Articles | Volume 6, issue 2
https://doi.org/10.5194/wes-6-521-2021
© Author(s) 2021. 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-6-521-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Apr 2021
Research article |
| 13 Apr 2021
| 13 Apr 2021
Offshore wind farm global blockage measured with scanning lidar
ForWind, Institute of Physics, Carl von Ossietzky Universität Oldenburg, Küpkersweg 70, 26129 Oldenburg, Germany
Frauke Theuer
CORRESPONDING AUTHOR
ForWind, Institute of Physics, Carl von Ossietzky Universität Oldenburg, Küpkersweg 70, 26129 Oldenburg, Germany
Andreas Rott
ForWind, Institute of Physics, Carl von Ossietzky Universität Oldenburg, Küpkersweg 70, 26129 Oldenburg, Germany
Martin Dörenkämper
Fraunhofer Institute for Wind Energy Systems, Küpkersweg 70, 26129 Oldenburg, Germany
Martin Kühn
ForWind, Institute of Physics, Carl von Ossietzky Universität Oldenburg, Küpkersweg 70, 26129 Oldenburg, Germany
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Cited
57 citations as recorded by crossref.
- Wind Speed‐Up in Wind Farm Wakes Quantified From Satellite SAR and Mesoscale Modeling C. Hasager et al. https://doi.org/10.1002/we.2943
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- Measurement of flow deflection effects around an offshore wind farm caused by global blockage J. Schneemann et al. https://doi.org/10.1088/1742-6596/3016/1/012012
- Investigating the physical mechanisms that modify wind plant blockage in stable boundary layers M. Sanchez Gomez et al. https://doi.org/10.5194/wes-8-1049-2023
- Scientific challenges to characterizing the wind resource in the marine atmospheric boundary layer W. Shaw et al. https://doi.org/10.5194/wes-7-2307-2022
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- Wind power potential assessment in the lower Mekong countries: a data-driven approach H. Manna et al. https://doi.org/10.1007/s10668-026-07604-x
- In situ airborne measurements of atmospheric parameters and airborne sea surface properties related to offshore wind parks in the German Bight during the project X-Wakes A. Lampert et al. https://doi.org/10.5194/essd-16-4777-2024
- A Field Study to Validate a Lagrangian Wind Field Reconstruction Method for Scanning Wind Lidar I. Ransquin et al. https://doi.org/10.1088/1742-6596/3224/2/022059
- Can lidars assess wind plant blockage in simple terrain? A WRF-LES study M. Sanchez Gomez et al. https://doi.org/10.1063/5.0103668
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- Topology-aware surrogate for future offshore wind farms using machine learning T. Nguyen et al. https://doi.org/10.1016/j.renene.2025.123657
- Coupling wind LiDAR fixed and volumetric scans for enhanced characterization of wind turbulence and flow three‐dimensionality M. Puccioni et al. https://doi.org/10.1002/we.2865
- A Study of Blockage Effects at the Wind Turbine and Wind Farm Scales M. Popescu & T. Flåtten https://doi.org/10.3390/en14196124
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- Hyperparameter tuning framework for calibrating analytical wake models using SCADA data of an offshore wind farm D. van Binsbergen et al. https://doi.org/10.5194/wes-9-1507-2024
- Three-dimensional spatiotemporal wind field reconstruction based on LiDAR and multi-scale PINN Y. Chen et al. https://doi.org/10.1016/j.apenergy.2024.124577
- Effects of self-induced gravity waves on finite wind-farm operations using a large-eddy simulation framework L. Lanzilao & J. Meyers https://doi.org/10.1088/1742-6596/2265/2/022043
- Investigating energy production and wake losses of multi-gigawatt offshore wind farms with atmospheric large-eddy simulation P. Baas et al. https://doi.org/10.5194/wes-8-787-2023
- Blockage and speedup in the proximity of an onshore wind farm: A scanning wind LiDAR experiment M. Puccioni et al. https://doi.org/10.1063/5.0157937
