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Environmental hazards represent a major socio-economic challenge where floods events are the most impactful in terms of global population affected (UNDRR, 2020). Coastal areas are exposed to multiple met-ocean extreme events which can occur separately or combined. Storm surges associated with wind waves, heavy rainfall and tides can lead to catastrophic inundation events associated with breakdown of structures, food and water insecurities and loss of lives. Additionally, climate changes are associated with two coastal risk factors: a) an increase of extreme events (Schiermeier, 2011; Vitousek et al., 2017) and b) an increase of sea level rise (IPCC, 2018).Different approaches exist to flood modelling (Vousdoukas et al.,2016; Dottori, Martina and Figueiredo, 2018), varying by complexity and accuracy. Simple hydrological models, which operate by integrating the 2D shallow water equation in a flood-plain, offer a good trade-off between computational demand and good skills in simulating real coastal flood events (Smith, Bates and Hayes, 2012). Since accurate inundation modelling is of great importance for risk prevention and management of coastal areas, a system that can be reallocated and calibrated for different regions is a forefront of the research topic.As a first case study, the flood event of February 2015 in Emilia-Romagna Region (Italy) was selected. The event was characterized by a combination of heavy rain, waves and tides which leads to one of the highest water levels ever recorded in the area (Perini et al., 2015). The model was run with different Digital Elevation Models and forced with water levels provided by Istituto Superiore per la Protezione e la Ricerca Ambientale (ISPRA) station. The results were compared with observational data of inundation maps. A broad agreement was found between inundation maps produced by the model and observational data, though with significant local discrepancies. The main differences between model and observations can be ascribed mainly to DEM’s local uncertainty. Work is in progress to include the different types of forcings and to elaborate machine-learning based protocols of calibration to locally improve the model skill, by a) optimizing the mean elevation of the DEM using the modelled and observed flooded areas and b) best-fitting Manning coefficients over the DEM using land use data.

We calculate the magnitude of a worst case scenario for extreme sea levels along the global coastline by 2100. Our worst case scenario for extreme sea levels is a combination of sea surface height associated with storm surge and wave (100-year return period, the 95th percentile), high tide (the 95th percentile) and a low probability sea level rise scenario (the 95th percentile). We show that by 2100 extreme sea levels have a 5% change of exceeding 4.2 m (global coastal average), compared to 2.6 m during the baseline period (1980-2014). Up to 90% of increases in magnitude of extreme sea levels are driven by future sea level rise, compare to 10% associated with changes in storm surges and waves. By 2030-2040 the present-day 100-year return period for extreme sea levels would be experienced at least once a year in tropical areas. This 100-fold increase in frequency will take place on all global coastlines by 2100. Future changes in magnitude and frequency of extreme sea levels undermine the resilience of coastal communities and ecosystems, considering that sea level rise will increase the magnitude, frequency of extreme sea levels and will reduce the time for post-event recovery.

Extreme sea levels (ESLs) in Europe could rise by as much as one metre or more by the end of this century due to climate change. This poses significant challenges to safeguard coastal communities. Here we present a comprehensive analysis of economically efficient protection scenarios along Europe’s coastlines during the present century. We employ a probabilistic framework that integrates dynamic simulations of all ESL components and flood inundation, impact modelling and a cost-benefit analysis of raising dykes. We find that at least 83% of flood damages in Europe could be avoided by elevating dykes in an economically efficient way along 23.7%-32.1% of Europe’s coastline, specifically where high value conurbations exist. The European mean benefit to cost ratio of the investments varies from 8.3 to 14.9 while at country level this ranges between 1.6 and 34.3, with higher efficiencies for a scenario with high-end greenhouse gas emissions and strong socio-economic growth., There lacks a European cost-benefit analysis of possible protective measures against rising seas. Here the authors used a probabilistic data and modeling framework to estimate costs and benefits of coastal protection measures and found that at least 83% of flood damages could be avoided by dyke improvements along a third of the European coastline.

Delivering infrastructure, resilient to multiple natural hazards and climate change, is fundamental to continued economic prosperity and social coherence. This is a strategic priority of the United Nations Sustainable Development Goals (SDGs), the World Bank, the Organisation for Economic Co-operation and Development (OECD), public policies and global initiatives. The operability and functionality of critical infrastructure are continuously challenged by multiple stressors, increasing demands and ageing, whilst their interconnectedness and dependencies pose additional challenges. Emerging and disruptive digital technologies have the potential to enhance climate resilience of critical infrastructure, by providing rapid and accurate assessment of asset condition and support decision-making and adaptation. In this pursuit, it is imperative to adopt multidisciplinary roadmaps and deploy computational, communication and other digital technologies, tools and monitoring systems. Nevertheless, the potential of these emerging technologies remains largely unexploited, as there is a lack of consensus, integrated approaches and legislation in support of their use. In this perspective paper, we discuss the main challenges and enablers of climate-resilient infrastructure and we identify how available roadmaps, tools and emerging digital technologies, e.g. Internet of Things, digital twins, point clouds, Artificial Intelligence, Building Information Modelling, can be placed at the service of a safer world. We show how digital technologies will lead to infrastructure of enhanced resilience, by delivering efficient and reliable decision-making, in a proactive and/or reactive manner, prior, during and after hazard occurrences. In this respect, we discuss how emerging technologies significantly reduce the uncertainties in all phases of infrastructure resilience evaluations. Thus, building climate-resilient infrastructure, aided by digital technologies, will underpin critical activities globally, contribute to Net Zero target and hence safeguard our societies and economies. To achieve this we set an agenda, which is aligned with the relevant SDGs and highlights the urgent need to deliver holistic and inclusive standards and legislation, supported by coordinated alliances, to fully utilise emerging digital technologies., Climate Risk Management, 35, ISSN:2212-0963

