Articles | Volume 8, issue 8
https://doi.org/10.5194/wes-8-1251-2023
© Author(s) 2023. 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-8-1251-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Aug 2023
Research article |
| 16 Aug 2023
| 16 Aug 2023
Lessons learned in coupling atmospheric models across scales for onshore and offshore wind energy
National Center for Atmospheric Research, Boulder, CO 80301, USA
Branko Kosović
National Center for Atmospheric Research, Boulder, CO 80301, USA
Larry K. Berg
Pacific Northwest National Laboratory, Richland, WA 99354, USA
Colleen M. Kaul
Pacific Northwest National Laboratory, Richland, WA 99354, USA
Matthew Churchfield
National Renewable Energy Laboratory, Golden, CO 80401, USA
Jeffrey Mirocha
Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
Dries Allaerts
Aerospace Engineering, Delft University of Technology, Delft, the Netherlands
Thomas Brummet
National Center for Atmospheric Research, Boulder, CO 80301, USA
Shannon Davis
Wind Energy Technology Office, U.S. Department of Energy, Washington, DC 20585, USA
Amy DeCastro
National Center for Atmospheric Research, Boulder, CO 80301, USA
Susan Dettling
National Center for Atmospheric Research, Boulder, CO 80301, USA
Caroline Draxl
National Renewable Energy Laboratory, Golden, CO 80401, USA
David John Gagne
National Center for Atmospheric Research, Boulder, CO 80301, USA
Patrick Hawbecker
National Center for Atmospheric Research, Boulder, CO 80301, USA
Pankaj Jha
Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
Timothy Juliano
National Center for Atmospheric Research, Boulder, CO 80301, USA
William Lassman
Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
Eliot Quon
National Renewable Energy Laboratory, Golden, CO 80401, USA
Raj K. Rai
Pacific Northwest National Laboratory, Richland, WA 99354, USA
Michael Robinson
Wind Energy Technology Office, U.S. Department of Energy, Washington, DC 20585, USA
William Shaw
Pacific Northwest National Laboratory, Richland, WA 99354, USA
Regis Thedin
National Renewable Energy Laboratory, Golden, CO 80401, USA
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Cited
15 citations as recorded by crossref.
- Sensitivity analysis of computational domain height for semi-infinite and finite-sized wind farms W. Chanprasert et al.
- On Predicting Offshore Hub Height Wind Speed and Wind Power Density in the Northeast US Coast Using High-Resolution WRF Model Configurations during Anticyclones Coinciding with Wind Drought T. Zaman et al.
- The actuator farm model for large eddy simulation (LES) of wind-farm-induced atmospheric gravity waves and farm–farm interaction S. Stipa et al.
- Development of Profile Assimilation Methods for Data-Driven Large Eddy Simulations A. Ajay et al.
- Model sensitivity across scales: a case study of simulating an offshore low-level jet P. Hawbecker et al.
- Investigating the impact of temporal wind-speed variations on wind power modeling using a dynamically coupled meso–microscale simulation framework Z. Wu et al.
- Measurement-driven large-eddy simulations of a diurnal cycle during a wake-steering field campaign E. Quon
- Stage-Aware Reconstruction of Typhoon Inflow for Offshore Wind Turbines Using WRF and TurbSim J. Wang et al.
- Dries Allaerts, 1989–2024 M. Bastankhah et al.
- Influences of lidar scanning parameters on wind turbine wake retrievals in complex terrain R. Robey & J. Lundquist
- TOSCA – an open-source, finite-volume, large-eddy simulation (LES) environment for wind farm flows S. Stipa et al.
- A Meso-Microscale Coupled Wind Farm Parameterization B. Du et al.
- Simulation and modeling of wind farms in baroclinic atmospheric boundary layers J. Kasper et al.
- From turbine-scale to wind farm-scale wake recovery: Understanding the transition J. Kasper & R. Stevens
- Data assimilation of generic boundary layer flows for wind turbine applications – an LES study L. Wrba et al.
15 citations as recorded by crossref.
- Sensitivity analysis of computational domain height for semi-infinite and finite-sized wind farms W. Chanprasert et al.
- On Predicting Offshore Hub Height Wind Speed and Wind Power Density in the Northeast US Coast Using High-Resolution WRF Model Configurations during Anticyclones Coinciding with Wind Drought T. Zaman et al.
- The actuator farm model for large eddy simulation (LES) of wind-farm-induced atmospheric gravity waves and farm–farm interaction S. Stipa et al.
- Development of Profile Assimilation Methods for Data-Driven Large Eddy Simulations A. Ajay et al.
- Model sensitivity across scales: a case study of simulating an offshore low-level jet P. Hawbecker et al.
- Investigating the impact of temporal wind-speed variations on wind power modeling using a dynamically coupled meso–microscale simulation framework Z. Wu et al.
- Measurement-driven large-eddy simulations of a diurnal cycle during a wake-steering field campaign E. Quon
- Stage-Aware Reconstruction of Typhoon Inflow for Offshore Wind Turbines Using WRF and TurbSim J. Wang et al.
- Dries Allaerts, 1989–2024 M. Bastankhah et al.
- Influences of lidar scanning parameters on wind turbine wake retrievals in complex terrain R. Robey & J. Lundquist
- TOSCA – an open-source, finite-volume, large-eddy simulation (LES) environment for wind farm flows S. Stipa et al.
- A Meso-Microscale Coupled Wind Farm Parameterization B. Du et al.
- Simulation and modeling of wind farms in baroclinic atmospheric boundary layers J. Kasper et al.
- From turbine-scale to wind farm-scale wake recovery: Understanding the transition J. Kasper & R. Stevens
- Data assimilation of generic boundary layer flows for wind turbine applications – an LES study L. Wrba et al.
Saved (final revised paper)
Latest update: 06 May 2026
Short summary
The Mesoscale to Microscale Coupling team, part of the U.S. Department of Energy Atmosphere to Electrons (A2e) initiative, has studied various important challenges related to coupling mesoscale models to microscale models. Lessons learned and discerned best practices are described in the context of the cases studied for the purpose of enabling further deployment of wind energy. It also points to code, assessment tools, and data for testing the methods.
The Mesoscale to Microscale Coupling team, part of the U.S. Department of Energy Atmosphere to...
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