- Blockage effects in a single row of wind turbines J. Bleeg & C. Montavon https://doi.org/10.1088/1742-6596/2265/2/022001
- Offshore wind farm cluster wakes as observed by long-range-scanning wind lidar measurements and mesoscale modeling B. Cañadillas et al. https://doi.org/10.5194/wes-7-1241-2022
- A case study of wind farm effects using two wake parameterizations in the Weather Research and Forecasting (WRF) model (V3.7.1) in the presence of low-level jets X. Larsén & J. Fischereit https://doi.org/10.5194/gmd-14-3141-2021
- Wind Farm Blockage Revealed by Fog: The 2018 Horns Rev Photo Case C. Hasager et al. https://doi.org/10.3390/en16248014
- Evaluation of the global-blockage effect on power performance through simulations and measurements A. Sebastiani et al. https://doi.org/10.5194/wes-7-875-2022
- Holistic scan optimization of nacelle-mounted lidars for inflow and wake characterization at the RAAW and AWAKEN field campaigns S. Letizia et al. https://doi.org/10.1088/1742-6596/2505/1/012048
- Wind farm flow control: prospects and challenges J. Meyers et al. https://doi.org/10.5194/wes-7-2271-2022
- Cross‐Border Cooperation to Mitigate Wake Losses in Offshore Wind Energy: A 2050 Case Study for the North Sea F. Fliegner et al. https://doi.org/10.1155/er/2518424
- Benchmarking engineering wake models for farm-to-farm interactions L. Vollmer et al. https://doi.org/10.1088/1742-6596/2767/9/092095
- Effects of the thrust force induced by wind turbine rotors on the incoming wind field: A wind LiDAR experiment S. Letizia et al. https://doi.org/10.1088/1742-6596/2265/2/022033
- Analysis of Some Major Limitations of Analytical Top-Down Wind-Farm Models S. Emeis https://doi.org/10.1007/s10546-021-00684-4
- Low-level jets' influence on the power conversion efficiency of offshore wind turbines J. Paulsen et al. https://doi.org/10.5194/wes-11-321-2026
- Overview of preparation for the American WAKE ExperimeNt (AWAKEN) P. Moriarty et al. https://doi.org/10.1063/5.0141683
- Long-range near-surface wake signatures of offshore wind farm clusters revealed by satellite observations R. Li et al. https://doi.org/10.1038/s44172-026-00684-7
- Alignment of scanning lidars in offshore campaigns – an extension of the sea surface levelling method K. Gramitzky et al. https://doi.org/10.5194/wes-11-861-2026
- Momentum fluxes from airborne wind measurements in three cumulus cases over land A. Koning et al. https://doi.org/10.5194/acp-22-7373-2022
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- The wind farm as a sensor: learning and explaining orographic and plant-induced flow heterogeneities from operational data R. Braunbehrens et al. https://doi.org/10.5194/wes-8-691-2023
- On the accuracy of predicting wind-farm blockage A. Meyer Forsting et al. https://doi.org/10.1016/j.renene.2023.05.129
- A parametric large-eddy simulation study of wind-farm blockage and gravity waves in conventionally neutral boundary layers L. Lanzilao & J. Meyers https://doi.org/10.1017/jfm.2023.1088
- Alignment calibration and correction for offshore wind measurements using scanning lidars K. Gramitzky et al. https://doi.org/10.1088/1742-6596/2767/4/042014
- Mutsu 2020 Scanning LiDAR Experiment: Comparison of Dual and Single Scanning LiDAR Systems for Near‐Shore Wind Measurement S. Shimada et al. https://doi.org/10.1002/we.70003
- A comprehensive procedure to process scanning lidar data for engineering wake model validation L. Hung et al. https://doi.org/10.1088/1742-6596/2265/2/022091
- Alignment of scanning lidars in offshore wind farms A. Rott et al. https://doi.org/10.5194/wes-7-283-2022
- RETRACTED: Wind energy resource assessment based on joint wolf pack intelligent optimization algorithm J. Wang & M. Suhail https://doi.org/10.1371/journal.pone.0326035