Climate change and anthropogenic pressures are widely expected to exacerbate coastal hazards such as episodic coastal flooding. This study presents global-scale potential coastal overtopping estimates, which account for not only the effects of sea level rise and storm surge, but also for wave runup at exposed open coasts. Here we find that the globally aggregated annual overtopping hours have increased by almost 50% over the last two decades. A first-pass future assessment indicates that globally aggregated annual overtopping hours will accelerate faster than the global mean sea-level rise itself, with a clearly discernible increase occurring around mid-century regardless of climate scenario. Under RCP 8.5, the globally aggregated annual overtopping hours by the end of the 21st-century is projected to be up to 50 times larger compared to present-day. As sea level continues to rise, more regions around the world are projected to become exposed to coastal overtopping., As sea levels rise, coasts are being increasingly threatened by overtopping caused by the combination of sea level rise, storm surge and wave runup. Here the authors find that global coastal overtopping has increased by over 50% in the last two decades, and under a RCP 8.5 scenario this could increase up to 50 times by 2100 compared to today.

Important heritage sites along the African coast are at risk from the threats associated with rising sea levels. Here, we quantify the exposure of natural and cultural heritage sites in Africa to coastal flooding and erosion in the 21st century. We develop a comprehensive database of 284 coastal African Heritage Sites (AHS), composed of 213 natural and 71 cultural heritage sites, which is then combined with coastal flooding and erosion projections to assess exposure to coastal extreme events for a moderate (RCP4.5) and high (RCP8.5) greenhouse gas emissions scenario. We find that 56 AHS are presently at risk from a 100-year extreme sea-level event, with a total exposed heritage area of 2,222 km2. Most of the currently exposed AHS are located in Northern and Western Africa. By mid-century, the number of exposed AHS is projected to increase more than 3 times to reach 191 and 198 under moderate and high emissions respectively. In the second half of the century, the number of exposed sites stabilizes, but the median exposed area increases to 6.6 to 8.5 times the present-day value, under moderate and high emissions, respectively. Mitigation from high to moderate emissions will reduce the end-century median exposed area and number of very highly exposed sites by 20% and 25% respectively.

Coastal erosion is a major issue facing Europe that will only worsen under future climate change and the resulting sea level rise. One effect of erosion is the loss of ecosystem services, which are provided by coastal areas, such as provisioning, regulating, habitat, and cultural services. These services can be quantified in monetary terms. Here, we present comprehensive estimates of future decline in coastal ecosystem services due to the erosion of sandy coastlines. We used datasets derived from remote sensing products: a pan-European land cover/use dataset (Corine Land Cover) and new global probabilistic coastal erosion projections constrained by artificial and topographical barriers to erosion. The results include historical changes (2000–2018) and projections under two emission scenarios (RCP4.5 and RCP8.5) for 2050 and 2100 together with uncertainty bounds. We estimate that in 2018, the coastal zone (excluding open sea) included 579,700 km2 of habitats generating 494 billion euros of services annually. The future sea-level rise could erode 1.0% [90% confidence interval 0.7–1.5%] of the 2018 area under RCP4.5, and 1.2% [0.7–2.2%] under RCP8.5. The decline in services would be even greater: 4.2% [3.0–6.1%] under RCP4.5, and 5.1% [3.3–8.5%] under RCP8.5. The highest absolute losses would be sustained by salt marshes, while relative losses would be highest in beaches, sands, and dunes. The most affected countries in relative economic terms would be Denmark, Albania, Greece, Estonia, and Finland, but countries such as Germany, the Netherlands, and France would be among those losing the largest share of their coastal ecosystem services. Regional analysis using NUTS 3 regions shows high diversity of the impacts, with many regions along the North Sea and eastern Mediterranean Sea that are heavily affected by coastal erosion-induced loss of ecosystem services. The study highlights the urgency of undertaking mitigation actions.

Floods in the Venice city centre result from the superposition of several factors: astronomical tides; seiches; and atmospherically forced fluctuations, which include storm surges, meteotsunamis, and surges caused by atmospheric planetary waves. All these factors can contribute to positive water height anomalies individually and can increase the probability of extreme events when they act constructively. The largest extreme water heights are mostly caused by the storm surges produced by the sirocco winds, leading to a characteristic seasonal cycle, with the largest and most frequent events occurring from November to March. Storm surges can be produced by cyclones whose centres are located either north or south of the Alps. Historically, the most intense events have been produced by cyclogenesis in the western Mediterranean, to the west of the main cyclogenetic area of the Mediterranean region in the Gulf of Genoa. Only a small fraction of the inter-annual variability in extreme water heights is described by fluctuations in the dominant patterns of atmospheric circulation variability over the Euro-Atlantic sector. Therefore, decadal fluctuations in water height extremes remain largely unexplained. In particular, the effect of the 11-year solar cycle does not appear to be steadily present if more than 100 years of observations are considered. The historic increase in the frequency of floods since the mid-19th century is explained by relative mean sea level rise. Analogously, future regional relative mean sea level rise will be the most important driver of increasing duration and intensity of Venice floods through this century, overcompensating for the small projected decrease in marine storminess. The future increase in extreme water heights covers a wide range, largely reflecting the highly uncertain mass contributions to future mean sea level rise from the melting of Antarctica and Greenland ice sheets, especially towards the end of the century. For a high-emission scenario (RCP8.5), the magnitude of 1-in-100-year water height values at the northern Adriatic coast is projected to increase by 26–35 cm by 2050 and by 53–171 cm by 2100 with respect to the present value and is subject to continued increase thereafter. For a moderate-emission scenario (RCP4.5), these values are 12–17 cm by 2050 and 24–56 cm by 2100. Local subsidence (which is not included in these estimates) will further contribute to the future increase in extreme water heights. This analysis shows the need for adaptive long-term planning of coastal defences using flexible solutions that are appropriate across the large range of plausible future water height extremes.

