheric reanalysis products could lead to spurious trends in the storm surge data. Even after removing unreliable data, the database still extends existing storm surge records by several decades for most of the tide gauges. Storm surges derived from the centennial 20CR and ERA-20C atmospheric reanalyses show consistently significant positive trends along the southern North Sea and the Kattegat Bay regions during the periods from 1930 and 1950 onwards and negative trends since 1980 period. When comparing all five storm surge reconstructions and observations for the overlapping 1980-2010 period we find overall good agreement, but distinct differences along some coastlines, such as the Bay of Biscay and Australia. We also assess changes in the frequency of extreme surges and find that the number of annual exceedances above the 95th percentile has increased since 1930 and 1950 in several regions such as Western Europe, Kattegat Bay, and the US East Coast.