- Investigations of Farm-to-Farm Interactions and Blockage Effects from AWAKEN Using Large-Scale Numerical Simulations L. Cheung et al. https://doi.org/10.1088/1742-6596/2505/1/012023
- Effects of wind shear and thrust coefficient on the induction zone of a porous disk: A wind tunnel study W. Ahmed & G. Iungo https://doi.org/10.1002/we.2910
- Virtual tower measurements during the American WAKE ExperimeNt (AWAKEN) R. Newsom et al. https://doi.org/10.1063/5.0206844
- LiDAR Measurements to Investigate Farm-to-Farm Interactions at the AWAKEN Experiment M. Puccioni et al. https://doi.org/10.1088/1742-6596/2505/1/012045
- Revealing inflow and wake conditions of a 6 MW floating turbine N. Angelou et al. https://doi.org/10.5194/wes-8-1511-2023
- Investigation of onshore wind farm wake recovery with in situ aircraft measurements during AWAKEN A. Voss et al. https://doi.org/10.5194/wes-11-71-2026
- Impact of inflow conditions and turbine placement on the performance of offshore wind turbines exceeding 7 MW K. Vratsinis et al. https://doi.org/10.5194/wes-11-1803-2026
- Pseudo-2D RANS: A LiDAR-driven mid-fidelity model for simulations of wind farm flows S. Letizia & G. Iungo https://doi.org/10.1063/5.0076739
- The sensitivity of the Fitch wind farm parameterization to a three-dimensional planetary boundary layer scheme A. Rybchuk et al. https://doi.org/10.5194/wes-7-2085-2022
- Physics-Guided Short-Term Offshore Wind Power Forecasting Considering Wake and Blockage Effects X. Sun et al. https://doi.org/10.1109/TIA.2025.3625881
- Profiling wind LiDAR measurements to quantify blockage for onshore wind turbines C. Moss et al. https://doi.org/10.1002/we.2877
57 citations as recorded by crossref.
- Wind Speed‐Up in Wind Farm Wakes Quantified From Satellite SAR and Mesoscale Modeling C. Hasager et al. https://doi.org/10.1002/we.2943
- Comparing and validating intra-farm and farm-to-farm wakes across different mesoscale and high-resolution wake models J. Fischereit et al. https://doi.org/10.5194/wes-7-1069-2022
- Measurement of flow deflection effects around an offshore wind farm caused by global blockage J. Schneemann et al. https://doi.org/10.1088/1742-6596/3016/1/012012
- Investigating the physical mechanisms that modify wind plant blockage in stable boundary layers M. Sanchez Gomez et al. https://doi.org/10.5194/wes-8-1049-2023
- Scientific challenges to characterizing the wind resource in the marine atmospheric boundary layer W. Shaw et al. https://doi.org/10.5194/wes-7-2307-2022
- Identification of wind farm blockage using SCADA and reanalysis data in a densely developed offshore concession zone D. van Binsbergen et al. https://doi.org/10.1088/1742-6596/3224/3/032055
- Wind power potential assessment in the lower Mekong countries: a data-driven approach H. Manna et al. https://doi.org/10.1007/s10668-026-07604-x
- In situ airborne measurements of atmospheric parameters and airborne sea surface properties related to offshore wind parks in the German Bight during the project X-Wakes A. Lampert et al. https://doi.org/10.5194/essd-16-4777-2024
- A Field Study to Validate a Lagrangian Wind Field Reconstruction Method for Scanning Wind Lidar I. Ransquin et al. https://doi.org/10.1088/1742-6596/3224/2/022059
- Can lidars assess wind plant blockage in simple terrain? A WRF-LES study M. Sanchez Gomez et al. https://doi.org/10.1063/5.0103668
- Synchronised WindScanner field measurements of the induction zone between two closely spaced wind turbines A. Kidambi Sekar et al. https://doi.org/10.5194/wes-9-1483-2024
- Topology-aware surrogate for future offshore wind farms using machine learning T. Nguyen et al. https://doi.org/10.1016/j.renene.2025.123657
- Coupling wind LiDAR fixed and volumetric scans for enhanced characterization of wind turbulence and flow three‐dimensionality M. Puccioni et al. https://doi.org/10.1002/we.2865