MedECC has prepared the First Mediterranean Assessment Report (MAR1) on the current state and expected risks of climate and environmental change in the Mediterranean Basin (November 2020). This is the Chapter 6 on future risks management and socio-ecological resilience. The Mediterranean Basin is experiencing major changes in environmental conditions, which can introduce new challenges to the resilience of its natural and human systems. This situation is combined with rapid and spatially diverse socio-economic development in the region, mainly in terms of demographic trends and settlement patterns, thus leading to higher exposure to environmental hazards. Furthermore, new risks are expected to emerge from interactions between drivers and impacts across sectors, thus increasing the vulnerability of natural systems and human populations., This chapter should be cited as: Vafeidis AT, Abdulla AA, Bondeau A, Brotons L, Ludwig R, Portman M, Reimann L, Vousdoukas M, Xoplaki E 2020: Managing future risks and building socio-ecological resilience in the Mediterranean. In: Climate and Environmental Change in the Mediterranean Basin – Current Situation and Risks for the Future. First Mediterranean Assessment Report [Cramer W, Guiot J, Marini K (eds.)] Union for the Mediterranean, Plan Bleu, UNEP/MAP, Marseille, France, pp. 539-588, doi:10.5281/zenodo.7101119.

Floods in the Venice city centre result from the superposition of several factors: astronomical tides, seiches and atmospherically forced fluctuations, which include storm surges, meteotsunamis, and surges caused by planetary waves. All these factors can contribute to positive sea-level anomalies individually and can also result in extreme sea-level events when they act constructively. The largest extreme sea level events have been mostly caused by storm surges produced by the Sirocco winds. This leads to a characteristic seasonal cycle, with the largest and most frequent events occurring from November to March. Storm surges can be produced by cyclones whose centers are located either north or south of the Alps. The most intense historical events have been produced by cyclogenesis in the western Mediterranean, to the west of the main cyclogenetic area of the Mediterranean region in the Gulf of Genoa. Only a small fraction of the interannual variability of extreme sea levels is described by fluctuations in the dominant patterns of atmospheric circulation variability over the Euro-Atlantic sector. Therefore, decadal fluctuations of sea-level extremes remain largely unexplained. In particular, the effect of the 11-year solar cycle appears to be small, non-stationary or masked by other factors. The historic increase in the frequency of extreme sea levels since the mid 19th Century is explained by relative sea level rise, with no long term trend in the intensity of the atmospheric forcing. Analogously, future regional relative mean sea level rise will be the most important driver of increasing duration and intensity of Venice floods through this century, overwhelming the small decrease in marine storminess projected during the 21 century. Consequently, the future increase of extreme sea levels covers a large range, partly reflecting the highly uncertain mass contributions to future mean sea level rise from the melting of Antarctica and Greenland ice-sheets, especially towards the end of the century. In conclusion, for a high emission scenario the magnitude of 1-in-100 year sea level events at the North Adriatic coast is projected to increase up to 65 % and 160 % in 2050 and 2100, respectively, with respect to the present value, and subject to continued increase thereafter. Local subsidence can further contribute to the future increase of extreme sea levels. This analysis shows the need for adaptive planning of coastal defenses with solutions that can be adopted to face the large range of plausible future sea-level extremes.

The Unresolved Obstacles Source Term (UOST) is a general methodology to parameterize the dissipative effects of subscale islands, cliffs and unresolved coastal features in ocean wave models. It can be applied to any numerical scheme and modulates the dissipation with spectral direction. Its applicability to practical contexts is made possible by the development of the software package alphaBetaLab, which given a mesh and a high-resolution bathymetry is able to automatically estimate the cell-dependent transparency coefficients needed by UOST (Mentaschi et al., 2018). Here we provide the documentation of the package, of its architecture and flow, and a couple of illustrative applications. Keywords: Wave modelling, Subscale modelling, Unresolved Obstacles Source Term (UOST), WAVEWATCH III

The world's coastline consists of more than 30% of sandy beaches, many of which are already eroding. Climate change is expected to put more pressure on sandy shorelines, not only because of rising seas, but also from changing weather patterns, affecting the characteristics of marine storms. Here we discuss projections of coastline dynamics along the world's sandy beaches in view of climate change. Using Bruun's rule combined with new global wave projections1 and a dataset on beach slopes2, we find that sea level rise will result in median retreat around -28 m and -35 m under RCP4.5 and RCP8.5, respectively, by the year 2050. the shoreline retreat is projected to climb to around -63 m and -105 m, respectively, by the end of the century. The impact of episodic erosion during storm events will most likely become more severe as sandy beaches will shrink, however, changes in the intensity and characteristics of storms seem to leave an noticeable footprint only in few locations worldwide. Ambient change, extrapolated from historical behaviour3, is expected to contribute signicantly to future sandy beach erosion. However, ambient change can also drive accretion, as is the case along a big part of East Asia. The present findings imply that many sandy beaches worldwide will experience retreat of more than 100 m, i.e. they are very likely to vanish, especially in the absence of accommodating space. The socio-economic implications to tourism, quality of life and the economy can be devastating, especially in small, tourism dependent communities.References:Vousdoukas, M. I. et al. Global probabilistic projections of extreme sea levels show intensication of coastal flood hazard. Nature Communications 9, 2360, doi:10.1038/s41467- 018-04692-w (2018). Athanasiou, P. et al. A global dataset of coastal slopes for coastal recession assessments. Earth System Science Data Discussions, 29, doi:https://doi.org/10.5194/essd-2019-71 (2019). Mentaschi, L., Vousdoukas, M. I., Pekel, J.-F., Voukouvalas, E. & Feyen, L. Global long-term observations of coastal erosion and accretion. Scientic Reports 8, 12876, doi:10.1038/s41598-018-30904-w (2018).

