Advances in offshore wind farm (OWF) technology have recently led to their construction in coastal waters that are deep enough to be seasonally stratified. As tidal currents move past the OWF foundation structures they generate a turbulent wake that will contribute to a mixing of the stratified water column. In this study we show that the mixing generated in this way may have a significant impact on the large-scale stratification of the German Bight region of the North Sea. This region is chosen as the focus of this study since the planning of OWFs is particularly widespread. Using a combination of idealised modelling and in situ measurements, we provide order-of-magnitude estimates of two important time scales that are key to understanding the impacts of OWFs: (i) a mixing time scale, describing how long a complete mixing of the stratification takes, and (ii) an advective time scale, quantifying for how long a water parcel is expected to undergo enhanced wind farm mixing. The results are especially sensitive to both the drag coefficient and type of foundation structure, as well as the evolution of the pycnocline under enhanced mixing conditions—both of which are not well known. With these limitations in mind, the results show that OWFs could impact the large-scale stratification, but only when they occupy extensive shelf regions. They are expected to have very little impact on large-scale stratification at the current capacity in the North Sea, but the impact could be significant in future large-scale development scenarios.

Storm surges in the North Sea are one of the threats for coastal infrastructure and human safety. Under an anthropogenic climate change, the threat of extreme storm surges may be enlarged due to changes in the wind climate. Possible future storm surge climates based on transient simulations (1961-2100) are investigated with a hydrodynamical model for the North Sea. The climate change scenarios are based on regionalized meteorological conditions with the regional climate model CCLM which is forced by AR4 climate simulations with the general circulation model ECHAM5/MPIOM under two IPCC emission scenarios (SRES A1B and B1) and two initial conditions. Possible sea level rise in the North Sea is not taken into account. The analysis of future wind-induced changes of the water levels is focused on extreme values. Special emphasis is given to the southeastern North Sea (German Bight). Comparing the 30-year averages of the annual 99 percentiles of the wind-induced water levels between the four climate realizations and the respective control climates, a small tendency toward an increase is inferred for all climate change realizations toward the end of the 21st century. Concerning the German Bight, the climate change signals are higher for the North Frisian coastal areas than for the East Frisian ones. This is consistent with an increase in frequency of strong westerly winds. Considering the whole time series (1961-2100) for selected areas, this tendency is superimposed with strong decadal fluctuations. It is found that uncertainties are related not only to the used models and emission scenarios but also to the initial conditions pointing to the internal natural variability.

Time variability of Eulerian residual currents in

The term "climate services" is commonly used to refer to the generation of climate information, their transformation according to user needs and the subsequent use of the information in decision making processes. More generally, the concept also involves contextualization of information and knowledge. In the following a series of examples from the marine sector is described covering the generation, transformation and the use of climate information in decision making processes while contextualization is not considered. Examples comprise applications from naval architecture, offshore wind and more generally renewable energies, shipping emissions, and tidal basin water exchange and eutrophication levels. Moreover effects of climate change on coastal flood damages and the need for coastal protection are considered. Based on the analysis of these examples it is concluded that reliable climate information in data sparse regions is urgently needed, that for many applications historical climate information may be as or even more important as future long-term projections, and that the specific needs of different sectors substantially depend on their planning horizons.

No abstract