1 Department of Wind Energy, Technical University of Denmark2 Meteorology, Department of Wind Energy, Technical University of Denmark3 Test and Measurements, Department of Wind Energy, Technical University of Denmark4 GL Garrad Hassan5 Fraunhofer Gesellschaft6 CLS7 KNMI8 Risø National Laboratory for Sustainable Energy, Technical University of Denmark9 Oldbaum Services Limited
Ocean winds have been observed in the Baltic, Irish and North Seas from a combination of groundbased lidars, tall offshore meteorological masts and satellites remote sensing in recent years. In the FP7 project NORSEWInD (2008-2012) the project partners joined forces to ensure collection of these data. In particular, an array of wind profiling lidars was deployed at offshore platforms. All lidars were tested at the Høvsøre test site at DTU Wind Energy (former Risø DTU) prior to installation at the offshore platforms. The lidar operated in the harsh marine environment for several months, a few of them for up to two years when the project campaign ended. The NORSEWInD database on lidar data in total contains around 11 years worth of observations (> 280.000 10 min data). The wind lidars were mounted such that winds were mapped at or very near 100 m above sea level. The lidars provide wind profile data and this has been used to characterize the vertical wind profile offshore. Also the data from the meteorological masts provide wind profile data. In addition, temperature profile observations are available at some of the meteorological masts. The temperature data were used to investigate the thermal effects on the wind profile. In conclusion, the parameters that influence the vertical wind profiles are found to be stability, surface roughness – the sea has changing roughness due to wind-wave interactions - , and boundary layer height, in this order of importance. However, it may be noted that for specific conditions, e.g. very stable atmosphere, the wind profiles can be heavily influenced by the boundary layer height at the 100 m level in the northern European seas. A very interesting part of the analysis includes the shear exponent (alpha) calculated during seasons, during 24-hours and for 12 wind directional bins. The latter resulted in so-called ‘alpha roses’, similar to wind roses but with the values of alpha given. Satellite ocean surface winds were collected from synthetic aperture radar (SAR), scatterometer and passive microwave instruments. All satellite wind data provide winds at 10 m above sea level. Satellite winds from Envisat ASAR, QuikSCAT, ASCAT and SSM/I have been compared to offshore meteorological data. For the final satellite-based wind atlas 9,000 SAR scenes, collected by CLS and DTU, were reprocessed with the same algorithm in order to get an homogeneous data set. The number of overlapping SAR scenes varied from a few hundred to more than 1,400 in the study area. For QuikSCAT and ASCAT the available number of overlapping scenes is around 7000 and 600, respectively. The results are publically available in digital form from GIS, free of charge, through a link at www.norsewind.eu. The SSM/I wind maps from covering a period of 25 years were used to study temporal and seasonal trends in the power index.
Proceedings of the 2013 International Conference on Aerodynamics of Offshore Wind Energy Systems and Wakes (icowes2013), 2013, p. 123-131
Main Research Area:
International Conference on aerodynamics of Offshore Wind Energy Systems and wakes (ICOWES 2013)