Rising extreme sea levels (ESLs) and continued socioeconomic development in coastal zones will lead to increasing future flood risk along the European coastline. We present a comprehensive analysis of future coastal flood risk (CFR) for Europe that separates the impacts of global warming and socioeconomic development. In the absence of further investments in coastal adaptation, the present expected annual damage (EAD) of €1.25 billion is projected to increase by two to three orders of magnitude by the end of the century, ranging between 93 and €961 billion. The current expected annual number of people exposed (EAPE) to coastal flooding of 102,000 is projected to reach 1.52–3.65 million by the end of the century. Climate change is the main driver of the future rise in coastal flood losses, with the importance of coastward migration, urbanization and rising asset values rapidly declining with time. To keep future coastal flood losses constant relative to the size of the economy, flood defence structures need to be installed or reinforced to withstand increases in ESLs that range from 0.5 to 2.5 m. Climate change is the main driver for future coastal flood risk in Europe. However, in the absence of increased flood protection, damages may rise by two to three orders of magnitude by the end of the century.

An upscaling of flood risk assessment frameworks beyond regional and national scales has taken place during recent years, with a number of large-scale models emerging as tools for hotspot identification, support for international policy-making and harmonization of climate change adaptation strategies. There is, however, limited insight on the scaling effects and structural limitations of flood risk models and, therefore, the underlying uncertainty. In light of this, we examine key sources of epistemic uncertainty in the Coastal Flood Risk (CFR) modelling chain: (i) the inclusion and interaction of different hydraulic components leading to extreme sea-level (ESL); (ii) inundation modelling; (iii) the underlying uncertainty in the Digital Elevation Model (DEM); (iv) flood defence information; (v) the assumptions behind the use of depth-damage functions that express vulnerability; and (vi) different climate change projections. The impact of these uncertainties to estimated Expected Annual Damage (EAD) for present and future climates is evaluated in a dual case study in Faro, Portugal and in the Iberian Peninsula. The ranking of the uncertainty factors varies among the different case studies, baseline CFR estimates, as well as their absolute/relative changes. We find that uncertainty from ESL contributions, and in particular the way waves are treated, can be higher than the uncertainty of the two greenhouse gas emission projections and six climate models that are used. Of comparable importance is the quality of information on coastal protection levels and DEM information. In the absence of large-extent datasets with sufficient resolution and accuracy the latter two factors are the main bottlenecks in terms of large-scale CFR assessment quality.

Global warming is expected to drive increasing extreme sea levels (ESLs) and flood risk along the world’s coastlines. In this work we present probabilistic projections of ESLs for the present century taking into consideration changes in mean sea level, tides, wind-waves, and storm surges. Between the year 2000 and 2100 we project a very likely increase of the global average 100-year ESL of 34–76 cm under a moderate-emission-mitigation-policy scenario and of 58–172 cm under a business as usual scenario. Rising ESLs are mostly driven by thermal expansion, followed by contributions from ice mass-loss from glaciers, and ice-sheets in Greenland and Antarctica. Under these scenarios ESL rise would render a large part of the tropics exposed annually to the present-day 100-year event from 2050. By the end of this century this applies to most coastlines around the world, implying unprecedented flood risk levels unless timely adaptation measures are taken.

Small island states around the world are among the areas most vulnerable to climate change and sea level rise. In this paper, we present results from an innovative methodology for a quantitative assessment of multiple hazards on coastal risks, driven by different hydro-meteorological events, and including the effects of climate change. Moreover, we take an additional step by including in the methodology the option to assess and compare the effectiveness of possible disaster risk reduction measures. The methodology is applied to a real case study at the island of Ebeye (the Republic of the Marshall Islands). An example is provided in which a rock revetment is implemented as a risk reduction measure for the island. Results show that yearly expected damages may increase, by the end of the century, by a factor of three to four, depending on the sea level rise scenario considered, while the number of yearly affected people may double. Putting a cap on the temperature increase (e.g. 1.5 vs. 2 °C) according to the Paris Agreement may reduce damages and number of affected people by about 20 and 15%, respectively. However, impacts for same warming levels can vary substantially among different emission scenarios. Disaster risk reduction measures can be useful for mitigating risks in current and future situations but should be incorporated within long-term adaptive planning for these islands.

Beach cliffing is a wide-spread characteristic of artificially-replenished beaches, which has many undesirable engineering, environmental and economic consequences. A sedimentological study undertaken on the replenished mixed gravel and sand beach of Hayling Island (southern England) has shown that the persisting beach cliff consists typically of three distinct layers. The textural, geochemical and mineralogical analyses of the deposit showed that the development of the cliff, and particularly the formation of the intermediate, densely-packed layer, could be attributed to a series of processes. Firstly, the techniques used to emplace the recharge material on the beach (i.e. placement by heavy dumper trucks/bulldozers) result in a compaction and grain-fracture of the recharge material, and therefore a denser packing arrangement than that expected by its textural characteristics alone. Secondly, percolating water transfers medium- and fine-grained material to deeper parts of the deposit, resulting in the clogging of the interstices between the gravels and the formation of a densely-packed, poorly-sorted layer. The above processes promote the interactions between the clay minerals of the deposit with [Ca2+] cations, resulting in the formation of particular cementing materials, such as Calcium Silicate Hydrates (CSH).

In this study we conducted a comprehensive modeling analysis to identify global trends in extreme wave energy flux (WEF) along coastlines in the 21st century under a high emission pathway (Representative Concentration Pathways 8.5). For the end of the century, results show a significant increase up to 30% in 100 year return level WEF for the majority of the coastal areas of the southern temperate zone, while in the Northern Hemisphere large coastal areas are characterized by a significant negative trend. We show that the most significant long-term trends of extreme WEF can be explained by intensification of teleconnection patterns such as the Antarctic Oscillation, El Niño–Southern Oscillation, and North Atlantic Oscillation. The projected changes will have broad implications for ocean engineering applications and disaster risk management. Especially low-lying coastal countries in the Southern Hemisphere will be particularly vulnerable due to the combined effects of projected relative sea level rise and more extreme wave activities.

