Around 2000 wind turbines in 58 offshore wind farms produce wind energy in the Northern European seas and many new wind farms are foreseen. The wind resource assessment is costly to observe using traditional meteorological masts and therefore atmospheric modeling is state of the art. However, to reduce the uncertainty on the model results on the offshore wind resource, it is necessary to compare model results with observations. Observations from ground-based wind lidar and satellite remote sensing are the two main technologies that can provide new types of offshore wind data at relatively low cost. The advantages of microwave satellite remote sensing are (1) horizontal spatial coverage, (2) long data archives, and (3) high spatial detail both in the coastal zone and of far-field wind farm wake. Passive microwave ocean wind speed data are available since 1987 with up to six observations per day with near-global coverage. The data are particularly useful for investigation of long-term wind conditions. Scatterometer ocean surface wind vectors provide a continuous series since 1999 with twice-daily near-global coverage. Both types of data have grid cells around 25 km. In contrast, synthetic aperture radar (SAR) wind maps can be retrieved at 1-km grid resolution. SAR-based wind maps have been used for wind resource assessment far offshore and in the coastal zones with good results when compared to e.g., meteorological data and mesoscale model results. High-resolution SAR data show very long far-field wind farm wakes. Thus wind farm wake loss is foreseen in wind farm clusters. WIREs Energy Environ 2014, 3:594–603. doi: 10.1002/wene.123

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Conflict of interest: The author has declared no conflicts of interest for this article.