Search

The temporal clustering of storms presents consecutive storm surge and wave hazards that can lead to amplified flood and erosional damages; thus, clustering is important for coastal stakeholders to consider. We analyse the prevalence of storm clustering around the UK coastline by examining the temporal and spatial characteristics of storm surge, wave height, and high still sea level exceedances at the 1 in 1- and 5-year return levels. First, at the interannual timescale, we show that there are periods of high/low exceedance counts on national and regional scales. Elevated annual counts of exceedances with smaller magnitudes can occur without a respective signal of higher-magnitude exceedances. Secondly, at the intra-annual timescale, we show that high proportions of exceedances are clustering over short timescales. Storm surge, wave height and still sea level exceedances occurring

Sea level rise is a major result of climate change that threatens coastal communities and has the potential to incur significant economic damage. Projecting sea level rise as temperatures rise is therefore crucial for policy and decision-making.The two modelling methods currently used to project future sea level change are process-based and semi-empirical. Process-based models rely on combining outputs from coupled atmosphere/ocean models for each component of sea level rise. Semi-empirical models calculate sea level as an integrated response to either warming or radiative forcing, using parameters constrained from past observations.Historically, there is disagreement in sea-level projections between different modelling methods. One source of the discrepancies is uncertainty in land ice response to warming; although nonlinearities exist within processes affecting this response, most existing semi-empirical models treat the relationship between warming and ice-melt as linear.Non-linear ice melt processes may have not yet affected the observational record (such as tipping points as future warming crosses some threshold) or may have already occurred (such as non-linear effects that apply across all levels of warming, or for which the threshold has already been passed). Here, we examine the effect on semi-empirical projections of sea level rise of nonlinearities in ice melt that have already affected the observed sea level record, by adding a nonlinear term to the relationship between warming and the rate of sea level rise within a large ensemble of historically constrained efficient earth systems model simulations.Projections reach a median sea level rise of 1.3m by 2300 following SSP245, and 2.6m by 2300 following SSP585. Results suggest that nonlinear interactions can be sub-linear, super-linear or 0, with a mainly symmetrical distribution. This includes high-impact, low-probability super-linear interactions that lead to significantly larger high-end sea level rise projections than when nonlinear interactions are not included. It is key to note that nonlinear interactions that have not yet occurred but that may occur in the future, are not considered – these will lead to an increased projection of sea level rise.

Billions of historical climatological observations remain unavailable to science as they exist only on paper, stored in numerous archives around the world. The conversion of these data from paper to digital could transform our understanding of historical climate variations, including extreme weather events. Here we demonstrate how the rescue of such paper observations has improved our understanding of a severe windstorm that occurred in February 1903 and its significant impacts. By assimilating newly rescued atmospheric pressure observations, the storm is now credibly represented in an improved reanalysis of the event. In some locations this storm produced stronger winds than any event during the modern period (1950–2015) and it is in the top-4 storms for strongest winds anywhere over land in England & Wales. As a result, estimates of risk from severe storms, based on modern period data, may need to be revised. Examining the atmospheric structure of the storm suggests that it is a classic Shapiro-Keyser-type cyclone with ‘sting jet’ precursors and associated extreme winds at locations and times of known significant damage. Comparison with both independent observations and qualitative information, such as photographs and written accounts, provides additional evidence of the credibility of the atmospheric reconstruction, including of sub-daily rainfall variations. Simulations of the storm surge resulting from this storm show a large coastal surge of around 2.5 m, comparing favourably with newly rescued tide gauge observations and adding to our confidence in the reconstruction. Combining historical rescued weather observations with modern reanalysis techniques has allowed us to plausibly reconstruct a severe windstorm and associated storm surge from more than 100 years ago, establishing an invaluable end-to-end tool to improve assessments of risks from extreme weather.

The original article has been corrected: Legends in Fig. 7 in the article and legends in Figs. 9 and 10 of Supplementary Material 1 as well as contents in columns H and J of Supplementary Material 2 have been amended to the valid results.

South Georgia is a heavily glaciated sub-Antarctic island in the Southern Ocean. Cumberland Bay is the largest fjord on the island, split into two arms, each with a large marine-terminating glacier at the head. Although these glaciers have shown markedly different retreat rates over the past century, the underlying drivers of such differential retreat are not yet understood. This study uses observations and a new high-resolution oceanographic model to characterize oceanographic variability in Cumberland Bay and to explore its influence on glacier retreat. While observations indicate a strong seasonal cycle in temperature and salinity, they reveal no clear hydrographic differences that could explain the differential glacier retreat. Model simulations suggest the subglacial outflow plume dynamics and fjord circulation are sensitive to the bathymetry adjacent to the glacier. The addition of a postulated shallow inner sill in one fjord arm significantly changes the water properties in the resultant inner basin by blocking the intrusion of colder, higher salinity waters at depth. This increase in temperature could accelerate both the subglacial plume-driven melt, and the melting of the wider submarine ice face, which is proposed as a possible explanation for the different rates of glacier retreat observed in the two fjord arms. This study represents the first detailed description of the oceanographic variability of a sub-Antarctic island fjord, highlighting the sensitivity of plume dynamics to bathymetry. Notably, in fjords systems where temperature decreases with depth, the presence of a shallow sill has the potential to accelerate glacier retreat.