Future extreme sea levels (ESLs) and flood risk along European coasts will be strongly impacted by global warming. Yet, comprehensive projections of ESL that include mean sea level (MSL), tides, waves, and storm surges do not exist. Here, we show changes in all components of ESLs until 2100 in view of climate change. We find that by the end of this century, the 100-year ESL along Europe's coastlines is on average projected to increase by 57 cm for Representative Concentration Pathways (RCP)4.5 and 81 cm for RCP8.5. The North Sea region is projected to face the highest increase in ESLs, amounting to nearly 1 m under RCP8.5 by 2100, followed by the Baltic Sea and Atlantic coasts of the UK and Ireland. Relative sea level rise (RSLR) is shown to be the main driver of the projected rise in ESL, with increasing dominance toward the end of the century and for the high-concentration pathway. Changes in storm surges and waves enhance the effects of RSLR along the majority of northern European coasts, locally with contributions up to 40%. In southern Europe, episodic extreme events tend to stay stable, except along the Portuguese coast and the Gulf of Cadiz where reductions in surge and wave extremes offset RSLR by 20–30%. By the end of this century, 5 million Europeans currently under threat of a 100-year ESL could be annually at risk from coastal flooding under high-end warming. The presented dataset is available through this link: http://data.jrc.ec.europa.eu/collection/LISCOAST. Plain Language Summary Future extreme sea levels and flood risk along European coasts will be strongly impacted by global warming. Here, we show changes in all acting components, i.e., sea level rise, tides, waves, and storm surges, until 2100 in view of climate change. We find that by the end of this century the 100-year event along Europe will on average increase between 57 and 81 cm. The North Sea region is projected to face the highest increase, amounting to nearly 1 m under a high emission scenario by 2100, followed by the Baltic Sea and Atlantic coasts of the UK and Ireland. Sea level rise is the main driver of the changes, but intensified climate extremes along most of northern Europe can have significant local effects. Little changes in climate extremes are shown along southern Europe, with the exception of a projected decrease along the Portuguese coast and the Gulf of Cadiz, offseting sea level rise by 20–30%. By the end of this century, 5 million Europeans currently under threat of a 100-year coastal flood event could be annually at risk from coastal flooding under high-end warming.

The present contribution constitutes the first comprehensive attempt to (a) record the spatial characteristics of the beaches of the Aegean archipelago (Greece), a critical resource for both the local and national economy, and (b) provide a rapid assessment of the impacts of the long-term and episodic sea level rise (SLR) under different scenarios. Spatial information and other attributes (e.g., presence of coastal protection works and backshore development) of the beaches of the 58 largest islands of the archipelago were obtained on the basis of remote-sensed images available on the web. Ranges of SLR-induced beach retreats under different morphological, sedimentological and hydrodynamic forcing, and SLR scenarios were estimated using suitable ensembles of cross-shore (1-D) morphodynamic models. These ranges, combined with empirically derived estimations of wave run-up induced flooding, were then compared with the recorded maximum beach widths to provide ranges of retreat/erosion and flooding at the archipelago scale. The spatial information shows that the Aegean pocket beaches may be particularly vulnerable to mean sea level rise (MSLR) and episodic SLRs due to (i) their narrow widths (about 59 % of the beaches have maximum widths

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Climate change driven sea level rise (SLR) is expected to rise with even higher rates during the second half of the present century. This will exacerbate shoreline retreat of sandy coasts, which comprise one third of the global coastline. Sandy coasts have high touristic and ecological value while they are the first level of defense against storms, protecting valuable infrastructures and buildings. Therefore, in recent years, large scale risk assessments are considered useful tools for the guidance of policy makers to identify high risk hotspots. Reliable input data at this scale are required in order to make useful estimations. Among others, crucial data to assess the impact of SLR on shoreline retreat are the detection of different coastal types and, in particular, of sandy erodible beaches, and the nearshore slope, which is usually assumed to be uniform.The important issue of input data uncertainty and spatial variation and consequent impact on predictions has been so far ignored in most large-scale studies. Estimates of shoreline retreat are however very sensitive to the variation in these inputs. Here we quantify SLR driven potential shoreline retreat and consequent land loss in Europe during the 21st century by employing different combinations of geophysical datasets for (a) the location of sandy beaches and (b) their nearshore slopes. For the estimation of the shoreline retreat, the Bruun Rule is used, which offers a suitable approach for a first approximation of erosion impacts at large scales. Sea level rise projections associated with the moderate-emission- mitigation-policy (RCP4.5) and the high-end, business-as-usual scenario (RCP8.5) are used as boundary conditions. The location of sandy beaches is determined from two different datasets. One is based on manual visual estimation from satellite images and the other on automatic detection from satellite images using machine learning techniques. For nearshore slopes we apply the commonly used constant slope assumption of 1:100 and a newly produced global dataset which captures the spatial variation of coastal slopes.With this approach, we create four different combinations for each SLR scenario, for which we estimate and compare land loss at EU, country and NUTS3 regional level. We find that the land loss estimations for each combination can differ significantly, especially at the regional and local level. At the European or country level, even though differences in total land loss projections can be significant, they can be concealed by the spatial aggregation of the results. Using data-based spatially-varying nearshore slope data, a European averaged median shoreline retreat of 97 m (54 m) is projected under RCP 8.5 (4.5) by year 2100, relative to the baseline year 2010. This retreat would translate to 2,500 km2 (1,400 km2) of land loss. A variance-based global sensitivity analysis indicates that the uncertainty associated with the choice of geophysical datasets can contribute up to 45% (26%) of the variance in land loss projections for Europe by 2050 (2100).

