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.

Analysis of multi-decadal tide records, satellite altimetry, and high-resolution oceanic reanalysis around the Hawaiian Ridge identifies correlations between offshore and onshore mean sea level (MSL), M2 tidal amplitudes, and ocean stratification; these are linked to Pacific decadal climate variability. Empirical orthogonal function analyses reveal strongly correlated quasi-decadal variability in onshore and offshore tides and MSL, and all three factors are highly correlated with regional density stratification. This decadal variability is highly correlated with multiple Pacific climate indices, suggesting that this climate variability influences internal tides via coupled ocean-atmosphere mechanisms. The surface expression of variations in the M2 internal tide yield correlated variability between MSL and M2 offshore and onshore. The M2 signals at all tide gauges have stronger relationships to MSL in the altimetry era (1992-2023) than their respective full records, and both factors show stronger connections to climate variations in recent years. The M2 signal at Hilo is most clearly connected to climate variability over its full record, stronger even than the MSL-climate connections at all tide gauges. The amplitudes of the climate-induced tidal variations are on are on the order of 10% on top of MSL variability and long-term steric sea level rise. This amplification may exacerbate the frequency of high-tide flooding (also known as “sunny-day flooding”) in harbors and other low-lying areas of Hawai’i, highlighting the need for dynamic coastal management strategies that integrate astronomical, non-astronomical, and climatic factors, in sea level projections.

Rates of sea-level rise are increasing across the global ocean. Since $\sim 2008$, sea-level acceleration is particularly pronounced along the US Gulf of Mexico coastline. Here we use model solutions and observational data to identify the physical mechanisms responsible for enhanced rates of recent coastal sea-level rise in this region. Specifically, we quantify the effect of offshore subsurface ocean warming on coastal sea-level rise and its relationship to regional hypsometry. Using the Estimating the Circulation and Climate of the Ocean (ECCO) Version 5 ocean state estimate, we establish that coastal sea-level changes are largely the result of changes in regional ocean mass, reflected in ocean bottom pressure, on interannual to decadal timescales. These coastal ocean bottom pressure changes reflect both net mass flux into and out of the Gulf, as well as internal mass redistribution within the Gulf, which can be understood as an isostatic ocean response to subsurface offshore warming. We test the relationships among coastal sea-level, ocean bottom pressure, and subsurface ocean warming predicted by the model using data from satellite gravimetry, satellite altimetery, tide gauges, and Argo floats. Our estimates of mass redistribution explain a significant fraction of coastal sea-level trends observed by tide gauges. For instance, at St. Petersburg, Florida, this mass redistribution accounts for $>$ 50\% of the coastal sea-level trend observed over the 2008-2017 decade. This study elucidates a physical mechanism whereby coastal sea-level responds to open-ocean subsurface warming and motivates future studies of this linkage in other regions.

Atmospheric rivers (ARs) effect inland hydrological impacts related to extreme precipitation. However, little is known about the possible coastal hazards associated with these events. Here we elucidate high-tide floods (HTFs) and storm surges during ARs on the US West Coast during 1980—2016. HTFs and landfalling ARs co-occur more often than expected from random chance. Between 10%—63% of HTFs coincide with landfalling ARs, depending on location. However, only 2%—15% of ARs coincide with HTFs, suggesting that ARs typically must co-occur with anomalously high tides or mean sea levels to cause HTFs. Storm surges during ARs are interpretable in terms of local wind, pressure, and precipitation forcing: meridional wind and barometric pressure are the primary drivers of storm surge, but precipitation can also make secondary contributions. This study highlights the relevance of ARs to coastal impacts, clarifies the drivers of storm surge during ARs, and identifies future research directions.

The Hawaiian Islands experienced record-high sea levels during 2017, which caused nuisance flooding in vulnerable coastal communities and exacerbate beach erosion, especially when positive sea level anomalies coincided with high tides. To build toward solutions for mitigating inundation risk, the predictability of daily-averaged sea level anomalies is investigated. Background sea level around the Hawaiian Islands was elevated during most of 2017 due to an oceanic Rossby-type planetary wave, which propagated slowly westward across the tropical North Pacific over the course of a year. The investigation focused on leveraging observed westward propagation that sea level anomalies exhibit over a range of timescales to make subseasonal predictions. Daily near-real-time gridded altimetry (CMEMS/AVISO) was used to specify upstream sea level at each site with propagation speeds based on mode-one baroclinic Rossby wave speeds. The skill of the predictions exceeds persistence at most locations around the archipelago out to a month or more lead time, but the skill is highly dependent on location even over the short distances spanned by the Hawaiian Ridge. Here, hindcast results are presented that establish where skillful subseasonal predictions can be made in Hawaii, as well as the barriers to predictability in locations where they cannot. These results inform the oceanographic and modelling communities about what processes need to be resolved in order to provide island communities with useful short-term sea level forecasts as the frequency of flooding events increases.