The interaction between waves, surges, and astronomical tides can lead to high coastal total water level (TWL), which can in turn trigger coastal flooding. Here, a high-resolution (1.5 km) simulation from a UK-focused regional coupled environmental prediction system is used to investigate the extreme events of winter 2013/4 around the UK and Irish coasts. The aim is to analyse the spatial distribution of coastal TWL and its components during this period by assessing (1) the relative contribution of different TWL components around the coast; (2) how extreme waves, surges, and tide interacted and if they occurred simultaneously; and (3) if this has implications in defining the severity of coastal hazard conditions. The TWL components' coastal distribution in winter 2013/4 was not constant in space, impacting differently over different regions. High (>90th percentile) waves and high surges occurred simultaneously at any tidal stage, including high tide (7.7 % of cases), but more often over the flood tide. During periods of high flood risk, a hazard proxy, defined as the sum of the sea surface height and half the significant wave height, at least doubled from average over three-quarters of the coast. These results have important implications for the risk management sector.

Long-phase (interannual) tidal cycles have been shown to influence coastal flooding and sedimentation, but their role in shaping the extent and condition of tidal wetlands has received little attention. Here, we show that the 18.61-year lunar nodal cycle, popularly termed the “lunar wobble,” is a dominant control over the expansion and contraction of mangrove canopy cover over much of the Australian continent. Furthermore, the contrasting phasing of the 18.61-year lunar nodal cycle between diurnal and semidiurnal tidal settings has mediated the severity of drought impacts in northern bioregions. Long-phase tidal cycles regulate maximum tide heights, are an important control over mangrove canopy cover, and may influence mangrove ecosystem services including forest productivity and carbon sequestration at regional scales.

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.

Coastal compound flooding events occur when extreme events of rainfall, river discharge and sea level coincide and collectively increase water surface elevation, exacerbating flooding. The meteorological conditions that generate these events are usually low-pressure systems that generate high winds and intense rainfall. In this study, we identify the types of synoptic atmospheric conditions that are typically associated with coastal compound events using a weathertype approach, for the North Atlantic coastlines (encompassing northwest Europe and the east coast of the United States). Compound events are identified along the estuaries of the study region from 1980 to 2014 based on an impact function defined by water surface elevation that resulted from the combination of river discharge and sea level. We find that compound events are more frequent along European as opposed to U.S. coastlines. In both cases, they are associated with a few dominant weather patterns. European hotspots of compound events are concentrated in the west coast of United Kingdom, the northwest coast of the Iberian Peninsula and around the Strait of Gibraltar. These areas share the same weather patterns which represent the main pathways of storms that cross the North Atlantic Ocean. In the case of U.S. locations, the areas with highest number of compound events are located mainly in the Gulf of Mexico and along Mexico and along the mid-eastern U.S. coastlines. In these areas, compound events are produced by transitional weather patterns, which describe storms that travel northward parallel to the coastline. Splitting the occurrence of compound events in the corresponding weather types discriminates the interannual variability based on the relationship with dominant climate indices in the North Atlantic Ocean. This research forms part of the CHANCE project, which is supported by awards from the UK Natural Environment Research Council (NE/S010262/1) and US National Science Foundation (1929382). We would like to thank Dirk Eilander for providing support about the use of dataset of simulated water levels and discharge at river mouth locations globally which is available on Zenodo(doi: 10.5281/zenodo.3665734).

Tropical cyclones (TC) are one of the deadliest and costliest natural disasters. To mitigate the impact of such disasters, it is essential to know extreme exceedance probabilities, also known as return periods, of TC hazards. In this paper, we demonstrate the use of the STORM dataset, containing synthetic TCs equivalent of 10,000 years under present-day climate conditions, for the calculation of TC wind speed return periods. The temporal length of the STORM dataset allows us to empirically calculate return periods up to 10,000 years without fitting an extreme value distribution. We show that fitting a distribution typically results in higher wind speeds compared to their empirically derived counterparts, especially for return periods exceeding 100-yr. By applying a parametric wind model to the TC tracks, we derive return periods at 10 km resolution in TC-prone regions. The return periods are validated against observations and previous studies, and show a good agreement. The accompanying global-scale wind speed return period dataset is publicly available and can be used for high-resolution TC risk assessments.