The Unresolved Obstacles Source Term (UOST) is a general methodology for parameterizing the dissipative effects of subscale islands, cliffs, and other unresolved features in ocean wave models. Since it separates the dissipation from the energy advection scheme, it can be applied to any numerical scheme or any type of mesh. UOST is now part of the official release of WAVEWATCH III, and the freely available package alphaBetaLab automates the estimation of the parameters needed for the obstructed cells. In this contribution, an assessment of global regular and unstructured (triangular) wave models employing UOST is presented. The results in regular meshes show an improvement in model skill, both in terms of spectrum and of integrated parameters, thanks to the UOST modulation of the dissipation with wave direction, and to considering the cell geometry. The improvement is clear in wide areas characterized by the presence of islands, like the whole central-western Pacific Basin. In unstructured meshes, the use of UOST removes the need of high resolution in proximity of all small features, leading to (a) a simplification in the development process of large scale and global meshes, and (b) a significant decrease of the computational demand of accurate large-scale models.

Sea level rise (SLR) will cause shoreline retreat of sandy coasts in the absence of sand supply mechanisms. These coasts have high touristic and ecological value and provide protection of valuable infrastructures and buildings to storm impacts. So far, large-scale assessments of shoreline retreat use specific datasets or assumptions for the geophysical representation of the coastal system, without any quantification of the effect that these choices might have on the assessment. Here we quantify SLR driven potential shoreline retreat and consequent coastal land loss in Europe during the twenty-first century using different combinations of geophysical datasets for (a) the location and spatial extent of sandy beaches and (b) their nearshore slopes. Using data-based spatially-varying nearshore slope data, a European averaged SLR driven median shoreline retreat of 97 m (54 m) is projected under RCP 8.5 (4.5) by year 2100, relative to the baseline year 2010. This retreat would translate to 2,500 km2 (1,400 km2) of coastal land loss (in the absence of ambient shoreline changes). A variance-based global sensitivity analysis indicates that the uncertainty associated with the choice of geophysical datasets can contribute up to 45% (26%) of the variance in coastal land loss projections for Europe by 2050 (2100). This contribution can be as high as that associated with future mitigation scenarios and SLR projections.

Compound flooding arises from storms causing concurrent extreme meteorological tides (that is the superposition of storm surge and waves) and precipitation. This flooding can severely affect densely populated low-lying coastal areas. Here, combining output from climate and ocean models, we analyse the concurrence probability of the meteorological conditions driving compound flooding. We show that, under a high emissions scenario, the concurrence probability would increase globally by more than 25% by 2100 compared to present. In latitudes above 40o north, compound flooding could become more than 2.5 times as frequent, in contrast to parts of the subtropics where it would weaken. Changes in extreme precipitation and meteorological tides account for most (77% and 20%, respectively) of the projected change in concurrence probability. The evolution of the dependence between precipitation and meteorological tide dominates the uncertainty in the projections. Our results indicate that not accounting for these effects in adaptation planning could leave coastal communities insufficiently protected against flooding., Concurrent coastal extremes - storm surges and flooding from precipitation - are 2.5 times as frequent in latitudes higher than 40∘N under a high emission scenario by 2100 compared to today, according to an analysis of climate and ocean model output.

International audience

More intense precipitation will increase the flood potential from concurring storm surges and precipitation in the future., In low-lying coastal areas, the co-occurrence of high sea level and precipitation resulting in large runoff may cause compound flooding (CF). When the two hazards interact, the resulting impact can be worse than when they occur individually. Both storm surges and heavy precipitation, as well as their interplay, are likely to change in response to global warming. Despite the CF relevance, a comprehensive hazard assessment beyond individual locations is missing, and no studies have examined CF in the future. Analyzing co-occurring high sea level and heavy precipitation in Europe, we show that the Mediterranean coasts are experiencing the highest CF probability in the present. However, future climate projections show emerging high CF probability along parts of the northern European coast. In several European regions, CF should be considered as a potential hazard aggravating the risk caused by mean sea level rise in the future.

This contribution presents the high-resolution Pan-European storm surge (SSL) dataset, ANYEU-SSL, produced with the SCHISM circulation model. The dataset covers 40 years (1979–2018) of SSL data along the European coastline with 3-hour temporal resolution and has been extensively validated for the period spanning from 1979 to 2016, considering the whole time series, as well as for the extreme SSL values. Validation against tidal gauge data shows an average RMSE of 0.10 m, and RMSE below 0.12 m in 75% of the tidal gauges. Comparisons with satellite altimetry data show average RMSE of 0.07 m. SSL trends are estimated as an example of a potential application case of the dataset. The results indicate an overall latitudinal gradient in the trend of the extreme storm surge magnitude for the period 1979–2016. SSLs appear to increase in areas with latitudes >50 °N and to decrease in the lower latitudes. Additionally, a seasonal variation of the extreme SSL, particularly strong in the northern areas, has been observed. The dataset is publicly available and aspires to provide the scientific community with an important data source for the study of storm surge phenomena and consequential impacts, either on large or local scales. Keywords: Storm surge, Coastal flooding, Marine storms, Natural hazards, Numerical modelling

Transport infrastructure is exposed to natural hazards all around the world. Here we present the first global estimates of multi-hazard exposure and risk to road and rail infrastructure. Results reveal that ~27% of all global road and railway assets are exposed to at least one hazard and ~7.5% of all assets are exposed to a 1/100 year flood event. Global Expected Annual Damages (EAD) due to direct damage to road and railway assets range from 3.1 to 22 billion US dollars, of which ~73% is caused by surface and river flooding. Global EAD are small relative to global GDP (~0.02%). However, in some countries EAD reach 0.5 to 1% of GDP annually, which is the same order of magnitude as national transport infrastructure budgets. A cost-benefit analysis suggests that increasing flood protection would have positive returns on ~60% of roads exposed to a 1/100 year flood event., Spatial distribution has been rarely studied in global disaster risk models. Here the authors address damaged networked infrastructure at the asset level for a wider range of hazards and reveal a global Expected Annual Damages ranging from $3.1 to 22 billion with a particular vulnerability of transport infrastructure in Small Island Developing States.

