Articles | Volume 11, issue 9
https://doi.org/10.5194/wes-11-3555-2026
© Author(s) 2026. 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-11-3555-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
18 Sep 2026
Research article |
| 18 Sep 2026
| 18 Sep 2026
Assessing the accuracy of a 3-year high-resolution mesoscale wind farm wake simulation with lidar and satellite radar data
Alexandros Palatos-Plexidas
CORRESPONDING AUTHOR
von Karman Institute for Fluid Dynamics, Environmental and Applied Fluid Dynamics, Waterloosesteenweg 72, 1640 Sint-Genesius-Rode, Belgium
Vrije Universiteit Brussel, Electronics and Informatics Department, Pleinlaan 2, 1050 Brussels, Belgium
Simone Gremmo
von Karman Institute for Fluid Dynamics, Environmental and Applied Fluid Dynamics, Waterloosesteenweg 72, 1640 Sint-Genesius-Rode, Belgium
Jeroen van Beeck
von Karman Institute for Fluid Dynamics, Environmental and Applied Fluid Dynamics, Waterloosesteenweg 72, 1640 Sint-Genesius-Rode, Belgium
Lesley De Cruz
Vrije Universiteit Brussel, Electronics and Informatics Department, Pleinlaan 2, 1050 Brussels, Belgium
Royal Meteorological Institute of Belgium, Observations and Research scientific services, Ringlaan 3, 1180 Brussels, Belgium
Wim Munters
von Karman Institute for Fluid Dynamics, Environmental and Applied Fluid Dynamics, Waterloosesteenweg 72, 1640 Sint-Genesius-Rode, Belgium
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Emmanuel Gillyns, Sophia Buckingham, Jeroen van Beeck, and Grégoire Winckelmans
Wind Energ. Sci., 11, 3531–3553, https://doi.org/10.5194/wes-11-3531-2026, https://doi.org/10.5194/wes-11-3531-2026, 2026
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We built a small wind turbine model and tested it in a wind tunnel while improving computer simulations. Results show simulations accurately predict wind turbine wake behavior behind spinning blades, matching measurements. Some differences remain near blade roots. Combining experiments with refined models helps engineers predict wind turbine performance with greater confidence, supporting more efficient renewable energy design.
Sara Porchetta, Wim Munters, Maxime Lejeune, Ruben Borgers, Sophia Buckingham, and Michael F. Howland
Wind Energ. Sci., 11, 3273–3294, https://doi.org/10.5194/wes-11-3273-2026, https://doi.org/10.5194/wes-11-3273-2026, 2026
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This study examines how a newly built offshore wind farm affects the power production of nearby existing wind farms. Using a full year of simulations, we compare detailed weather-based models with faster simplified models. The results show clear differences in predicted power losses, especially during calm summer conditions, highlighting the importance of model choice for future offshore wind farm planning and design.
Sara Porchetta, Michael F. Howland, Maxime Lejeune, Ruben Borgers, Sophia Buckingham, and Wim Munters
Wind Energ. Sci., 11, 3295–3319, https://doi.org/10.5194/wes-11-3295-2026, https://doi.org/10.5194/wes-11-3295-2026, 2026
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This study examines how a newly built offshore wind farm affects the power production of nearby existing wind farms. Using a full year of simulations, we compare detailed weather-based models with faster simplified models. The results show clear differences in predicted power losses, especially during calm summer conditions, highlighting the importance of model choice for future offshore wind farm planning and design.
Konstantinos Vratsinis, Rebeca Marini, Pieter-Jan Daems, Lukas Pauscher, Jeroen van Beeck, and Jan Helsen
Wind Energ. Sci., 11, 1803–1820, https://doi.org/10.5194/wes-11-1803-2026, https://doi.org/10.5194/wes-11-1803-2026, 2026
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Using data collected over 13 months at an offshore wind farm, our study shows that a wind turbine’s position within the farm influences its energy output at a given nacelle-measured wind speed. Front-row turbines respond differently to similar wind speeds and turbulence than those further back. This finding suggests that current methods for characterizing inflow conditions may not fully capture actual wind behavior, underscoring the need for improved performance analysis techniques.
Martin Bonte, Lesley De Cruz, Fabian Debal, and Stéphane Vannitsem
EGUsphere, https://doi.org/10.5194/egusphere-2026-1460, https://doi.org/10.5194/egusphere-2026-1460, 2026
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The predictability of the generative AI-based nowcasting model LDCast is evaluated over Belgium, together with the pysteps implementation of the nowcasting algorithm STEPS. It appears that the ensembles of both models correctly estimate the error size through their spread, but fail at spatially representing the error. The analysis is done for two dynamically different types of events, showing how the models adapt their ensembles depending on the situation.
Etienne Muller, Simone Gremmo, Felix Houtin-Mongrolle, Laurent Beaudet, Juliette Coussy, Luis A. Martínez-Tossas, and Pierre Bénard
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2026-37, https://doi.org/10.5194/wes-2026-37, 2026
Manuscript not accepted for further review
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The energy yield of wind turbines within wind farms can be increased with control strategies. One way consists in misaligning the turbines with respect to the wind direction, to redirect their wake away from downstream turbines. Using models and advanced simulations, this work confirms a true potential but stresses how measurement biases on the wind direction and the flow complexity may critically affect both the performance in the field, and the reliability of the field validation campaigns.