There is growing interest in harnessing renewable energy resources in Latin America. Converting the energy of the tides into electricity has the distinct advantage of being predictable, yet the tidal range resource of Latin America is largely unquantified. The northern part of the Gulf of California (GC) in Mexico has a relatively large mean tidal range (4m–5m), and so could be a potential site for tidal range energy exploitation. A detailed quantification of the theoretical tidal range energy resource was performed using tidal level predictions from a depth-averaged barotropic hydrodynamic model. In addition, a 0-D operation modelling approach was applied to determine the power that can be technically extracted at four key sites. The results show that the annual energy yield ranges from 20 to 50 kWh/m2, while the maximum values are between 45 and 50 kWh/m2 in the vicinity of the Gulf of Santa Clara. Within the region, the Gulf of Santa Clara is one of the most promising, delivering a technical annual energy output of 125 GWh (ebb-only generation), 159 GWh (two-way) and 174 GWh (two-way with pumping) within an impoundment area of 10 km2. This equates to 50%, 40% and 33% of the absolute energy conversion relative to a much-studied reference site (Swansea Bay, UK) that has been under consideration as the world’s first tidal lagoon power plant. This study provides the basis for more detailed analysis of the GC to guide selection of suitable sites for tidal range energy exploitation in the region.

Natural World Heritage Sites (NWHS), which are of Outstanding Universal Value, are increasingly threatened by natural and anthropogenic pressures. This is especially true for coastal NWHS, which are additionally subject to erosion and flooding. This study assesses shoreline change from 1984 to 2016 within the boundaries of 67 designated sites, providing a first global consistent assessment of its drivers. It develops a transferable methodology utilising new satellite-derived global shoreline datasets, which are classified based on linearity of change against time and compared with global datasets of geomorphology (topography, land cover, coastal type, and lithology), climate variability and sea-level change. Significant shoreline change is observed on 14% of 52 coastal NWHS shorelines that show the largest recessional and accretive trends (means of -3.4 m yr-1 and 3.5 m yr-1, respectively). These rapid shoreline changes are found in low-lying shorelines (< 1 m elevation) composed of unconsolidated sediments in vegetated tidal coastal systems (means of -7.7 m yr-1 and 12.5 m yr-1), and vegetated tidal deltas at the mouth of large river systems (means of -6.9 and 11 m yr-1). Extreme shoreline changes occur as a result of redistribution of sediment driven by a combination of geomorphological conditions with (1) specific natural coastal morphodynamics such as opening of inlets (e.g. Río Plátano Biosphere Reserve) or gradients of alongshore sediment transport (e.g. Namib Sea) and (2) direct or indirect human interferences with natural coastal processes such as sand nourishment (e.g. Wadden Sea) and damming of river sediments upstream of a delta (e.g. Danube Delta). The most stable soft coasts are associated with the protection of coral reef ecosystems (e.g. Great Barrier Reef) which may be degraded/destroyed by climate change or human stress in the future. A positive correlation between shoreline retreat and local relative sea-level change was apparent in the Wadden Sea. However, globally, the effects of contemporary sea-level rise are not apparent for coastal NWHS, but it is a major concern for the future reinforcing the shoreline dynamics already being observed due to other drivers. Hence, future assessments of shoreline change need to account of other drivers of coastal change in addition to sea-level rise projections. In conclusion, extreme multi-decadal linear shoreline trends occur in coastal NWHS and are driven primarily by sediment redistribution. Future exacerbation of these trends may affect heritage values and coastal communities. Thus shoreline change should be considered in future management plans where necessary. This approach provides a consistent method to assess NWHS which can be repeated and help steer future management of these important sites.

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.

We demonstrate that long-term tidally induced changes in extreme sea levels affect estimates of major flood hazard in a predictable way. Long-term variations in tides due to the 4.4 and 18.6-year cycles influence extreme sea levels at 380 global tide gauges out of a total of 581 analyzed. Results show coherent regions where the amplitudes of the modulations are particularly relevant in the 100-year return sea level, reaching more than 20 cm in some regions (western Europe, north Australia, and Singapore). We identify locations that are currently in a positive phase of the modulation and therefore at a higher risk of flooding, as well as when (year) the next peak of the long-term tidal modulations is expected to occur. The timing of the peak of the modulation is spatially coherent and influenced by the relative importance of each cycle (4.4 or 18.6-year) over the total amplitude. An evaluation of four locations suggests that the potentially flooded area in a 100-year event can vary up to ∼45% (in Boston) as a result of the long-term tidal cycles; however, the flooded area varies due to local topography and tidal characteristics (6%–13%). We conclude that tidally modulated changes in extreme sea levels can alter the potentially inundated area in a 100-year event and that the traditional, fixed 100-year floodplain is inadequate for describing coastal flood risk, even without considering sea-level rise.

