313 research outputs found
Parameterizing unresolved obstacles with source terms in wave modeling: A real-world application
No full textExtreme sea levels on the rise along Europe’s coasts
No full textFuture 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 ESL until 2100 in view of climate change. We find that by the end of this century the 100-year event ESL along Europe’s coastlines will on average increase by 57 cm for RCP4.5 and 81 cm for RCP8.5. The North Sea region will 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 the main driver of the projected rise in ESL, with increasing dominance towards 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.JRC.E.1 - Disaster Risk Managemen
An object-oriented signal processing environment: the knowledge-based signal processing package
No full text"October 1984."Includes bibliographical references (p. 63) and index.Supported by Advanced Research Projects Agency, monitored by ONR. N00014-81-K-0742 NR-049-506. Supported by Sanders Associates, and an Amoco Foundation Fellowship.Software authors: Webster P. Dove and Cory Meyers ; Document author: Evangelos E. Milios
Global changes of extreme coastal wave energy fluxes triggered by intensified teleconnection patterns
No full textIn 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
PARMENIDES AND THE HORSE OF IBYCUS. THE HIDDEN MEANING OF THE PERSONIFICATION AND ITS ROLE IN THE DIALOGUE OF THE PARMENIDES
No full textIn this essay, the function of the personification of Parmenides himself with the horse of Ibycus in Plato's Parmenides will be elaborated. The analytical process of this reference by Parmenides will focus to demonstrate that the personification is an allegorical element of Plato whose role in the dialogue is crucial for the understanding of the author's objective about the second more extended part of the Parmenides. © Evangelos Rousakis, 2024
Climatic and socioeconomic controls of future coastal flood risk in Europe
No full textRising 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
Global long-term observations of coastal erosion and accretion
No full textChanges 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
Parameterizing unresolved obstacles with source terms in wave modeling: A real-world application
No full textParameterizing 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
The transformed-stationary approach: a generic and simplified methodology for non-stationary extreme value analysis
No full textStatistical 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).JRC.E.1 - Disaster Risk Managemen
Correction to: Safety of same-day discharge versus overnight stay strategy following cardiac device implantations: a high-volume single-centre experience (Journal of Interventional Cardiac Electrophysiology, (2022), 66, 2, (471-481), 10.1007/s10840-022-01319-5)
No full textIn this article the author name Evangelos Oikonomou was incorrectly written as Evangelos K. Oikonomou. The original article has been corrected. © 2022 The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature
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