<p>Storm surges pose an increasing risk to coastline communities. These events, combined with high tide, can result in coastal flooding. To reduce the impact of storm surges, an accurate estimate of coastal flood risk is necessary. Specifically, estimates are required for the return level of sea levels (still water), which is the level with annual exceedance probability <em>p</em>. This estimate is used as an input to determine the height for a coastal defence, such as a sea wall. The return level estimation requires statistical analysis based on extreme value theory, as we need to know about the frequency of events that are more extreme than those previously observed.</p><p>Large storm surges exhibit seasonality, they are typically at their worst in the winter and least extreme in the summer. This seasonal pattern differs from that of the tide, whose seasonality is driven astronomically, resulting in tidal peaks at the spring and autumn equinoxes. Hence, the worst levels of these two components of still water level are likely to peak at different times in the year, and so statistical methods that treat them as independent variables are likely to over-estimate return levels.</p><p>We focus on the skew surge: the difference between the observed and predicted high water within a tidal cycle. Williams et al. (2016) show that tide and skew surge are independent conditional on the time of year. Batstone et al. (2013) used this property to derive estimates used for UK coastal flood defences. They used generalised Pareto distributions for the skew surge tail but did not account for the separate seasonality of tide and skew surge.</p><p>This work aims to model how the distribution of skew surges changes over a year and we combine our results with the known seasonality of tides to derive estimates of still water level return levels. We compare our results with the Batstone et al. (2013) approach at a few locations on the UK coastline.</p><p>References:</p><p>Batstone, C., Lawless, M., Tawn, J., Horsburgh, K., Blackman, D., McMillan, A., Worth, D., Laeger, S. and Hunt, T., 2013. A UK best-practice approach for extreme sea-level analysis along complex topographic coastlines. Ocean Engineering, 71, pp.28-39.</p><p>Williams, J., Horsburgh, K.J., Williams, J.A. and Proctor, R.N., 2016. Tide and skew surge independence: New insights for flood risk. Geophysical Research Letters, 43(12), pp.6410-6417.</p>

Beaches are both sensitive and critical components of the coastal systems, as they are particularly vulnerable to environmental change (e.g., the sea level rise) and form valuable coastal ecosystems and economic resources. The objective of the present study has been to record the spatial characteristics and other attributes (e.g., topography, sediments and accessibility) of the 71 beaches of the E. Crete (Eastern Mediterranean) that are either already developed or have a reasonable development potential and assess their erosion risk under sea level rise. Beach retreats are predicted by ensembles of six crossshore (1D) analytical and numerical morphodynamic models, set up/forced on the basis of collected/collated information and three sea level rise scenarios (0.26, 0.82 and 1.86 m); these retreats are then compared with the recorded maximum (dry) beach widths. Projections by the unified ensemble suggest that, in the case of a 0.26 m rise, 80 % of the examined beaches are to retreat by more than 20 and 16 % by more than 50 % of their maximum dry width. In the case of a 0.82 m rise, 72 % of the tested beaches are predicted to retreat by more than 50 % of their dry width and 21 % by a distance at least equal to their observed maximum dry widths. A sea level rise of 1.86 m represents a 'doom' scenario, as 75 % of the beaches are predicted to retreat by more than their maximum width. These results may be conservative, as other significant beach erosion factors (e.g., decreasing beach sediment supply) have not been considered.

Abstract. Among the most promising ocean renewable energy sources, offshore wave energy stands out. In Europe, intensive research and development of offshore wave energy technologies has been carried out with the aim of contributing to the growing demand for clean energy. In order to assess the feasibility of the development of a wave energy device in a specific region, the reliable estimation of the local wave energy potential is crucial. In this work, the offshore wave energy potential for the Mediterranean Sea is presented in an annual and seasonal basis. The assessment is based on wave data from numerical wave simulation models obtained by ECMWF. These hindcast data are in the form of time series and cover a 35-year period (1979 -2013). In addition, in the same time scales the mean wave direction is estimated, a variable that is often omitted from similar analyses.

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