Marine spatial planning requires reliable data for, e.g., the design of coastal structures, research, or sea level rise adaptation. This task is particularly ambiguous in the German Bight (North Sea, Europe) because a compromise must be found between economic interests and biodiversity since the environmental status is monitored closely by the European Union. For this reason, we have set up an open-access, integrated marine data collection for the period from 1996 to 2015. It provides bathymetry, surface sediments, tidal dynamics, salinity, and waves for the German Bight and is of interest to stakeholders in science, government, and the economy. This part of a two-part publication presents data from numerical hindcast simulations for sea surface elevation, depth-averaged current velocity, bottom shear stress, depth-averaged salinity, wave parameters, and wave spectra. As an improvement to existing data collections, our data represent the variability in the bathymetry by using annually updated model topographies. Moreover, we provide data at a high temporal and spatial resolution (Hagen et al., 2020b); i.e., numerical model results are gridded to 1000 m at 20 min intervals (https://doi.org/10.48437/02.2020.K2.7000.0004). Tidal characteristic values (Hagen et al., 2020a), such as tidal range or ebb current velocity, are computed based on numerical modeling results (https://doi.org/10.48437/02.2020.K2.7000.0003). Therefore, this integrated marine data collection supports the work of coastal stakeholders and scientists, which ranges from developing detailed coastal models to handling complex natural-habitat problems or designing coastal structures.

In this study, the projected future long-term changes of the local wave conditions at the German Baltic Sea coast over the course of the 21st century are analyzed and assessed with special focus on model agreement, statistical significance and ranges/spread of the results. An ensemble of new regional climate model (RCM) simulations with the RCM REMO for three RCP forcing scenarios was used as input data. The outstanding feature of the simulations is that the data are available with a high horizontal resolution and at hourly timesteps which is a high temporal resolution and beneficial for the wind–wave modelling. A new data interface between RCM output data and wind–wave modelling has been developed. Suitable spatial aggregation methods of the RCM wind data have been tested and used to generate input for the calculation of waves at quasi deep-water conditions and at a mean water level with a hybrid approach that enables the fast compilation of future long-term time series of significant wave height, mean wave period and direction for an ensemble of RCM data. Changes of the average wind and wave conditions have been found, with a majority of the changes occurring for the RCP8.5 forcing scenario and at the end of the 21st century. At westerly wind-exposed locations mainly increasing values of the wind speed, significant wave height and mean wave period have been noted. In contrast, at easterly wind-exposed locations, decreasing values are predominant. Regarding the changes of the mean wind and wave directions, westerly directions becoming more frequent. Additional research is needed regarding the long-term changes of extreme wave events, e.g., the choice of a best-fit extreme value distribution function and the spatial aggregation method of the wind data.

For many coastal areas including the Baltic Sea, ambitious nutrient abatement goals have been set to curb eutrophication, but benefits of such measures were normally not studied in light of anticipated climate change. To project the likely responses of nutrient abatement on eelgrass (Zostera marina), we coupled a species distribution model with a biogeochemical model, obtaining future water turbidity, and a wave model for predicting the future hydrodynamics in the coastal area. Using this, eelgrass distribution was modeled for different combinations of nutrient scenarios and future wind fields. We are the first to demonstrate that while under a business as usual scenario overall eelgrass area will not recover, nutrient reductions that fulfill the Helsinki Commission’s Baltic Sea Action Plan (BSAP) are likely to lead to a substantial areal expansion of eelgrass coverage, primarily at the current distribution’s lower depth limits, thereby overcompensating losses in shallow areas caused by a stormier climate.

Dreier, N. and Fröhle, P., 2018. Operational wave forecast in the German Bight as part of a sensor- and risk based early warning system. In: Shim, J.-S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 1161–1165. Coconut Creek (Florida), ISSN 0749-0208. Today's available flood- respectively storm surge warning systems for the German North Sea coast consist exclusively of water level forecasts. Other hydrodynamic loads caused by wind waves and local currents as well as the resistance of the flood protection structure itself (e.g. coastal dikes, flood protection walls etc.) are not taken into account. Therefore, an operational now- and forecast system for waves and wave induced hydrodynamic loads is set up that consists of available field measurements and data from numerical wave simulations in the German Bight. A hybrid model approach is used for the forecast of hydrod...

Xu, Z.S.; Dreier, N.; Chen, Y.P., Fröhle, P. and Xie, D.M., 2016. On the long-term changes of extreme wave heights at the German Baltic Sea Coast. In: Vila-Concejo, A.; Bruce, E.; Kennedy, D.M., and McCarroll, R.J. (eds.), Proceedings of the 14th International Coastal Symposium (Sydney, Australia). Journal of Coastal Research, Special Issue, No. 75, pp. 962–966. Coconut Creek (Florida), ISSN 0749-0208. The assessment of extreme wave heights is of great importance for the design of coastal protection strucutres. This paper aims to present long-term changes of extreme wave heights at several selected locations at the German Baltic Sea Coast. Annual maximum significant wave heights were selected from the hourly wave data obtained from a hybrid approach (wind-wave-correlations combined with numerical simulations on the basis of the SWAN model) for a total period of 140 years, spanning from 1961 to 2100. The future projections of wind data were dreived from the regional COSMO-Climate Local Model for two emission scenarios A1B and B1. The extreme wave heights at each location were estimated from the respective best-fitting distribution, log-normal or Weibull distribution. The results indicate that, the long-term changes of extreme wave heights are related to the emission scenarios used in the regional climate model, the distribution chosen for the estimating (up to +9.6%) and also the sample size for the extreme value analysis (up to +8.7%). These factors should be carefully considered in the future coastal structure design.