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Open AccessArticle

The RUNE Experiment—A Database of Remote-Sensing Observations of Near-Shore Winds

DTU Wind Energy, Technical University of Denmark, Risø Campus, Roskilde 4000, Denmark
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Academic Editors: Deepak R. Mishra, Xiaofeng Li and Prasad S. Thenkabail
Remote Sens. 2016, 8(11), 884; https://doi.org/10.3390/rs8110884
Received: 31 August 2016 / Revised: 17 October 2016 / Accepted: 19 October 2016 / Published: 26 October 2016
(This article belongs to the Special Issue Remote Sensing of Wind Energy)
We present a comprehensive database of near-shore wind observations that were carried out during the experimental campaign of the RUNE project. RUNE aims at reducing the uncertainty of the near-shore wind resource estimates from model outputs by using lidar, ocean, and satellite observations. Here, we concentrate on describing the lidar measurements. The campaign was conducted from November 2015 to February 2016 on the west coast of Denmark and comprises measurements from eight lidars, an ocean buoy and three types of satellites. The wind speed was estimated based on measurements from a scanning lidar performing PPIs, two scanning lidars performing dual synchronized scans, and five vertical profiling lidars, of which one was operating offshore on a floating platform. The availability of measurements is highest for the profiling lidars, followed by the lidar performing PPIs, those performing the dual setup, and the lidar buoy. Analysis of the lidar measurements reveals good agreement between the estimated 10-min wind speeds, although the instruments used different scanning strategies and measured different volumes in the atmosphere. The campaign is characterized by strong westerlies with occasional storms. View Full-Text
Keywords: coastal; experiment; lidar; near-shore; offshore; wind resources coastal; experiment; lidar; near-shore; offshore; wind resources
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MDPI and ACS Style

Floors, R.; Peña, A.; Lea, G.; Vasiljević, N.; Simon, E.; Courtney, M. The RUNE Experiment—A Database of Remote-Sensing Observations of Near-Shore Winds. Remote Sens. 2016, 8, 884.

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