In the UK, coastal flooding and erosion are two of the primary climate-related hazards to communities, businesses, and infrastructure. To better address the ramifications of those hazards, now and into the future, the UK needs to transform its scattered, fragmented coastal data resources into a systematic, integrated, quality-controlled, openly accessible data portal. Such a portal would support analyses of coastal risk and resilience by hosting, in addition to data layers for coastal flooding and erosion, a diverse array of spatial datasets for building footprints, infrastructure networks, land use, population, and various socio-economic measures and indicators derived from survey and census data. Rather than prescribe user engagement, the portal would facilitate novel combinations of spatial data layers in order to yield scientifically, societally, and economically beneficial insights into UK coastal systems.

Coastal floods, driven by extreme sea levels, are one of the most dangerous natural hazards. The people at highest risk are those living in low-lying coastal areas exposed to tropical-cyclone-forced storm surges. Here we apply a novel modelling framework to estimate past and/or present and future storm-surge-level and extreme-sea-level probabilities along the coastlines of southern China, Vietnam, Cambodia, Thailand, and Malaysia. A regional hydrodynamic model is configured to simulate 10 000 years of synthetic tropical cyclone activity, representative of a past/present (1980–2017) and high-emission-scenario future (2015–2050) period. Results show that extreme storm surges, and therefore total water levels, will increase substantially in the coming decades, driven by an increase in the frequency of intense tropical cyclones. Storm surges along the southern Chinese and northern and southern Vietnamese coastlines increase by up to 1 m, significantly larger than expected changes in mean sea-level rise over the same period. The length of coastline that is presently exposed to storm surge levels of 2.5 m or greater will more than double by 2050. Sections of Cambodian, Thai, and Malaysian coastlines are projected to experience storm surges (at higher return periods) in the future, not previously seen, due to a southward shift in tropical cyclone tracks. Given these findings, coastal flood management and adaptation in these areas should be reviewed for their resilience against future extreme sea levels.

Estuarine margins are usually heavily occupied areas that are commonly affected by compound flooding triggers originating from different sources (e.g., coastal, fluvial, and pluvial). Therefore, estuarine flood management remains a challenge due to the need to combine the distinct dimensions of flood triggers and damages. Past flood data are critical for improve our understanding of flood risks in these areas, while providing the basis for a preliminary flood risk assessment, as required by European Floods Directive. This paper presents a spin-off database of estuarine flood events built upon previously existing databases and a framework for working with qualitative past flood information using multiple correspondence analysis. The methodology is presented, with steps ranging from a spin-off database building process to information extraction techniques, and the statistical method used was further explored through the study of information acquired from the categories and their relation to the dimensions. This work enabled the extraction of the most relevant estuarine flood risk indicators and demonstrates the transversal importance of triggers, since they are of utmost importance for the characterization of estuarine flood risks. The results showed a relation between sets of triggers and damages that are related to estuarine margin land use, demonstrating their ability to inform flood risk management options. This work provides a consistent and coherent approach to use qualitative information on past floods, as a useful contribution in the context of scarce data, where measured and documentary data are not simultaneously available info:eu-repo/semantics/publishedVersion

Although regional studies and projections suggest the deterioration of estuaries as a consequence of climate change, it is still difficult to fully understand the importance of such changes in estuarine systems. This limitation is particularly important considering their high dynamism and the lack of temporally extended in situ databases with a good spatial coverage for these systems worldwide. Furthermore, contradictory patterns have been observed across the globe. Motivated by these issues, in this study we question the availability of in situ observational evidence of climate change in estuarine systems through a detailed meta-analysis of existing publications. A topic-related search considering the outputs of the Web of Science library was conducted in order to obtain a characterization of the existing studies on climate change in estuarine systems. Results confirmed that climate change has increasingly been studied since 2000 and that marine climate change constituted the focus of 9.69 % of those studies. From these, only 9.30 % encompassed estuarine studies and just 1.13 % used in situ observations from estuarine systems (i.e., 0.11 % of the total climate change publications). Reanalysis products were the most used tools to assess changes in estuarine systems and sea temperature was the most analyzed variable. These results highlight the need to further address such questions using in situ observational data and to implement long-term observatories to fully identify evidence of climate change in estuarine systems, supporting modelling approaches and promoting the development of effective mitigation plans.