- A Study of Blockage Effects at the Wind Turbine and Wind Farm Scales M. Popescu & T. Flåtten https://doi.org/10.3390/en14196124
- Influence of simple terrain on the spatial variability of a low-level jet and wind farm performance in the AWAKEN field campaign W. Radünz et al. https://doi.org/10.5194/wes-10-2365-2025
- Review of atmospheric stability estimations for wind power applications C. Pérez Albornoz et al. https://doi.org/10.1016/j.rser.2022.112505
- Hyperparameter tuning framework for calibrating analytical wake models using SCADA data of an offshore wind farm D. van Binsbergen et al. https://doi.org/10.5194/wes-9-1507-2024
- Three-dimensional spatiotemporal wind field reconstruction based on LiDAR and multi-scale PINN Y. Chen et al. https://doi.org/10.1016/j.apenergy.2024.124577
- Effects of self-induced gravity waves on finite wind-farm operations using a large-eddy simulation framework L. Lanzilao & J. Meyers https://doi.org/10.1088/1742-6596/2265/2/022043
- Investigating energy production and wake losses of multi-gigawatt offshore wind farms with atmospheric large-eddy simulation P. Baas et al. https://doi.org/10.5194/wes-8-787-2023
- Blockage and speedup in the proximity of an onshore wind farm: A scanning wind LiDAR experiment M. Puccioni et al. https://doi.org/10.1063/5.0157937
- Blockage effects in a single row of wind turbines J. Bleeg & C. Montavon https://doi.org/10.1088/1742-6596/2265/2/022001
- Offshore wind farm cluster wakes as observed by long-range-scanning wind lidar measurements and mesoscale modeling B. Cañadillas et al. https://doi.org/10.5194/wes-7-1241-2022
- A case study of wind farm effects using two wake parameterizations in the Weather Research and Forecasting (WRF) model (V3.7.1) in the presence of low-level jets X. Larsén & J. Fischereit https://doi.org/10.5194/gmd-14-3141-2021
- Wind Farm Blockage Revealed by Fog: The 2018 Horns Rev Photo Case C. Hasager et al. https://doi.org/10.3390/en16248014
- Evaluation of the global-blockage effect on power performance through simulations and measurements A. Sebastiani et al. https://doi.org/10.5194/wes-7-875-2022
- Holistic scan optimization of nacelle-mounted lidars for inflow and wake characterization at the RAAW and AWAKEN field campaigns S. Letizia et al. https://doi.org/10.1088/1742-6596/2505/1/012048
- Wind farm flow control: prospects and challenges J. Meyers et al. https://doi.org/10.5194/wes-7-2271-2022
- Cross‐Border Cooperation to Mitigate Wake Losses in Offshore Wind Energy: A 2050 Case Study for the North Sea F. Fliegner et al. https://doi.org/10.1155/er/2518424
- Benchmarking engineering wake models for farm-to-farm interactions L. Vollmer et al. https://doi.org/10.1088/1742-6596/2767/9/092095
- Effects of the thrust force induced by wind turbine rotors on the incoming wind field: A wind LiDAR experiment S. Letizia et al. https://doi.org/10.1088/1742-6596/2265/2/022033
- Analysis of Some Major Limitations of Analytical Top-Down Wind-Farm Models S. Emeis https://doi.org/10.1007/s10546-021-00684-4
- Low-level jets' influence on the power conversion efficiency of offshore wind turbines J. Paulsen et al. https://doi.org/10.5194/wes-11-321-2026
- Overview of preparation for the American WAKE ExperimeNt (AWAKEN) P. Moriarty et al. https://doi.org/10.1063/5.0141683
- Long-range near-surface wake signatures of offshore wind farm clusters revealed by satellite observations R. Li et al. https://doi.org/10.1038/s44172-026-00684-7
- Alignment of scanning lidars in offshore campaigns – an extension of the sea surface levelling method K. Gramitzky et al. https://doi.org/10.5194/wes-11-861-2026
- Momentum fluxes from airborne wind measurements in three cumulus cases over land A. Koning et al. https://doi.org/10.5194/acp-22-7373-2022
