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On October 30th, 2020, a magnitude 7.0 earthquake offshore off the northern coast of Samos, Greece, generated a tsunami that impacted the nearshore Greek islands and the Aegean coastline of Turkey. Here, we describe detailed results from several post-event field surveys, and report first wave arrival timing and polarity information as well as tsunami height/runup measurements, from five islands. In Chios, wave runup reached 1.38 m, in Samos ~ 3 m, in Fourni 1.57 m, in Thimena 1.46 m, and in Ikaria 1.18 m. This event marks two milestones. One, the General Secretariat for Civil Protection of Greece, disseminated a message through Greece's 1-1-2 Emergency Communications Service to all cell phones in the eastern Aegean geographical region, warning recipients to stay away from coastal areas. According to eyewitnesses, the message was received ~ 3-5 min prior to the second and largest flood in Vathi, as the first flood had not sufficiently alarmed the local authorities to evacuate residents. Two, we were able to infer complete tsunami hydrographs from measurements for the first two floods in Vathi, which suggests that the water level rose to about one meter overland flow depth in one minute.

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.

The long-term offshore wind characteristics in the Mediterranean Sea are assessed using the ERA-Interim dataset for the period 1979–2014. Three main aspects of the wind climate analysis are examined in detail; the spatio-temporal behaviour (including variability characteristics) of wind speed and direction for the annual and monthly time scale; the joint association of wind speed and direction for the annual and monthly time scale, and; the wind speed trends and wind direction changes. From this analysis, the systematic wind flow patterns are identified and the general features of the wind climatology patterns are revealed. The most typical examples of stable and intense regional winds are the Mistral (throughout the year) in the Gulf of Lion and the Etesians (during summer) in the Aegean Sea. High values of mean annual variability of wind speed occur over the western part of the basin (Balearic, Tyrrhenian and Ligurian sub-basins) as well as over the Adriatic and N Aegean Seas, and the E Levantine Basin. Moreover, the assessment of the joint association of wind speed and direction indicates that areas with high values of linear–circular correlation are the ones characterized by intense wind climate. As regards, long-term changes of wind speed and direction, the linear trend for the former and the angular distance for the latter variable are provided. The fastest increasing wind speed trends are observed in the Ionian, the N Tyrrhenian and N Adriatic Seas, the eastern part of the Algerian Basin up to Balearic Isl. and the western part of the S Levantine Basin while the fastest decreasing ones are observed offshore Monaco, the central Aegean and the E Alboran Seas and the N Levantine Basin. The highest values of angular variance and mean angular distances are depicted for the Ligurian, Balearic and Alboran Seas.

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 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.

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.

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).

The development of offshore wind farms (OWFs) and the establishment of marine protected areas (MPAs) comprise two main elements for the production of clean energy, and the simultaneous maintenance and protection of biodiversity in the Mediterranean and Black seas. Successful, efficient, and sustainable coupling of these two aspects presumes that the criteria for selecting suitable locations for the deployment of OWFs should not only include technical-engineering terms (e.g. high wind energy efficiency, bottom suitability, inland infrastructures) but also ecological–environmental considerations (e.g. the least possible impact on biodiversity, ecosystem functioning) and socio-economic aspects (e.g. effects on coastal and marine activities, development of marine spatial planning). In the context of the FP7 CoCoNet project, the integration between OWFs and MPAs is based on four main steps: (i) the identification of existing (networks of) MPAs focusing on the biodiversity distribution patterns and current legislation, (ii) the coupling of offshore wind potential within networks of MPAs, (iii) the evaluation of the knowledge gained up to date and the theoretical approaches at the two pilot sites of the Mediterranean and Black sea basins, and (iv) the development of the "Smart Wind Chart", a convenient and rational tool addressed to scientists and policy makers for the evaluation of maritime policy management schemes. The latter step comprises the core of this work.

This contribution presents an assessment of the potential vulnerabilities to climate variability and change (CV & C) of the critical transportation infrastructure of Caribbean Small Island Developing States (SIDS). It focuses on potential operational disruptions and coastal inundation forced by CV & C on four coastal international airports and four seaports in Jamaica and Saint Lucia which are critical facilitators of international connectivity and socioeconomic development. Impact assessments have been carried out under climatic conditions forced by a 1.5°C specific warming level (SWL) above pre-industrial levels, as well as for different emission scenarios and time periods in the twenty-first century. Disruptions and increasing costs due to, e.g., more frequent exceedance of high temperature thresholds that could impede transport operations are predicted, even under the 1.5°C SWL, advocated by the Alliance of Small Island States (AOSIS) and reflected as an aspirational goal in the Paris Climate Agreement. Dynamic modeling of the coastal inundation under different return periods of projected extreme sea levels (ESLs) indicates that the examined airports and seaports will face increasing coastal inundation during the century. Inundation is projected for the airport runways of some of the examined international airports and most of the seaports, even from the 100-year extreme sea level under 1.5°C SWL. In the absence of effective technical adaptation measures, both operational disruptions and coastal inundation are projected to increasingly affect all examined assets over the course of the century.

