Nearshore wave forecasting and hindcasting by dynamical and statistical downscaling

A high-resolution nested WAM/SWAN wave model suite aimed at rapidly establishing nearshore wave forecasts as well as a climatology and return values of the local wave conditions with Rapid Enviromental Assessment (REA) in mind is described. The system is targeted at regions where local wave growth and partial exposure to complex open-ocean wave conditions makes diagnostic wave modelling difficult. SWAN is set up on 500 m resolution and is nested in a 10 km version of WAM. A model integration of more than one year is carried out to map the spatial distribution of the wave field. The model correlates well with wave buoy observations (0.96) but overestimates the wave height somewhat (18%, bias 0.29 m). To estimate wave height return values a much longer time series is required and running SWAN for such a period is unrealistic in a REA setting. Instead we establish a direction-dependent transfer function between an already existing coarse open-ocean hindcast dataset and the high-resolution nested SWAN model. Return values are estimated using ensemble estimates of two different extreme-value distributions based on the full 52 years of statistically downscaled hindcast data. We find good agreement between downscaled wave height and wave buoy observations. The cost of generating the statistically downscaled hindcast time series is negligible and can be redone for arbitrary locations within the SWAN domain, although the sectors must be carefully chosen for each new location. The method is found to be well suited to rapidly providing detailed wave forecasts as well as hindcasts and return values estimates of partly sheltered coastal regions.Comment: 20 pages, 7 figures and 2 tables, MREA07 special issue on Marine rapid environmental assessmen

Changes in compound flood event frequency in northern and central Europe under climate change

The simultaneous occurrence of increased river discharge and high coastal water levels may cause compound flooding. Compound flood events can potentially cause greater damage than the separate occurrence of the underlying extreme events, making them essential for risk assessment. Even though a general increase in the frequency and/or severity of compound flood events is assumed due to climate change, there have been very few studies conducted for larger regions of Europe. Our work, therefore, focuses on the high-resolution analysis of changes in extreme events of coastal water levels, river discharge, and their concurrent appearance at the end of this century in northern and central Europe (2070–2099). For this, we analyze downscaled data sets from two global climate models (GCMs) for the two emissions scenarios RCP2.6 and RCP8.5. First, we compare the historical runs of the downscaled GCMs to historical reconstruction data to investigate if they deliver comparable results for northern and central Europe. Then we study changes in the intensity of extreme events, their number, and the duration of extreme event seasons under climate change. Our analysis shows increases in compound flood events over the whole European domain, mostly due to the rising mean sea level. In some areas, the number of compound flood event days increases by a factor of eight at the end of the current century. This increase is concomitant with an increase in the annual compound flood event season duration. Furthermore, the sea level rise associated with a global warming of 2K will result in double the amounts of compound flood event days for nearly every European river estuary considered

Compound flood events: analysing the joint occurrence of extreme river discharge events and storm surges in northern and central Europe

The simultaneous occurrence of extreme events gained more and more attention from scientific research in the last couple of years. Compared to the occurrence of single extreme events, co-occurring or compound extremes may substantially increase risks. To adequately address such risks, improving our understanding of compound flood events in Europe is necessary and requires reliable estimates of their probability of occurrence together with potential future changes. In this study compound flood events in northern and central Europe were studied using a Monte Carlo-based approach that avoids the use of copulas. Second, we investigate if the number of observed compound extreme events is within the expected range of 2 standard deviations of randomly occurring compound events. This includes variations of several parameters to test the stability of the identified patterns. Finally, we analyse if the observed compound extreme events had a common large-scale meteorological driver. The results of our investigation show that rivers along the west-facing coasts of Europe experienced a higher amount of compound flood events than expected by pure chance. In these regions, the vast majority of the observed compound flood events seem to be related to the cyclonic westerly general weather pattern (Großwetterlage).</p