Articles | Volume 6, issue 4
https://doi.org/10.5194/wes-6-1043-2021
© 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-6-1043-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
10 Aug 2021
Research article |
| 10 Aug 2021
| 10 Aug 2021
Extreme wind shear events in US offshore wind energy areas and the role of induced stratification
Mithu Debnath
CORRESPONDING AUTHOR
National Renewable Energy Laboratory, Golden, Colorado, USA
Paula Doubrawa
National Renewable Energy Laboratory, Golden, Colorado, USA
Mike Optis
National Renewable Energy Laboratory, Golden, Colorado, USA
Patrick Hawbecker
National Center for Atmospheric Research, Boulder, Colorado, USA
Nicola Bodini
National Renewable Energy Laboratory, Golden, Colorado, USA
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Cited
19 citations as recorded by crossref.
- Lessons learned in coupling atmospheric models across scales for onshore and offshore wind energy S. Haupt et al. 10.5194/wes-8-1251-2023
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- Application of low-altitude wind shear recognition algorithm and laser wind radar in aviation meteorological services T. Xu et al. 10.1515/phys-2023-0154
- Scientific challenges to characterizing the wind resource in the marine atmospheric boundary layer W. Shaw et al. 10.5194/wes-7-2307-2022
- Seasonal variability of wake impacts on US mid-Atlantic offshore wind plant power production D. Rosencrans et al. 10.5194/wes-9-555-2024
- Brief communication: On the definition of the low-level jet C. Hallgren et al. 10.5194/wes-8-1651-2023
- Classification and properties of non-idealized coastal wind profiles – an observational study C. Hallgren et al. 10.5194/wes-7-1183-2022
- 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
- Estimating hub-height wind speed based on a machine learning algorithm: implications for wind energy assessment B. Liu et al. 10.5194/acp-23-3181-2023
- Characterization of wind speed and directional shear at the AWAKEN field campaign site M. Debnath et al. 10.1063/5.0139737
- Sensitivity analysis of numerical modeling input parameters on floating offshore wind turbine loads W. Wiley et al. 10.5194/wes-8-1575-2023
- Extreme wind load analysis using non-stationary risk-based approach M. Arif et al. 10.1007/s42797-022-00064-2
- 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
- Structure of Offshore Low-Level Jet Turbulence and Implications to Mesoscale-to-Microscale Coupling B. Jayaraman et al. 10.1088/1742-6596/2265/2/022064
- Offshore low-level jet observations and model representation using lidar buoy data off the California coast L. Sheridan et al. 10.5194/wes-9-741-2024
- Application of Nanometer Heavy-duty Coating in the Optimization of Process Parameters for Power Generation Machinery W. Long & N. Vasimalai 10.1155/2022/5600230
- Machine learning methods to improve spatial predictions of coastal wind speed profiles and low-level jets using single-level ERA5 data C. Hallgren et al. 10.5194/wes-9-821-2024
- Offshore wind energy forecasting sensitivity to sea surface temperature input in the Mid-Atlantic S. Redfern et al. 10.5194/wes-8-1-2023
- New methods to improve the vertical extrapolation of near-surface offshore wind speeds M. Optis et al. 10.5194/wes-6-935-2021
18 citations as recorded by crossref.
- Lessons learned in coupling atmospheric models across scales for onshore and offshore wind energy S. Haupt et al. 10.5194/wes-8-1251-2023
- Spatiotemporal observations of nocturnal low-level jets and impacts on wind power production E. Weide Luiz & S. Fiedler 10.5194/wes-7-1575-2022
- Application of low-altitude wind shear recognition algorithm and laser wind radar in aviation meteorological services T. Xu et al. 10.1515/phys-2023-0154
- Scientific challenges to characterizing the wind resource in the marine atmospheric boundary layer W. Shaw et al. 10.5194/wes-7-2307-2022
- Seasonal variability of wake impacts on US mid-Atlantic offshore wind plant power production D. Rosencrans et al. 10.5194/wes-9-555-2024
- Brief communication: On the definition of the low-level jet C. Hallgren et al. 10.5194/wes-8-1651-2023
- Classification and properties of non-idealized coastal wind profiles – an observational study C. Hallgren et al. 10.5194/wes-7-1183-2022
- 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
- Estimating hub-height wind speed based on a machine learning algorithm: implications for wind energy assessment B. Liu et al. 10.5194/acp-23-3181-2023
- Characterization of wind speed and directional shear at the AWAKEN field campaign site M. Debnath et al. 10.1063/5.0139737
- Sensitivity analysis of numerical modeling input parameters on floating offshore wind turbine loads W. Wiley et al. 10.5194/wes-8-1575-2023
- Extreme wind load analysis using non-stationary risk-based approach M. Arif et al. 10.1007/s42797-022-00064-2
- 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
- Structure of Offshore Low-Level Jet Turbulence and Implications to Mesoscale-to-Microscale Coupling B. Jayaraman et al. 10.1088/1742-6596/2265/2/022064
- Offshore low-level jet observations and model representation using lidar buoy data off the California coast L. Sheridan et al. 10.5194/wes-9-741-2024
- Application of Nanometer Heavy-duty Coating in the Optimization of Process Parameters for Power Generation Machinery W. Long & N. Vasimalai 10.1155/2022/5600230
- Machine learning methods to improve spatial predictions of coastal wind speed profiles and low-level jets using single-level ERA5 data C. Hallgren et al. 10.5194/wes-9-821-2024
- Offshore wind energy forecasting sensitivity to sea surface temperature input in the Mid-Atlantic S. Redfern et al. 10.5194/wes-8-1-2023
1 citations as recorded by crossref.
Latest update: 20 Nov 2024
Short summary
As the offshore wind industry emerges on the US East Coast, a comprehensive understanding of the wind resource – particularly extreme events – is vital to the industry's success. We leverage a year of data of two floating lidars to quantify and characterize the frequent occurrence of high-wind-shear and low-level-jet events, both of which will have a considerable impact on turbine operation. We find that almost 100 independent long events occur throughout the year.
As the offshore wind industry emerges on the US East Coast, a comprehensive understanding of the...
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