Articles | Volume 5, issue 3
https://doi.org/10.5194/wes-5-1191-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-5-1191-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Review article
| 
17 Sep 2020
Review article |
| 17 Sep 2020
| 17 Sep 2020
US East Coast synthetic aperture radar wind atlas for offshore wind energy
Tobias Ahsbahs
DTU Wind Energy, Risø, Roskilde, Denmark
Galen Maclaurin
National Renewable Energy Laboratory, Golden, Colorado, USA
Caroline Draxl
National Renewable Energy Laboratory, Golden, Colorado, USA
Christopher R. Jackson
Global Ocean Associates, Alexandria, Virginia, USA
Frank Monaldo
Applied Physics Laboratory, Johns Hopkins University, Baltimore,
Maryland, USA
DTU Wind Energy, Risø, Roskilde, Denmark
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Total article views: 1,628 (including HTML, PDF, and XML)
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Total article views: 1,785 (including HTML, PDF, and XML)
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Cited
18 citations as recorded by crossref.
- SARAL-AltiKa Wind and Significant Wave Height for Offshore Wind Energy Applications in the New England Region X. Li et al. 10.3390/rs13010057
- Wind Retrieval from Constellations of Small SAR Satellites: Potential for Offshore Wind Resource Assessment M. Badger et al. 10.3390/en16093819
- Gap-Filling Sentinel-1 Offshore Wind Speed Image Time Series Using Multiple-Point Geostatistical Simulation and Reanalysis Data S. Hadjipetrou et al. 10.3390/rs15020409
- Characterizing Coastal Wind Speed and Significant Wave Height Using Satellite Altimetry and Buoy Data P. Mitsopoulos & M. Peña 10.3390/rs15040987
- New methods to improve the vertical extrapolation of near-surface offshore wind speeds M. Optis et al. 10.5194/wes-6-935-2021
- Extreme Wind and Waves in U.S. East Coast Offshore Wind Energy Lease Areas R. Barthelmie et al. 10.3390/en14041053
- Modeling Annual Electricity Production and Levelized Cost of Energy from the US East Coast Offshore Wind Energy Lease Areas R. Barthelmie et al. 10.3390/en16124550
- Study of Coastal Effects Relevant for Offshore Wind Energy Using Spaceborne Synthetic Aperture Radar (SAR) B. Djath et al. 10.3390/rs14071688
- A Mediterranean Sea Offshore Wind classification using MERRA-2 and machine learning models M. Majidi Nezhad et al. 10.1016/j.renene.2022.03.110
- Occurrence of Low-Level Jets over the Eastern U.S. Coastal Zone at Heights Relevant to Wind Energy J. Aird et al. 10.3390/en15020445
- Wind power production from very large offshore wind farms S. Pryor et al. 10.1016/j.joule.2021.09.002
- High-resolution offshore wind resource assessment at turbine hub height with Sentinel-1 synthetic aperture radar (SAR) data and machine learning L. de Montera et al. 10.5194/wes-7-1441-2022
- Power Production, Inter- and Intra-Array Wake Losses from the U.S. East Coast Offshore Wind Energy Lease Areas S. Pryor & R. Barthelmie 10.3390/en17051063
- Wind shadows impact planning of large offshore wind farms S. Pryor & R. Barthelmie 10.1016/j.apenergy.2024.122755
- High-resolution satellite observations to account for coastal gradient in wind resource assessment: application to French coastal areas M. Cathelain et al. 10.1088/1742-6596/2505/1/012027
- Improving SAR wind retrieval through automatic anomalous pixel detection A. Owda et al. 10.1016/j.jag.2023.103444
- A SWOT Analysis for Offshore Wind Energy Assessment Using Remote-Sensing Potential M. Majidi Nezhad et al. 10.3390/app10186398
- Europe's offshore winds assessed with synthetic aperture radar, ASCAT and WRF C. Hasager et al. 10.5194/wes-5-375-2020
16 citations as recorded by crossref.
- SARAL-AltiKa Wind and Significant Wave Height for Offshore Wind Energy Applications in the New England Region X. Li et al. 10.3390/rs13010057
- Wind Retrieval from Constellations of Small SAR Satellites: Potential for Offshore Wind Resource Assessment M. Badger et al. 10.3390/en16093819
- Gap-Filling Sentinel-1 Offshore Wind Speed Image Time Series Using Multiple-Point Geostatistical Simulation and Reanalysis Data S. Hadjipetrou et al. 10.3390/rs15020409
- Characterizing Coastal Wind Speed and Significant Wave Height Using Satellite Altimetry and Buoy Data P. Mitsopoulos & M. Peña 10.3390/rs15040987
- New methods to improve the vertical extrapolation of near-surface offshore wind speeds M. Optis et al. 10.5194/wes-6-935-2021
- Extreme Wind and Waves in U.S. East Coast Offshore Wind Energy Lease Areas R. Barthelmie et al. 10.3390/en14041053
- Modeling Annual Electricity Production and Levelized Cost of Energy from the US East Coast Offshore Wind Energy Lease Areas R. Barthelmie et al. 10.3390/en16124550
- Study of Coastal Effects Relevant for Offshore Wind Energy Using Spaceborne Synthetic Aperture Radar (SAR) B. Djath et al. 10.3390/rs14071688
- A Mediterranean Sea Offshore Wind classification using MERRA-2 and machine learning models M. Majidi Nezhad et al. 10.1016/j.renene.2022.03.110
- Occurrence of Low-Level Jets over the Eastern U.S. Coastal Zone at Heights Relevant to Wind Energy J. Aird et al. 10.3390/en15020445
- Wind power production from very large offshore wind farms S. Pryor et al. 10.1016/j.joule.2021.09.002
- High-resolution offshore wind resource assessment at turbine hub height with Sentinel-1 synthetic aperture radar (SAR) data and machine learning L. de Montera et al. 10.5194/wes-7-1441-2022
- Power Production, Inter- and Intra-Array Wake Losses from the U.S. East Coast Offshore Wind Energy Lease Areas S. Pryor & R. Barthelmie 10.3390/en17051063
- Wind shadows impact planning of large offshore wind farms S. Pryor & R. Barthelmie 10.1016/j.apenergy.2024.122755
- High-resolution satellite observations to account for coastal gradient in wind resource assessment: application to French coastal areas M. Cathelain et al. 10.1088/1742-6596/2505/1/012027
- Improving SAR wind retrieval through automatic anomalous pixel detection A. Owda et al. 10.1016/j.jag.2023.103444
Latest update: 25 Apr 2024
Short summary
Before constructing wind farms we need to know how much energy they will produce. This requires knowledge of long-term wind conditions from either 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 in 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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