Quantification of the controls on turbidity current recurrence is required to better constrain land to sea fluxes of sediment, carbon and pollutants, and design resilient infrastructure that is vulnerable to such flows. This is particularly important offshore from river deltas, where sediment supply is high. Numerous mechanisms can trigger turbidity currents, even at a single river mouth. However quantitative analysis of recurrence and triggers has been limited to an individual trigger for each turbidity current due to the low number of precisely timed (via direct monitoring) flows. We are therefore yet to quantify if and how coincident processes combine to generate turbidity currents, and their relative importance. Here, we analyse the timing and causes of 113 turbidity currents directly-monitored from the source of turbidity current initiation to depositional sink in a single submarine channel. This submarine channel is located offshore from glacial-fed river-deltas at Bute Inlet, a fjord in British Columbia, Canada. Using a multivariate statistical approach, we demonstrate the statistical significance of combined river discharge and tidal controls on turbidity current occurrence during 2018, from which we derive a statistical model that calculates turbidity current probability for any given input of river discharge and water level. This new model predicts turbidity current activity with >84% success offshore other river deltas where flow timing is precisely constrained by directly monitoring, including the Squamish and Fraser River-deltas in British Columbia. We suggest that this model will be applicable for turbidity current prediction at glacial meltwater-fed fjords in many other regions worldwide.

The Global Extreme Sea Level Analysis (GESLA) dataset contains, in its recently released version 3, a total of 5199 tide gauge records of hourly (or higher) temporal resolution, globally distributed and totalling more than 91000 years of data (www.gesla.org). This represents twice the number of observations compared to the former version of the database. The tide gauge records have been compiled from multiple data providers and so they have different levels of quality controls. Here we describe a set of tools to homogenise and quality control sea level observations from raw GESLA files, including adjustments of datum jumps and time shifts in the time series. We apply these tools to estimate tidal constituents from the extended in-situ dataset. The results are used to identify the river influences on coastal tide gauges and to map the spatial patterns of mean tidal ranges along densely monitored coastlines.

Coastal flooding is a major global hazard, yet few studies have examined the spatial and temporal characteristics of extreme sea level and associated coastal flooding. Here we analyse sea-level records around the coast of New Zealand (NZ) to quantify extreme storm-tide and skew-surge frequency and magnitude. We identify the relative magnitude of sea-level components contributing to 85 extreme sea level and 135 extreme skew-surge events recorded in NZ since 1900. We then examine the spatial and temporal clustering of these extreme storm-tide and skew-surge events and identify typical storm tracks and weather types associated with the spatial clusters of extreme events. We find that most extreme storm tides were driven by moderate skew surges combined with high perigean spring tides. The spring–neap tidal cycle, coupled with a moderate surge climatology, prevents successive extreme storm-tide events from happening within 4–10 d of each other, and generally there are at least 10 d between extreme storm-tide events. This is similar to findings from the UK (Haigh et al., 2016), despite NZ having smaller tides. Extreme events more commonly impacted the east coast of the North Island of NZ during blocking weather types, and the South Island and west coast of the North Island during trough weather types. The seasonal distribution of both extreme storm-tide and skew-surge events closely follows the seasonal pattern of mean sea-level anomaly (MSLA) – MSLA was positive in 92 % of all extreme storm-tide events and in 88 % of all extreme skew-surge events. The strong influence of low-amplitude (−0.06 to 0.28 m) MSLA on the timing of extreme events shows that mean sea-level rise (SLR) of similarly small height will drive rapid increases in the frequency of presently rare extreme sea levels. These findings have important implications for flood management, emergency response and the insurance sector, because impacts and losses may be correlated in space and time.

In coastal regions, floods can arise through a combination of multiple drivers, including direct surface run-off, river discharge, storm surge, and waves. In this study, we analyse compound flood potential in Europe and environs caused by these four main flooding sources using state-of-the-art databases with coherent forcing (i.e. ERA5). First, we analyse the sensitivity of the compound flooding potential to several factors: (1) sampling method, (2) time window to select the concurrent event of the conditioned driver, (3) dependence metrics, and (4) wave-driven sea level definition. We observe higher correlation coefficients using annual maxima than peaks over threshold. Regarding the other factors, our results show similar spatial distributions of the compound flooding potential. Second, the dependence between the pairs of drivers using the Kendall rank correlation coefficient and the joint occurrence are synthesized for coherent patterns of compound flooding potential using a clustering technique. This quantitative multi-driver assessment not only distinguishes where overall compound flooding potential is the highest, but also discriminates which driver combinations are more likely to contribute to compound flooding. We identify that hotspots of compound flooding potential are located along the southern coast of the North Atlantic Ocean and the northern coast of the Mediterranean Sea.