The dependence between extreme storm surges and wind waves is assessed statistically along the global coasts using the outputs of two numerical models consistently forced with the same atmospheric fields. We show that 55% of the world coastlines face compound storm surge wave extremes. Hence, for a given level of probability, neglecting these dependencies leads to underestimating extreme coastal water levels. Dependencies are dominant in midlatitudes and are likely underestimated in the tropics due to limited representation of tropical cyclones. Furthermore, we show that in half of the areas with dependence, the estimated probability of occurrence of coastal extreme water levels increases significantly when it is accounted for. Translated in terms of return periods, this means that along 30% of global coastlines, extreme water levels expected at most once in a century without considering dependence between storm surges and waves become a 1 in 50-year event., This study was supported by the ERA4CS INSeaPTION project (grants 690462 and PCIN‐2017‐038).

This contribution presents the results of a study on the shoreline variability of a natural perched urban beach (Ammoudara, N. Crete, Greece). Shoreline variability was monitored in high spatio-temporal resolution using time series of coastal video images and a novel, fully automated 2-D shoreline detection algorithm. Ten-month video monitoring showed that cross-shore shoreline change was, in some areas, up to 8 m with adjacent sections of the shoreline showing contrasting patterns of beach loss or gain. Variability increased in spring/early summer and stabilized until the end of the summer when partial beach recovery commenced. Correlation of the patterns of beach change with wave forcing (as recorded at an offshore wave buoy) is not straightforward; the only discernible association was that particularly energetic waves from the northern sector can trigger changes in the patterns of shoreline variability and that increased variability might be sustained by increases in offshore wave steepness. It was also found that the fronting beachrock reef exerts significant geological control on beach hydrodynamics. Hydrodynamic modelling and observations during an energetic event showed that the reef can filter wave energy in a highly differential manner, depending on its local architecture. In some areas, the reef allows only low-energy waves to impinge on the shoreline, whereas elsewhere penetration of higher waves is facilitated by the low elevation and limited width of the reef or by the presence of an inlet. Wave/reef interaction can also generate complex circulation patterns, including rip currents that appeared to be also constrained by the reef architecture.

While reported losses of climate-related hazards are at historically high levels, climate change is likely to enhance the risk posed by extreme weather events. Several regions are likely to be exposed to multiple climate hazards, yet their modeling in a joint scheme is still at the early stages. A multi-hazard framework to map exposure to multiple climate extremes in Europe along the twenty-first century is hereby presented. Using an ensemble of climate projections, changes in the frequency of heat and cold waves, river and coastal flooding, streamflow droughts, wildfires and windstorms are evaluated. Corresponding variations in expected annual exposure allow for a quantitative comparison of hazards described by different process characteristics and metrics. Projected changes in exposure depict important variations in hazard scenarios, especially those linked to rising temperatures, and spatial patterns largely modulated by local climate conditions. Results show that Europe will likely face a progressive increase in overall climate hazard with a prominent spatial gradient towards south-western regions mainly driven by the rise of heat waves, droughts and wildfires. Key hotspots emerge particularly along coastlines and in floodplains, often highly populated and economically pivotal, where floods and windstorms could be critical in combination with other climate hazards. Projected increases in exposure will be larger for very extreme events due to their pronounced changes in frequency. Results of this appraisal provide useful input for forthcoming European disaster risk and adaptation policy.

This paper investigates the potential of using a polynomial radial basis function (RBF) neural network to extract the shoreline position from coastal video images. The basic structure of the proposed network encompasses a standard RBF network module, a module of nodes that use Chebyshev polynomials as activation functions, and an inference module. The experimental setup is an operational coastal video monitoring system deployed in two sites in Southern Europe to generate variance coastal images. Thehistogram of each image isapproximated by non-linear regression, and associated witha manually extracted intensity threshold value that quantifies the shoreline position. The key idea is to use the set of the resulting regression parameters as input data, and the intensity threshold values as output data of the network. In summary, the data set is extracted by quantifying the qualitative image information, and the proposed network takes the advantage of the powerful approximation capabilities of the Chebyshev polynomials by utilizing a small number of coefficients. For comparative reasons, we apply a polynomial RBF network trained by fuzzy clustering, and a feed-forward neural network trained by the back propagation algorithm. The comparison criteria used are the standard mean square error; the data return rates, and the root mean square error of the cross- shore shoreline position, calculated against the shorelines extracted by the aforementioned annotated threshold values. The main conclusions of the simulation study are: (a) the proposed method outperforms the other networks, especially in extracting the shoreline from images used as testing data; (b) for higher polynomial orders it obtains data return rates greater than 84%, and the root mean square error of the cross-shore shoreline position is less than 1.8 meters.

Operational forecasting systems are important for disaster risk reduction. In this work we implement a coupled storm surge and tidal model on an unstructured grid over Europe towards the development of a pan-European Storm Surge Forecasting System (EU-SSF). The skill to predict tidal, surge and total water levels was evaluated based on measurements from 208 tidal gauge stations. Results show satisfactory performance for the two atmospheric forcing datasets tested, a High Resolution Forecast and ERA-INTERIM reanalysis, both provided by the European Center for Medium range Weather Forecast. For tidal predictions, the total RSS is equal to 0.197 m, lower than the values estimated by the global tidal model FES2004, and outperformed only by FES2012 (RSS = 0.05 m), which however is a product of data assimilation. Storm surge validation results show good predictive skill, with 0.04 m < RMSE < 0.21 m and %RMSE within 4%–22%. Coupling with tides results in improved storm surge level predictions, with RMSE reducing by up to 0.033 m. The areas benefiting most from the coupling are the North Sea and the English Channel, resulting in up to 2% reduction of the %RMSE. Increasing the resolution of atmospheric forcing also improves the predictive skill, leading to a reduction of RMSE up to 0.06 m in terms of the extremes, especially in shallow areas where wind is the main driver for surge production. We propose a setup for operational pan-European storm surge forecasting combining tidal levels from the FES2012 model and storm surge residuals from the EU-SSF setup which couples meteorological and astronomic tides.