- Field comparison of load-based wind turbine wake tracking with a scanning lidar reference D. Onnen et al. https://doi.org/10.5194/wes-11-175-2026
- The wind farm as a sensor: learning and explaining orographic and plant-induced flow heterogeneities from operational data R. Braunbehrens et al. https://doi.org/10.5194/wes-8-691-2023
- On the accuracy of predicting wind-farm blockage A. Meyer Forsting et al. https://doi.org/10.1016/j.renene.2023.05.129
- A parametric large-eddy simulation study of wind-farm blockage and gravity waves in conventionally neutral boundary layers L. Lanzilao & J. Meyers https://doi.org/10.1017/jfm.2023.1088
- Alignment calibration and correction for offshore wind measurements using scanning lidars K. Gramitzky et al. https://doi.org/10.1088/1742-6596/2767/4/042014
- Mutsu 2020 Scanning LiDAR Experiment: Comparison of Dual and Single Scanning LiDAR Systems for Near‐Shore Wind Measurement S. Shimada et al. https://doi.org/10.1002/we.70003
- A comprehensive procedure to process scanning lidar data for engineering wake model validation L. Hung et al. https://doi.org/10.1088/1742-6596/2265/2/022091
- Alignment of scanning lidars in offshore wind farms A. Rott et al. https://doi.org/10.5194/wes-7-283-2022
- RETRACTED: Wind energy resource assessment based on joint wolf pack intelligent optimization algorithm J. Wang & M. Suhail https://doi.org/10.1371/journal.pone.0326035
- Investigations of Farm-to-Farm Interactions and Blockage Effects from AWAKEN Using Large-Scale Numerical Simulations L. Cheung et al. https://doi.org/10.1088/1742-6596/2505/1/012023
- Effects of wind shear and thrust coefficient on the induction zone of a porous disk: A wind tunnel study W. Ahmed & G. Iungo https://doi.org/10.1002/we.2910
- Virtual tower measurements during the American WAKE ExperimeNt (AWAKEN) R. Newsom et al. https://doi.org/10.1063/5.0206844
- LiDAR Measurements to Investigate Farm-to-Farm Interactions at the AWAKEN Experiment M. Puccioni et al. https://doi.org/10.1088/1742-6596/2505/1/012045
- Revealing inflow and wake conditions of a 6 MW floating turbine N. Angelou et al. https://doi.org/10.5194/wes-8-1511-2023
- Investigation of onshore wind farm wake recovery with in situ aircraft measurements during AWAKEN A. Voss et al. https://doi.org/10.5194/wes-11-71-2026
- Impact of inflow conditions and turbine placement on the performance of offshore wind turbines exceeding 7 MW K. Vratsinis et al. https://doi.org/10.5194/wes-11-1803-2026
- Pseudo-2D RANS: A LiDAR-driven mid-fidelity model for simulations of wind farm flows S. Letizia & G. Iungo https://doi.org/10.1063/5.0076739
- The sensitivity of the Fitch wind farm parameterization to a three-dimensional planetary boundary layer scheme A. Rybchuk et al. https://doi.org/10.5194/wes-7-2085-2022
- Physics-Guided Short-Term Offshore Wind Power Forecasting Considering Wake and Blockage Effects X. Sun et al. https://doi.org/10.1109/TIA.2025.3625881
- Profiling wind LiDAR measurements to quantify blockage for onshore wind turbines C. Moss et al. https://doi.org/10.1002/we.2877
Saved (final revised paper)
Latest update: 11 Aug 2026
Short summary
A wind farm can reduce the wind speed in front of it just by its presence and thus also slightly impact the available power. In our study we investigate this so-called global-blockage effect, measuring the inflow of a large offshore wind farm with a laser-based remote sensing method up to several kilometres in front of the farm. Our results show global blockage under a certain atmospheric condition and operational state of the wind farm; during other conditions it is not visible in our data.
A wind farm can reduce the wind speed in front of it just by its presence and thus also slightly...
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