Sea-levels will rise, even with stringent climate change mitigation. Mitigation will slow the rate of rise. There is limited knowledge on how the costs of coastal protection vary with alternative global warming levels of 1.5°C to 4.0°C. Analysing six sea-level rise scenarios (0.74m to 1.09m, 50th percentile) across these warming levels, and five Shared Socioeconomic Pathways, this paper quantifies the economic costs of flooding and protection due to sea-level rise using the Dynamic Interactive Vulnerability Assessment (DIVA) modelling framework. Results are presented for World Bank income groups and five selected countries from the present to 2100. Annual sea flood damage costs without additional adaptation are more influenced by socio-economic development than sea-level rise, indicating there are opportunities to control risk with development choices. In contrast, annual sea dike investment costs are more dependent on the magnitude of sea-level rise. In terms of total costs with adaptation, upper middle, low middle and low income groups are projected to have higher relative costs as a proportion of GDP compared with high income groups. If low income countries protected now, flood costs could be reduced after 2050 and beyond. However, without further adaptation, their coasts will experience growing risks and costs leaving them increasingly reliant on emergency response measures. adaptation. Without mitigation or adaptation, greater inequalities in damage costs between income groups could result. At country level, annual sea flood damage costs without additional adaptation are projected to rapidly increase with approximately 0.2m of sea-level rise, leaving limited time to plan and adapt. SB, PG, KJ, RJ and RW were funded by the Department for Business, Energy and Industrial Strategy (BEIS) under contract UK SBS CR18083. ASA, SB, SJ, DL, RN, RT and AV were funded by the European Union’s Seventh Programme for Research, Technological Development and Demonstration under grant agreement No. 603396 (RISES-AM project).

Flooding is of particular concern in low-lying coastal zones that are prone to flooding impacts from multiple drivers, such as oceanographic (storm surge and wave), fluvial (excessive river discharge), and/or pluvial (surface runoff). In this study, we analyse, for the first time, the compound flooding potential along the contiguous United States (CONUS) coastline from all flooding drivers, using observations and reanalysis data sets. We assess the overall dependence from observations by using Kendall's rank correlation coefficient (τ) and tail (extremal) dependence (χ). Geographically, we find the highest dependence between different drivers at locations in the Gulf of Mexico, southeastern, and southwestern coasts. Regarding different driver combinations, the highest dependence exists between surge–waves, followed by surge–precipitation, surge–discharge, waves–precipitation, and waves–discharge. We also perform a seasonal dependence analysis (tropical vs. extra-tropical season), where we find higher dependence between drivers during the tropical season along the Gulf and parts of the East Coast and stronger dependence during the extra-tropical season on the West Coast. Finally, we compare the dependence structure of different combinations of flooding drivers, using observations and reanalysis data, and use the Kullback–Leibler (KL) divergence to assess significance in the differences of the tail dependence structure. We find, for example, that models underestimate the tail dependence between surge–discharge on the East and West coasts and overestimate tail dependence between surge–precipitation on the East Coast, while they underestimate it on the West Coast. The comprehensive analysis presented here provides new insights on where the compound flooding potential is relatively higher, which variable combinations are most likely to lead to compounding effects, during which time of the year (tropical versus extra-tropical season) compound flooding is more likely to occur, and how well reanalysis data capture the dependence structure between the different flooding drivers.

Turbidity currents dominate sediment transfer into the deep ocean, and can damage critical seabed infrastructure. It is commonly inferred that powerful turbidity currents are triggered by major external events, such as storms, river floods, or earthquakes. However, basic models for turbidity current triggering remain poorly tested, with few studies accurately recording precise flow timing. Here, we analyse the most detailed series of measurements yet made of powerful (up to 7.2 m s−1) turbidity currents, within Monterey Canyon, offshore California. During 18-months of instrument deployment, fourteen turbidity currents were directly monitored. No consistent triggering mechanism was observed, though flows did cluster around enhanced seasonal sediment supply. We compare turbidity current timing at Monterey Canyon (a sandy canyon-head fed by longshore drift) to the only other systems where numerous (>10-100) flows have been measured precisely via direct monitoring; the Squamish Delta (a sandy fjord-head delta), and the Congo Canyon (connected to the mud-dominated mouth of the Congo River). A common seasonal pattern emerges, leading to a new model for preconditioning and triggering of turbidity currents initiating through slope failure in areas of sediment accumulation, such as canyon heads or river mouths. In this model, rapid or sustained sediment supply alone can produce elevated pore pressures, which may persist, thereby predisposing slopes to fail. Once preconditioned, a range of minor external perturbations, such as moderate storm-waves, result in local pore pressure variation, and thus become effective triggers. Major external triggers are therefore not always a prerequisite for triggering of powerful turbidity currents.

