Follow us at  twitter
CLS Figure 1 Features articleCombining SAR Measurements, Models, Lidar and Artificial Intelligence
Offshore wind resource assessment (WRA) is a challenge due to the scarcity of measurements at hub height. The 18-year database of European synthetic aperture radars (SAR) provides worldwide sea surface wind measurements at 1-kilometre resolution. Through an innovative vertical extrapolation methodology these long-term, wide, high-resolution observations can complement in situ observations and mesoscale modelling for offshore WRA. The methodology is based on four steps: derivation of the 10-minute SAR surface winds from SAR sea surface roughness, a site- and time-independent machine learning algorithm based on a large buoy network to correct SAR surface winds, extrapolation up to 250 metres based on a second machine learning algorithm trained with in situ observations and physical parameters from a high-resolution mesoscale model related to atmospheric stability, and a final post-processing step to correct for low temporal sampling of the SAR database and to retrieve wind statistics.
 
By Mauricio Fragoso, Director, Energies and Infrastructure Monitoring, CLS, France

Want to read full articles? Sign up free of charge and login and read the full text of published articles on our website.

Joomla SEF URLs by Artio