Anouk Dierickx, Wout Dewettinck, Bert Van Schaeybroeck, Lesley De Cruz, Steven Caluwaerts, Piet Termonia, and Hans Van de Vyver
Earth Syst. Sci. Data, 17, 6747–6762, https://doi.org/10.5194/essd-17-6747-2025, https://doi.org/10.5194/essd-17-6747-2025, 2025
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This study introduces the EURO-SUPREME dataset consisting of extreme precipitation events selected from a large ensemble of climate models over Europe. The dataset contains information on extreme precipitation events with a precipitation duration of 1 to 72 h that can lead to flooding, high mortality rates and infrastructure damage. We highlight the usefulness of the dataset as a benchmark for improving high-resolution climate models for risk assessment of future extreme floods.
Tsvetelina Ivanova, Sara Porchetta, Sophia Buckingham, Gertjan Glabeke, Jeroen van Beeck, and Wim Munters
Wind Energ. Sci., 10, 245–268, https://doi.org/10.5194/wes-10-245-2025, https://doi.org/10.5194/wes-10-245-2025, 2025
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This study explores how wind and power predictions can be improved by introducing local forcing of measurement data in a numerical weather model while taking into account the presence of neighboring wind farms. Practical implications for the wind energy industry include insights for informed offshore wind farm planning and decision-making strategies using open-source models, even under adverse weather conditions.
Majid Bastankhah, Marcus Becker, Matthew Churchfield, Caroline Draxl, Jay Prakash Goit, Mehtab Khan, Luis A. Martinez Tossas, Johan Meyers, Patrick Moriarty, Wim Munters, Asim Önder, Sara Porchetta, Eliot Quon, Ishaan Sood, Nicole van Lipzig, Jan-Willem van Wingerden, Paul Veers, and Simon Watson
Wind Energ. Sci., 9, 2171–2174, https://doi.org/10.5194/wes-9-2171-2024, https://doi.org/10.5194/wes-9-2171-2024, 2024
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Dries Allaerts was born on 19 May 1989 and passed away at his home in Wezemaal, Belgium, on 10 October 2024 after battling cancer. Dries started his wind energy career in 2012 and had a profound impact afterward on the community, in terms of both his scientific realizations and his many friendships and collaborations in the field. His scientific acumen, open spirit of collaboration, positive attitude towards life, and playful and often cheeky sense of humor will be deeply missed by many.
Vera Melinda Galfi, Tommaso Alberti, Lesley De Cruz, Christian L. E. Franzke, and Valerio Lembo
Nonlin. Processes Geophys., 31, 185–193, https://doi.org/10.5194/npg-31-185-2024, https://doi.org/10.5194/npg-31-185-2024, 2024
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In the online seminar series "Perspectives on climate sciences: from historical developments to future frontiers" (2020–2021), well-known and established scientists from several fields – including mathematics, physics, climate science and ecology – presented their perspectives on the evolution of climate science and on relevant scientific concepts. In this paper, we first give an overview of the content of the seminar series, and then we introduce the written contributions to this special issue.
Etienne Muller, Simone Gremmo, Félix Houtin-Mongrolle, Bastien Duboc, and Pierre Bénard
Wind Energ. Sci., 9, 25–48, https://doi.org/10.5194/wes-9-25-2024, https://doi.org/10.5194/wes-9-25-2024, 2024
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This article presents an advanced tool designed for the high-fidelity and high-performance simulation of operating wind turbines, allowing for instance the computation of a blade deformation, as well as of the surrounding airflow. As this tool relies on coupling two existing codes, the coupling strategy is first described in depth. The article then compares the code results to field data for validation.
Adithya Vemuri, Sophia Buckingham, Wim Munters, Jan Helsen, and Jeroen van Beeck
Wind Energ. Sci., 7, 1869–1888, https://doi.org/10.5194/wes-7-1869-2022, https://doi.org/10.5194/wes-7-1869-2022, 2022
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The sensitivity of the WRF mesoscale modeling framework in accurately representing and predicting wind-farm-level environmental variables for three extreme weather events over the Belgian North Sea is investigated in this study. The overall results indicate highly sensitive simulation results to the type and combination of physics parameterizations and the type of the weather phenomena, with indications that scale-aware physics parameterizations better reproduce wind-related variables.
Nicolas Ghilain, Stéphane Vannitsem, Quentin Dalaiden, Hugues Goosse, Lesley De Cruz, and Wenguang Wei
Earth Syst. Sci. Data, 14, 1901–1916, https://doi.org/10.5194/essd-14-1901-2022, https://doi.org/10.5194/essd-14-1901-2022, 2022
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Modeling the climate at high resolution is crucial to represent the snowfall accumulation over the complex orography of the Antarctic coast. While ice cores provide a view constrained spatially but over centuries, climate models can give insight into its spatial distribution, either at high resolution over a short period or vice versa. We downscaled snowfall accumulation from climate model historical simulations (1850–present day) over Dronning Maud Land at 5.5 km using a statistical method.
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Short summary
In this study, we use advanced weather simulations, real-world measurements, and satellite images, showing that modeling wind farm effects improves accuracy, especially in areas influenced by turbines. Focusing on one of the largest wind farm clusters in the North Sea, we investigate wind speed deficits based on different atmospheric conditions. These findings help quantify the influence of large wind farm clusters, improve predictions, and support planning for future wind energy development.
In this study, we use advanced weather simulations, real-world measurements, and satellite...
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