In this paper, we show that over the next few decades, the natural variability of mid-latitude storm systems is likely to be a more important driver of coastal extreme sea levels than either mean sea level rise or climatically induced changes to storminess. Due to their episodic nature, the variability of local sea level response, and our short observational record, understanding the natural variability of storm surges is at least as important as understanding projected long-term mean sea level changes due to global warming. Using the December 2013 North Atlantic Storm Xaver as a baseline, we used a meteorological forecast modification tool to create “grey swan” events, whilst maintaining key physical properties of the storm system. Here we define “grey swan” to mean an event which is expected on the grounds of natural variability but is not within the observational record. For each of these synthesised storm events, we simulated storm tides and waves in the North Sea using hydrodynamic models that are routinely used in operational forecasting systems. The grey swan storms produced storm surges that were consistently higher than those experienced during the December 2013 event at all analysed tide gauge locations along the UK east coast. The additional storm surge elevations obtained in our simulations are comparable to high-end projected mean sea level rises for the year 2100 for the European coastline. Our results indicate strongly that mid-latitude storms, capable of generating more extreme storm surges and waves than ever observed, are likely due to natural variability. We confirmed previous observations that more extreme storm surges in semi-enclosed basins can be caused by slowing down the speed of movement of the storm, and we provide a novel explanation in terms of slower storm propagation allowing the dynamical response to approach equilibrium. We did not find any significant changes to maximum wave heights at the coast, with changes largely confined to deeper water. Many other regions of the world experience storm surges driven by mid-latitude weather systems. Our approach could therefore be adopted more widely to identify physically plausible, low probability, potentially catastrophic coastal flood events and to assist with major incident planning.

Rain-gauge datasets indicate strong increases in both annual mean and extreme precipitation over large parts of the Mainland Southeast Asia (MSEA) including Vietnam and the northwestern part of the peninsula over the last 40 years. Increasing precipitation is associated with increased monsoon intensity in southeast Asia and a northward shift of the monsoon activity centre towards MSEA. Warming-driven evaporation increases over the three main oceanic moisture sources - the Arabian Sea, the Bay of Bengal, and the South China Sea- may partially explain increasing precipitation in large parts of MSEA. Changes in the patterns of the two main modes of natural variability in the tropical Indian Ocean – the Indian Ocean Basin Mode (IOBM) and the Indian Ocean Dipole (IOD) – contribute to surface warming in these oceanic moisture source regions supplying precipitation to MSEA. Climate model projections show robust wide-spread trends in wet season precipitation with increasing frequency and intensity of extreme precipitation events throughout MSEA over the 21st century. Similar to observations, the projected precipitation trends are associated with strong warming-driven increases in evaporation in all major oceanic moisture sources supplying precipitation to MSEA.

In coastal regions, floods can arise through a combination of multiple drivers, including direct surface run- off, river discharge, storm surge and waves. In this study, we analyse compound flood potential in Europe caused by these four main flooding sources using state-of-the-art databases with homogenous forcing (i.e., ERA5). First, we perform an analysis to assess the sensitivity of the compound flooding potential to several factors: 1) sampling method; 2) time window to select the concurrent event of the conditioned driver; 3) dependence metrics; 4) wave-driven sea level definition. We observe higher correlation coefficients using annual maxima than peaks over threshold. Regarding the other factors, our results show similar spatial distributions of the compound flooding potential. Second, the dependence between the pairs of drivers using the Kendall's rank correlation coefficient and the joint occurrence are synthesized for coherent patterns of compound flooding potential using a clustering technique. This quantitative multi-driver assessment not only distinguishes where overall compound flooding potential is the highest, but also discriminates which driver combinations are more likely to contribute to compound flooding. We identify hotspots of compound flooding potential located along the southern coast of the North Atlantic Ocean and the northern coast of the Mediterranean Sea.

Observational rain gauge/satellite and reanalysis datasets since the 1950s are evaluated for trends in mean and extreme rainfall over Mainland Southeast Asia (MSEA). Rain gauge data indicate strong increases exceeding 50% in both annual mean precipitation and various extreme precipitation indices over Vietnam and the northwestern part of the peninsula since 1979. Increasing precipitation in MSEA is associated with increased monsoon intensity in southeast Asia and a northward shift of the monsoon activity centre towards MSEA over 1979-2018. Re-analysis data reveal warming-driven increases in evaporation over the seas adjacent to MSEA, including the main oceanic source regions feeding precipitation over the peninsula - the Arabian Sea, the Bay of Bengal, and the South China Sea. Furthermore, moisture budget analysis based on the ERA5 re-analysis also showed increasing oceanic moisture transport along the typical winter and summer moisture pathways towards the MSEA. However, the majority of the increased moisture from these oceanic sources ends up as summer precipitation over the oceanic regions adjacent to the MSEA. In contrast, the ERA5 data do reveal pronounced increases in winter precipitation over the MSEA, in accordance with rain-gauge data, that are associated with increased transport of moisture that originated from the western tropical Pacific and the South China Sea. Long-term amplification of the regional hydrological cycle is further investigated, through analysis of CMIP5 coupled climate models in historical and RCP4.5/8.5 21st century scenario simulations. The CMIP5 ensemble mean shows robust wide-spread trends in wet season precipitation with increasing frequency and intensity of extreme precipitation events over the MSEA, following strong increases in evaporation in the oceanic moisture sources.