Statistical approaches to study extreme events require, by definition, long time series of data. In many scientific disciplines, these series are often subject to variations at different temporal scales that affect the frequency and intensity of their extremes. Therefore, the assumption of stationarity is violated and alternative methods to conventional stationary extreme value analysis (EVA) must be adopted. Using the example of environmental variables subject to climate change, in this study we introduce the transformed-stationary (TS) methodology for non-stationary EVA. This approach consists of (i) transforming a non-stationary time series into a stationary one, to which the stationary EVA theory can be applied, and (ii) reverse transforming the result into a non-stationary extreme value distribution. As a transformation, we propose and discuss a simple time-varying normalization of the signal and show that it enables a comprehensive formulation of non-stationary generalized extreme value (GEV) and generalized Pareto distribution (GPD) models with a constant shape parameter. A validation of the methodology is carried out on time series of significant wave height, residual water level, and river discharge, which show varying degrees of long-term and seasonal variability. The results from the proposed approach are comparable with the results from (a) a stationary EVA on quasi-stationary slices of non-stationary series and (b) the established method for non-stationary EVA. However, the proposed technique comes with advantages in both cases. For example, in contrast to (a), the proposed technique uses the whole time horizon of the series for the estimation of the extremes, allowing for a more accurate estimation of large return levels. Furthermore, with respect to (b), it decouples the detection of non-stationary patterns from the fitting of the extreme value distribution. As a result, the steps of the analysis are simplified and intermediate diagnostics are possible. In particular, the transformation can be carried out by means of simple statistical techniques such as low-pass filters based on the running mean and the standard deviation, and the fitting procedure is a stationary one with a few degrees of freedom and is easy to implement and control. An open-source MATLAB toolbox has been developed to cover this methodology, which is available at https://github.com/menta78/tsEva/ (Mentaschi et al., 2016).

Changes in coastal morphology have broad consequences for the sustainability of coastal communities, structures and ecosystems. Although coasts are monitored locally in many places, understanding long-term changes at a global scale remains a challenge. Here we present a global and consistent evaluation of coastal morphodynamics over 32 years (1984–2015) based on satellite observations. Land losses and gains were estimated from the changes in water presence along more than 2 million virtual transects. We find that the overall surface of eroded land is about 28,000 km2, twice the surface of gained land, and that often the extent of erosion and accretion is in the order of km. Anthropogenic factors clearly emerge as the dominant driver of change, both as planned exploitation of coastal resources, such as building coastal structures, and as unforeseen side effects of human activities, for example the installment of dams, irrigation systems and structures that modify the flux of sediments, or the clearing of coastal ecosystems, such as mangrove forests. Another important driver is the occurrence of natural disasters such as tsunamis and extreme storms. The observed global trend in coastal erosion could be enhanced by Sea Level Rise and more frequent extreme events under a changing climate.

The published version of this article is available at https://advances.sciencemag.org/content/5/9/eaaw5531. Compound flooding (CF) is an extreme event taking place in low-lying coastal areas as a result of co-occurring high sea level and large amounts of runoff, caused by precipitation. The impact from the two hazards occurring individually can be significantly lower than the result of their interaction. Both the risk of storm surges and heavy precipitation, as well as their interplay is likely to change in response to anthropogenic global warming. Despite CF relevance, a comprehensive risk assessment beyond individual locations at the country scale is missing. In particular, no studies have examined possible future CF risk. Here we estimate the potential CF risk along the European coasts both for present and future climate according to the business-as-usual (RCP8.5) scenario. Under current climate conditions, the locations experiencing the highest risk are mostly located along the Mediterranean Sea. However, future climate projections show emerging risk along parts of the Atlantic coast and the North Sea. The increase of the risk is mostly driven by an intensification of precipitation extremes. In several European regions, increasing CF risk should be considered as a potential hazard aggravating the risk caused by the mean sea level rise (SLR).

Coastal flood maps covering the whole European continent have become available in recent years. However, their ability to complement or replace high-resolution local flood maps was not investigated so far. In this paper we compare pan-European estimates of extreme sea levels and coastal flood extents at given return periods with observations and high-resolution reference maps. The analysis is done for two pan-European assessments and one global study. We find that whereas the models have good accuracy in estimating storm surge heights, large disparities exist between the large-scale flood maps and four local maps of flood extents from England, the Netherlands, Poland and France. Moreover, the accuracy of the underlying digital elevation model and assumptions about flood protection existing in a given area influence significantly the results. Additionally, the first pan-European projection of temporal trends in the size of flood zones is presented, with and without assuming flood protection levels.

The interaction between storm surges and inland runoff has been gaining increasing attention recently, as they have the potential to result in compound floods. In Europe, several flood events of this type have been recorded in the past century in Belgium, France, Ireland, Italy and United Kingdom. Here, we investigate the probability of joint occurrence of storm surges, precipitation, river discharges and waves. A coincidence of those factors have a potential to cause compound floods. We use several datasets covering most of Europe, including observations and data from the European Flood Awareness System (EFAS), ERA-Interim climate reanalysis and a regional climate model within the CORDEX framework, and carry out a statistical analysis based on copulas to assess the likelihood of joint occurrence. Further, we synthesize the joint probability of occurrence of extreme compound events, and their intensity, in the form of a composite index, thus identifying areas where compound floods could be of most concern. The results show considerable regional differences in dependency structure and the resulting joint probability of extreme surge, precipitation and river discharge events. In southern Europe the probability of joint occurrence of storm surge and precipitation is relatively high due to significant flash flood hazard. In northern Europe, along the main corridor of winter storms, dependency between surges and river discharges is higher than elsewhere, with large differences between west-facing and east-facing coasts. The occurrence of compound floods in most of the Nordic countries and along the Black Sea is very unlikely. The results allow the identification of areas at risk from compound flooding. Future studies that utilize statistical and physical methods are recommended to assess interactions between surges and inland runoff at a local scale.