Sentinel-1 for offshore wind energy application

This review presents Sentinel-1 (S-1) SAR wind products that are being used in the offshore wind energy sector, motivated by the unique properties of SAR mapping ocean winds with high spatial detail. High spatial detail is significant as offshore wind farms operate in coastal zones with high spatial wind variability. The SAR products reviewed include wind speeds at 10 m height, wind farm wakes, wind resources, and the identification of wind turbine locations. Main findings from the literature indicate that the thoroughly tested scatterometer-based geophysical model functions (GMFs) for SAR wind speed, compared to buoys, have an RMSE of approximately 1.5 m/s and a bias of around ±0.5 m/s. CMOD5.N shows better statistics compared to other scatterometer-based GMFs and is applied in near-real-time SAR-based ocean wind mapping by Copernicus and DTU Wind. One recent SAR-calibrated model, called OPEN, outperforms CMOD5.N; however, OPEN has not been tested by other researchers. The literature review on SAR for wind energy applications reveals that SAR can detect wind farms and cluster wakes extending over 100 km. SAR winds contain greater spatial detail than mesoscale models. For offshore wind resource assessment based on SAR, the reviewed literature indicates that the required extrapolation of winds from 10 m to hub height using stability information from mesoscale models is accurate within a few percent. The limitations due to coverage and revisit times of S-1 are negligible according to the reviewed literature for wind energy applications in the studied regions; however, these limitations are unknown in other regions. The lack of common databases on offshore wind turbine locations, combined with the rapid growth in numbers, has prompted interest in using S-1 data hard-target identification methods. A standardized global coverage turbine location database has been achieved based on S-1. A key challenge and limitation of assessing wind resource performance based on S-1 is the limited number of comparison results for hub-height wind resource data. It is recommended to conduct systematic comparisons of wind resource assessment and wind farm wake to enhance trust, benefit, and future use of S-1 data within the offshore wind energy sector in the years ahead. • SAR wind speeds vs. buoys show RMSE around 1.5 m/s and bias around ±0.5 m/s. • Post-processed SAR winds vs. buoys show RMSE around 1.2 m/s and bias near 0 m/s. • SAR winds provide significantly greater spatial detail than mesoscale models. • Wind resources extrapolated from SAR to hub height are accurate within a few percent. • SAR wind maps show wind farm and cluster wakes reaching longer than 100 km.

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Publication Details

Journal
Remote Sensing of Environment
Published
2026-03-31
DOI
https://doi.org/10.1016/j.rse.2026.115369
Primary Topic
Ocean Waves and Remote Sensing
Type
article
Field-Weighted Citation Impact
0.00

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article

Sentinel-1 for offshore wind energy application

C.B. Hasager, Krystallia Dimitriadou
Remote Sensing of Environment
Ocean Waves and Remote Sensing
article

Sentinel-1 for offshore wind energy application

C.B. Hasager, Krystallia Dimitriadou
article en

Abstract

This review presents Sentinel-1 (S-1) SAR wind products that are being used in the offshore wind energy sector, motivated by the unique properties of SAR mapping ocean winds with high spatial detail. High spatial detail is significant as offshore wind farms operate in coastal zones with high spatial wind variability. The SAR products reviewed include wind speeds at 10 m height, wind farm wakes, wind resources, and the identification of wind turbine locations. Main findings from the literature indicate that the thoroughly tested scatterometer-based geophysical model functions (GMFs) for SAR wind speed, compared to buoys, have an RMSE of approximately 1.5 m/s and a bias of around ±0.5 m/s. CMOD5.N shows better statistics compared to other scatterometer-based GMFs and is applied in near-real-time SAR-based ocean wind mapping by Copernicus and DTU Wind. One recent SAR-calibrated model, called OPEN, outperforms CMOD5.N; however, OPEN has not been tested by other researchers. The literature review on SAR for wind energy applications reveals that SAR can detect wind farms and cluster wakes extending over 100 km. SAR winds contain greater spatial detail than mesoscale models. For offshore wind resource assessment based on SAR, the reviewed literature indicates that the required extrapolation of winds from 10 m to hub height using stability information from mesoscale models is accurate within a few percent. The limitations due to coverage and revisit times of S-1 are negligible according to the reviewed literature for wind energy applications in the studied regions; however, these limitations are unknown in other regions. The lack of common databases on offshore wind turbine locations, combined with the rapid growth in numbers, has prompted interest in using S-1 data hard-target identification methods. A standardized global coverage turbine location database has been achieved based on S-1. A key challenge and limitation of assessing wind resource performance based on S-1 is the limited number of comparison results for hub-height wind resource data. It is recommended to conduct systematic comparisons of wind resource assessment and wind farm wake to enhance trust, benefit, and future use of S-1 data within the offshore wind energy sector in the years ahead. • SAR wind speeds vs. buoys show RMSE around 1.5 m/s and bias around ±0.5 m/s. • Post-processed SAR winds vs. buoys show RMSE around 1.2 m/s and bias near 0 m/s. • SAR winds provide significantly greater spatial detail than mesoscale models. • Wind resources extrapolated from SAR to hub height are accurate within a few percent. • SAR wind maps show wind farm and cluster wakes reaching longer than 100 km.

Remote Sensing of EnvironmentVol. 339
Technical University of Denmark (DK)
European Space Agency
Affordable and clean energy
Openalex Percentile: Top 11%
Ocean Waves and Remote Sensing
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