a b s t r a c tModel-based wind speed data derived from the coastDat2 data set for the North Sea were used to assess wind power potential considering both spatial and temporal variability. The atmospheric part of coastDat2 was simulated with the regional climate model COSMO-CLM 4.8. The quality of the used wind speed data is analysed by comparison with buoy and QuikSCAT data. To determine where an offshore power plant can be cost-effectively developed, the distribution of the possible production dependencies on the offshore distance is one of the more important factors. A synthetic power function was used to convert the model-derived wind speeds at a height of 100 m to wind power. The data were analyzed for the period of 1958-2012, and the results obtained for the decadal and spatial variability were mapped. The site related summaries are discussed.The inter-annual to decadal variability can reach up to 5% from the multi-decadal mean and therefore plays an important role in wind energy; wind power estimates based on short observational time series, particularly from the late 1990s, may exhibit high biases. The up-scaling from wind speeds at a height of 10 m using conventional power laws may result in similar biases. On inter-annual to decadal time scales, synergies are not expected from the different arrays in the North Sea, i.e., a decrease in the power output of an array may not be balanced by another.
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.
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