Articles | Volume 10, issue 1
https://doi.org/10.5194/wes-10-117-2025
© Author(s) 2025. 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-10-117-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Simulations suggest offshore wind farms modify low-level jets
Daphne Quint
Department of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, Colorado 80309-0311, United States
National Renewable Energy Laboratory, Golden, Colorado 80401, United States
Julie K. Lundquist
CORRESPONDING AUTHOR
Department of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, Colorado 80309-0311, United States
National Renewable Energy Laboratory, Golden, Colorado 80401, United States
Ralph O'Conor Sustainable Energy Institute, Johns Hopkins University, Baltimore, Maryland 21218, United States
David Rosencrans
Department of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, Colorado 80309-0311, United States
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Cited
16 citations as recorded by crossref.
- Assessing the accuracy of a 3-year high-resolution mesoscale wind farm wake simulation with lidar and satellite radar data A. Palatos-Plexidas et al. https://doi.org/10.5194/wes-11-3555-2026
- Hungarian Drone-Based Wind Measurements During the WMO UAS Demonstration Campaign—A Low-Level Jet Case Study Á. Steierlein et al. https://doi.org/10.3390/drones10020118
- Modeling Offshore Wind Farm Performance in Coastal Low-Level Jets Using Coupled Mesoscale-Microscale Large Eddy Simulations T. Chatterjee et al. https://doi.org/10.1103/vj2s-gflw
- Model sensitivity across scales: a case study of simulating an offshore low-level jet P. Hawbecker et al. https://doi.org/10.5194/wes-11-51-2026
- The Prediction of Low-Level Jet Using Machine Learning Based on Turbulence Observations and Remote Sensing M. Chen et al. https://doi.org/10.3390/rs18030470
- Impact of atmospheric turbulence on performance and loads of wind turbines: knowledge gaps and research challenges B. Kosović et al. https://doi.org/10.5194/wes-11-509-2026
- A perspective on lessons learned and future needs for wind energy field campaigns N. Bodini et al. https://doi.org/10.1063/5.0252362
- Identification of wind inflow characteristics from nacelle lidar measurements in the induction zone of a 9 MW wind turbine Y. Fang et al. https://doi.org/10.1016/j.renene.2025.124523
- Sea surface warming and ocean-to-atmosphere feedback driven by large-scale offshore wind farms under seasonally stratified conditions H. Seo et al. https://doi.org/10.1126/sciadv.adw7603
- A total of 19 months of daily weather logging on the US east coast: the WFIP3 event log N. Bodini et al. https://doi.org/10.5194/wes-11-1949-2026
- 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
- Multi-season evaluation of temperature and wind in the marine boundary layer along the United States northeast coast in the High-Resolution Rapid Refresh model B. Adler et al. https://doi.org/10.5194/gmd-19-8627-2026
- Simulated meteorological impacts of offshore wind turbines and sensitivity to the amount of added turbulence kinetic energy D. Quint et al. https://doi.org/10.5194/wes-10-1269-2025
- 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
- Observations of the Marine Atmospheric Boundary Layer’s Response to a Solar Eclipse M. Solari et al. https://doi.org/10.1007/s10546-026-00973-w
- Extreme turbulence effects on wind turbine loads: A case study for the North China Plain using nacelle lidar F. Guo et al. https://doi.org/10.1016/j.renene.2026.125774
16 citations as recorded by crossref.
- Assessing the accuracy of a 3-year high-resolution mesoscale wind farm wake simulation with lidar and satellite radar data A. Palatos-Plexidas et al. https://doi.org/10.5194/wes-11-3555-2026
- Hungarian Drone-Based Wind Measurements During the WMO UAS Demonstration Campaign—A Low-Level Jet Case Study Á. Steierlein et al. https://doi.org/10.3390/drones10020118
- Modeling Offshore Wind Farm Performance in Coastal Low-Level Jets Using Coupled Mesoscale-Microscale Large Eddy Simulations T. Chatterjee et al. https://doi.org/10.1103/vj2s-gflw
- Model sensitivity across scales: a case study of simulating an offshore low-level jet P. Hawbecker et al. https://doi.org/10.5194/wes-11-51-2026
- The Prediction of Low-Level Jet Using Machine Learning Based on Turbulence Observations and Remote Sensing M. Chen et al. https://doi.org/10.3390/rs18030470
- Impact of atmospheric turbulence on performance and loads of wind turbines: knowledge gaps and research challenges B. Kosović et al. https://doi.org/10.5194/wes-11-509-2026
- A perspective on lessons learned and future needs for wind energy field campaigns N. Bodini et al. https://doi.org/10.1063/5.0252362
- Identification of wind inflow characteristics from nacelle lidar measurements in the induction zone of a 9 MW wind turbine Y. Fang et al. https://doi.org/10.1016/j.renene.2025.124523
- Sea surface warming and ocean-to-atmosphere feedback driven by large-scale offshore wind farms under seasonally stratified conditions H. Seo et al. https://doi.org/10.1126/sciadv.adw7603
- A total of 19 months of daily weather logging on the US east coast: the WFIP3 event log N. Bodini et al. https://doi.org/10.5194/wes-11-1949-2026
- 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
- Multi-season evaluation of temperature and wind in the marine boundary layer along the United States northeast coast in the High-Resolution Rapid Refresh model B. Adler et al. https://doi.org/10.5194/gmd-19-8627-2026
- Simulated meteorological impacts of offshore wind turbines and sensitivity to the amount of added turbulence kinetic energy D. Quint et al. https://doi.org/10.5194/wes-10-1269-2025
- 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
- Observations of the Marine Atmospheric Boundary Layer’s Response to a Solar Eclipse M. Solari et al. https://doi.org/10.1007/s10546-026-00973-w
- Extreme turbulence effects on wind turbine loads: A case study for the North China Plain using nacelle lidar F. Guo et al. https://doi.org/10.1016/j.renene.2026.125774
Saved (final revised paper)
Latest update: 14 Oct 2026
Short summary
Offshore wind farms will be built along the East Coast of the United States. Low-level jets (LLJs) – layers of fast winds at low altitudes – also occur here. LLJs provide wind resources and also influence moisture and pollution transport, so it is important to understand how they might change. We develop and validate an automated tool to detect LLJs and compare 1 year of simulations with and without wind farms. Here, we describe LLJ characteristics and how they change with wind farms.
Offshore wind farms will be built along the East Coast of the United States. Low-level jets...
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