Scientists and engineers have observed for some time that tidal amplitudes at many locations are shifting considerably due to nonastronomical factors. Here we review comprehensively these important changes in tidal properties, many of which remain poorly understood. Over long geological time scales, tectonic processes drive variations in basin size, depth, and shape and hence the resonant properties of ocean basins. On shorter geological time scales, changes in oceanic tidal properties are dominated by variations in water depth. A growing number of studies have identified widespread, sometimes regionally coherent, positive, and negative trends in tidal constituents and levels during the 19th, 20th, and early 21st centuries. Determining the causes is challenging because a tide measured at a coastal gauge integrates the effects of local, regional, and oceanic changes. Here, we highlight six main factors that can cause changes in measured tidal statistics on local scales and a further eight possible regional/global driving mechanisms. Since only a few studies have combined observations and models, or modeled at a temporal/spatial resolution capable of resolving both ultralocal and large‐scale global changes, the individual contributions from local and regional mechanisms remain uncertain. Nonetheless, modeling studies project that sea level rise and climate change will continue to alter tides over the next several centuries, with regionally coherent modes of change caused by alterations to coastal morphology and ice sheet extent. Hence, a better understanding of the causes and consequences of tidal variations is needed to help assess the implications for coastal defense, risk assessment, and ecological change.

This paper describes a major update to the quasi‐global, higher‐frequency sea‐level dataset known as GESLA (Global Extreme Sea Level Analysis). Versions 1 (released 2009) and 2 (released 2016) of the dataset have been used in many published studies, across a wide range of oceanographic and coastal engineering‐related investigations concerned with evaluating tides, storm surges, extreme sea levels, and other related processes. The third version of the dataset (released 2021), presented here, contains double the number of years of data, and nearly four times the number of records, compared to Version 2. The dataset consists of records obtained from multiple sources around the world. This paper describes the assembly of the dataset, its processing, and its format, and outlines potential future improvements.

In this paper we analyse the spatial footprint and temporal clustering of extreme sea level and skew surge events around the UK coast over the last 100 years (1915–2014). The vast majority of the extreme sea level events are generated by moderate, rather than extreme skew surges, combined with spring astronomical high tides. We distinguish four broad categories of spatial footprints of events and the distinct storm tracks that generated them. There have been rare events when extreme levels have occurred along two unconnected coastal regions during the same storm. The events that occur in closest succession (<4 days) typically impact different stretches of coastline. The spring/neap tidal cycle prevents successive extreme sea level events from happening within 4–8 days. Finally, the 2013/14 season was highly unusual in the context of the last 100 years from an extreme sea level perspective.

Sea level rise (SLR) is a long‐lasting consequence of climate change because global anthropogenic warming takes centuries to millennia to equilibrate for the deep ocean and ice sheets. SLR projections based on climate models support policy analysis, risk assessment and adaptation planning today, despite their large uncertainties. The central range of the SLR distribution is estimated by process‐based models. However, risk‐averse practitioners often require information about plausible future conditions that lie in the tails of the SLR distribution, which are poorly defined by existing models. Here, a community effort combining scientists and practitioners builds on a framework of discussing physical evidence to quantify high‐end global SLR for practitioners. The approach is complementary to the IPCC AR6 report and provides further physically plausible high‐end scenarios. High‐end estimates for the different SLR components are developed for two climate scenarios at two timescales. For global warming of +2°C in 2100 (RCP2.6/SSP1‐2.6) relative to pre‐industrial values our high‐end global SLR estimates are up to 0.9 m in 2100 and 2.5 m in 2300. Similarly, for a (RCP8.5/SSP5‐8.5), we estimate up to 1.6 m in 2100 and up to 10.4 m in 2300. The large and growing differences between the scenarios beyond 2100 emphasize the long‐term benefits of mitigation. However, even a modest 2°C warming may cause multi‐meter SLR on centennial time scales with profound consequences for coastal areas. Earlier high‐end assessments focused on instability mechanisms in Antarctica, while here we emphasize the importance of the timing of ice shelf collapse around Antarctica. This is highly uncertain due to low understanding of the driving processes. Hence both process understanding and emission scenario control high‐end SLR.

There is considerable uncertainty surrounding future changes in tropical cyclone (TC) frequency and intensity, particularly at local scales. This uncertainty complicates risk assessments and implementation of risk mitigation strategies. We present a novel approach to overcome this problem, using the statistical model STORM to generate 10,000 years of synthetic TCs under past (1980–2017) and future climate (SSP585; 2015–2050) conditions from an ensemble of four high-resolution climate models. We then derive high-resolution (10-km) wind speed return period maps up to 1000 years to assess local-scale changes in wind speed probabilities. Our results indicate that the probability of intense TCs, on average, more than doubles in all regions except for the Bay of Bengal and the Gulf of Mexico. Our unique and innovative methodology enables globally consistent comparison of TC risk in both time and space and can be easily adapted to accommodate alternative climate scenarios and time periods.

There is observational evidence that global sea level is rising and there is concern that the rate of rise will increase, significantly threatening coastal communities. However, considerable debate remains as to whether the rate of sea level rise is currently increasing and, if so, by how much. Here we provide new insights into sea level accelerations by applying the main methods that have been used previously to search for accelerations in historical data, to identify the timings (with uncertainties) at which accelerations might first be recognized in a statistically significant manner (if not apparent already) in sea level records that we have artificially extended to 2100. We find that the most important approach to earliest possible detection of a significant sea level acceleration lies in improved understanding (and subsequent removal) of interannual to multidecadal variability in sea level records.