This study reports a new and significantly enhanced analysis of US flood hazard at 30 m spatial resolution. Specific improvements include updated hydrography data, new methods to determine channel depth, more rigorous flood frequency analysis, output downscaling to property tract level, and inclusion of the impact of local interventions in the flooding system. For the first time, we consider pluvial, fluvial, and coastal flood hazards within the same framework and provide projections for both current (rather than historic average) conditions and for future time periods centered on 2035 and 2050 under the RCP4.5 emissions pathway. Validation against high-quality local models and the entire catalog of FEMA 1% annual probability flood maps yielded Critical Success Index values in the range 0.69–0.82. Significant improvements over a previous pluvial/fluvial model version are shown for high-frequency events and coastal zones, along with minor improvements in areas where model performance was already good. The result is the first comprehensive and consistent national-scale analysis of flood hazard for the conterminous US for both current and future conditions. Even though we consider a stabilization emissions scenario and a near-future time horizon, we project clear patterns of changing flood hazard (3σ changes in 100 years inundated area of −3.8 to +16% at 1° scale), that are significant when considered as a proportion of the land area where human use is possible or in terms of the currently protected land area where the standard of flood defense protection may become compromised by this time.

Este artículo contiene 7 páginas, 3 figuras., Explaining why some species are widespread, while others are not, is fundamental to biogeography, ecology, and evolutionary biology. A unique way to study evolutionary and ecological mechanisms that either limit species’ spread or facilitate range expansions is to conduct research on species that have restricted distributions. Nonindigenous species, particularly those that are highly invasive but have not yet spread beyond the introduced site, represent ideal systems to study range size changes. Here, we used species distribution modeling and genomic data to study the restricted range of a highly invasive Australian marine species, the ascidian Pyura praeputialis. This species is an aggressive space occupier in its introduced range (Chile), where it has fundamentally altered the coastal community. We found high genomic diversity in Chile, indicating high adaptive potential. In addition, genomic data clearly showed that a single region from Australia was the only donor of genotypes to the introduced range. We identified over 3,500 km of suitable habitat adjacent to its current introduced range that has so far not been occupied, and importantly species distribution models were only accurate when genomic data were considered. Our results suggest that a slight change in currents, or a change in shipping routes, may lead to an expansion of the species’ introduced range that will encompass a vast portion of the South American coast. Our study shows how the use of population genomics and species distribution modeling in combination can unravel mechanisms shaping range sizes and forecast future range shifts of invasive species., M.R. received funds from ASSEMBLE (a European Union Seventh Framework Programme research infrastructure initiative comprising a network of marine research stations) to visit the Estación Costera de Investigaciones Marinas de Las Cruces and the Pontificia Universidad Católica de Chile. P.R.T. was supported by the University of Johannesburg (Faculty Research Committee/ University Research Committee grant) and L.B.B. by the Australian Research Council. J.C.C. acknowledges financial support from the Nucleo Milenio en Conservación Marina. J.C.C. sincerely acknowledges long-term financial support (Pontificia Universidad Católica de Chile–Escondida Project) fromMinera Escondida Ltda, the last 10-y support from the Academic Chair “Arauco-UC” and the important and constant assistance and advice from Dr. PatricioManríquez. C.D.M. received funding fromthe South African Research Chairs Initiative of the Department of Science and Technology and the National Research Foundation (Grant 64801).

Simple flushing time calculations for estuarine systems can be used as proxies for eutrophication susceptibility. However, more complex methods are required to better understand entire systems. Understanding of the hydrodynamics driving circulation and flushing times in small, eutrophic, temperate estuaries is less advanced than larger counterparts due to lack of data and difficulties in accurately modelling small-scale systems. This paper uses the microtidal Christchurch Harbour estuary in Southern UK as a case study to elucidate the physical controls on eutrophication susceptibility in small shallow basins. A depth-averaged hydrodynamic model has been configured of the estuary to investigate the physical processes driving circulation with particular emphasis on understanding the impact of riverine inputs to this system. Results indicate circulation control changes from tidally to fluvially driven as riverine inputs increase. Flushing times, calculated using a particle tracking method, indicate that the system can take as long as 132 h to flush when river flow is low, or as short as 12 h when riverine input is exceptionally high. When total river flow into the estuary is less than 30 m3 s−1, tidal flux is the dominant hydrodynamic control, which results in high flushing times during neap tides. Conversely, when riverine input is greater than 30 m3 s−1, the dominant hydrodynamic control is fluvial flux, and flushing times during spring tides are longer than at neaps. The methodology presented here shows that modelling at small spatial scales is possible but highlights the importance of particle tracking methods to determine flushing time variability across a system.