196,102 research outputs found
Extreme sea levels on the rise along Europe’s coasts
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 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
A Pan-European high resolution storm surge hindcast
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
alphaBetaLab: Automatic estimation of subscale transparencies for the Unresolved Obstacles Source Term in ocean wave modelling
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
A Pan-European high resolution storm surge hindcast
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
Sandy coastlines under threat of erosion
Sandy beaches occupy more than one-third of the global coastline1 and have high socioeconomic value related to recreation, tourism and ecosystem services2. Beaches are the interface between land and ocean, providing coastal protection from marine storms and cyclones3. However the presence of sandy beaches cannot be taken for granted, as they are under constant change, driven by meteorological4,5, geological6 and anthropogenic factors1,7. A substantial proportion of the world’s sandy coastline is already eroding1,7, a situation that could be exacerbated by climate change8,9. Here, we show that ambient trends in shoreline dynamics, combined with coastal recession driven by sea level rise, could result in the near extinction of almost half of the world’s sandy beaches by the end of the century. Moderate GHG emission mitigation could prevent 40% of shoreline retreat. Projected shoreline dynamics are dominated by sea level rise for the majority of sandy beaches, but in certain regions the erosive trend is counteracted by accretive ambient shoreline changes; for example, in the Amazon, East and Southeast Asia and the north tropical Pacific. A substantial proportion of the threatened sandy shorelines are in densely populated areas, underlining the need for the design and implementation of effective adaptive measures.Accepted Author ManuscriptCoastal Engineerin
Climatic and socioeconomic controls of future coastal flood risk in Europe
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
Parameterizing unresolved obstacles with source terms in wave modeling: A real-world application
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
Dr. Duane M. Jackson, Morehouse College, July 2011
This video is a conversation with Dr. Duane M. Jackson. Dr. Jackson talks about his paper, "Recall and the Serial Position Effect: The Role of Primacy and Recency on Accounting Students' Performance." Jackie Daniel, AUC Woodruff Library, is the interviewer
The transformed-stationary approach: a generic and simplified methodology for non-stationary extreme value analysis
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).JRC.E.1 - Disaster Risk Managemen
Global changes of extreme coastal wave energy fluxes triggered by intensified teleconnection patterns
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
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