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Wind Energy Science The interactive open-access journal of the European Academy of Wind Energy
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Discussion papers
https://doi.org/10.5194/wes-2019-16
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-2019-16
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: review article 23 May 2019

Submitted as: review article | 23 May 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Wind Energy Science (WES).

US East Coast synthetic aperture radar wind atlas for offshore wind energy

Tobias Ahsbahs1, Galen Maclaurin2, Caroline Draxl2, Christopher Jackson3, Frank Monaldo3, and Merete Badger1 Tobias Ahsbahs et al.
  • 1DTU Wind Energy Risø, Roskilde, Denmark
  • 2National Renewable Energy Laboratory, Golden, Colorado, USA
  • 3Applied Physics Laboratory, Johns Hopkins University, Baltimore, Maryland, USA

Abstract. We present the first synthetic aperture radar (SAR)-based offshore wind atlas of the US East Coast from Georgia to the Canadian border. Images from Radarsat-1, Envisat, Sentinel-1A, and Sentinel-1B are processed to wind maps using the Geophysical Model Function (GMF) CMOD5.N. Extensive comparisons with 6,008 collocated buoy observations revealed that biases of the individual system range from −0.8 to 0.6 m/s. Unbiased wind retrievals are crucial for producing an accurate wind atlas and intercalibration for correcting these biases by adjusting the normalized radar cross section is applied. The intercalibrated SAR observations show biases in the range of to −0.2 to 0.0 m/s, while at the same time improving the root mean squared error from 1.67 to 1.46 m/s. These intercalibrated SAR observations are, for the first time, aggregated to create a wind atlas. Monthly averages are used to correct artefacts from seasonal biases. The SAR wind atlas is used as a reference to study wind resources derived from the Weather Research and Forecasting (WRF) model. Comparisons focus on the spatial variation of wind resources and show that model results estimate lower coastal wind speed gradients than those from SAR. At sites designated for offshore wind development by the Bureau of Ocean Energy Management, mean wind speeds typically vary between 0.3 and 0.5 m/s for SAR and less than 0.2 m/s for the WRF model within each site. Findings indicate that wind speed gradients and variation might be underestimated in mesoscale model outputs along US East Coast.

Tobias Ahsbahs et al.
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Tobias Ahsbahs et al.
Tobias Ahsbahs et al.
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Latest update: 09 Dec 2019
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Short summary
Before constructing wind farms we need to know how much energy they will produce. This requires knowledge of long term wind conditions either from measurements or models. At the US East Coast there are few wind measurements and little experience with offshore wind farms. Therefore, we created a satellite-based high resolution wind resource map to quantify spatial variations of the wind conditions over potential sites for wind farms and found larger variation than modelling suggested.
Before constructing wind farms we need to know how much energy they will produce. This requires...
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