Parameterizing the dissipative effects of small, unresolved coastal features, is fundamental to improve the skills of wave models. The established technique to deal with this problem consists in reducing the amount of energy advected within the propagation scheme, and is currently available only for regular grids. To find a more general approach, Mentaschi et al., 2015b formulated a technique based on source terms, and validated it on synthetic case studies. This technique separates the parameterization of the unresolved features from the energy advection, and can therefore be applied to any numerical scheme and to any type of mesh. Here we developed an open-source library for the estimation of the transparency coefficients needed by this approach, from bathymetric data and for any type of mesh. The spectral wave model WAVEWATCH III was used to show that in a real-world domain, such as the Caribbean Sea, the proposed approach has skills comparable and sometimes better than the established propagation-based technique.

Statistical approaches to study extreme events require by definition long time series of data. The climate is subject to natural and anthropogenic variations at different temporal scales, leaving their footprint on the frequency and intensity of climatic and hydrological extremes, therefore assumption of stationarity is violated and alternative methods to conventional stationary Extreme Value Analysis (EVA) need to be adopted. In this study we introduce the Transformed-Stationary (TS) methodology for non-stationary EVA. This approach consists in (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 allows a comprehensive formulation of non stationary GEV/GPD models with 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 ones from (a) a stationary EVA on quasi-stationary slices of non stationary series and (b) the previously applied non stationary EVA approach. However, the proposed technique comes with advantages in both cases, as in contrast to (a) it uses the whole time horizon of the series for the estimation of the extremes, allowing for a more accurate estimation of large return levels; and with respect to (b) it decouples the detection of non-stationary patterns from the fitting of the extreme values 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 running mean and standard deviation, and the fitting procedure is a stationary one with a few degrees of freedom and easy to implement and control. An open-source MATLAB toolbox has been developed to cover this methodology, available at https://bitbucket.org/menta78/tseva.

Summarization: We conduct a comprehensive study of the Amorgos, Greece earthquake and tsunami of 1956 July 09, the largest such event in the Aegean Sea in the 20th century. Systematic relocation of the main shock and 34 associated events defines a rupture area measuring 75 × 40 km. The use of the Preliminary Determination of Focal Mechanism algorithm resolves the longstanding controversy about the focal geometry of the event, yielding a normal faulting mechanism along a plane dipping to the southeast, which expresses extensional tectonics in the back arc behind the Hellenic subduction zone. The seismic moment of 3.9 × 1027 dyn cm is the largest measured in the past 100 yr in the Mediterranean Basin. A quantitative database of 68 values of tsunami run-up was built through the systematic interview, over the past 5 yr, of elderly eyewitness residents of 16 Aegean islands and the Turkish coast of Asia Minor. It confirms values of up to 20 m on the southern coast of Amorgos, 10 m on Astypalaia, and up to 14 m on the western coast of Folegandros, 80 km to the west of the epicentre. These values, largely in excess of the inferred seismic slip at the source, and their concentration along isolated segments of fault, are incompatible with the generation of the tsunami by the seismic dislocation, and require an ancillary source, in the form of a series of landslides triggered by the earthquake and/or its main aftershocks, a model confirmed by hydrodynamic simulations using both the dislocation source and models of landslide sources. Παρουσιάστηκε στο: Geophysical Journal International

Current climate policy and issues of energy security mean wind farms are being built at an increasing rate to meet energy demand. As wind farm development is very likely in the Mediterranean Sea, we provide an assessment of the offshore wind potential and identify expected biological effects of such developments in the region. We break new ground here by identifying potential offshore wind farm (OWF) “hotspots” in the Mediterranean. Using lessons learned in Northern Europe, and small-scale experiments in the Mediterranean, we identify sensitive species and habitats that will likely be influenced by OWFs in both these hotspot areas and at a basin level. This information will be valuable to guide policy governing OWF development and will inform the industry as and when environmental impact assessments are required for the Mediterranean Sea, SI

Storm surges are an important coastal hazard component and it is unknown how they will evolve along Europe’s coastline in view of climate change. In the present contribution, the hydrodynamic model Delft3D-Flow was forced by surface wind and atmospheric pressure fields from a 8-member climate model ensemble in order to evaluate dynamics in storm surge levels (SSL) along the European coastline (1) for the baseline period 1970–2000; and (2) during this century under the Representative Concentration Pathways RCP4.5 and RCP8.5. Validation simulations, spanning from 2008 to 2014 and driven by ERA-Interim atmospheric forcing, indicated good predictive skill (0.06 m