Articles | Volume 11, issue 11
https://doi.org/10.5194/wes-11-4077-2026
© 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-11-4077-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
03 Nov 2026
Research article |
| 03 Nov 2026
| 03 Nov 2026
Investigating the wind–wave interaction on mean wind and turbulence structure using COAWST with WRF-LES during a storm event
Technical University of Denmark, Frederiksborgvej 399, Roskilde 4000, Denmark
Xiaoli Guo Larsén
Technical University of Denmark, Frederiksborgvej 399, Roskilde 4000, Denmark
Alfredo Peña
Technical University of Denmark, Frederiksborgvej 399, Roskilde 4000, Denmark
Jana Fischereit
Technical University of Denmark, Frederiksborgvej 399, Roskilde 4000, Denmark
Oscar García-Santiago
Technical University of Denmark, Frederiksborgvej 399, Roskilde 4000, Denmark
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Jana Fischereit, Bjarke T. E. Olsen, Marc Imberger, Henrik Vedel, Kristian H. Møller, Andrea N. Hahmann, and Xiaoli Guo Larsén
Geosci. Model Dev., 19, 8115–8147, https://doi.org/10.5194/gmd-19-8115-2026, https://doi.org/10.5194/gmd-19-8115-2026, 2026
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We evaluated how operating wind farms influence the atmosphere in numerical weather prediction using two wind farm parameterizations in the HARMONIE-AROME model, applied by over 10 European weather services. Accurate yield forecasts require including both onshore and offshore turbines. Wind turbines slightly alter near-surface temperature (<1 K on average). We also present an open-access European wind turbine dataset combining multiple data sources.
Nicola Bodini, Patrick Moriarty, Regis Thedin, Paula Doubrawa, Cristina Archer, Myra Blaylock, Carlo Bottasso, Bruno Carmo, Lawrence Cheung, Camille Dubreuil, Rogier Floors, Thomas Herges, Daniel Houck, Ali Kanjari, Colleen M. Kaul, Christopher Kelley, Ru Li, Julie K. Lundquist, Desirae Major, Anh Kiet Nguyen, Mike Optis, Luan R. C. Parada, Alfredo Peña, Julian Quick, David Ricarte, William C. Radünz, Raj K. Rai, Oscar García-Santiago, Jonas Schulte, Knut S. Seim, M. Paul van der Laan, Kisorthman Vimalakanthan, and Adam Wise
Wind Energ. Sci., 11, 3107–3135, https://doi.org/10.5194/wes-11-3107-2026, https://doi.org/10.5194/wes-11-3107-2026, 2026
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Predicting wind farm energy production is challenging because wind patterns are complex. We tested 16 different models against real data from a major field experiment to see which worked best. Surprisingly, the most expensive and detailed models were not always more accurate than simpler ones. We found that feeding models better weather data was the most effective way to improve accuracy. These results help the industry choose the right tools for designing more-efficient wind farms.
Nicolas G. Alonso-de-Linaje, Andrea N. Hahmann, and Alfredo Peña
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2026-143, https://doi.org/10.5194/wes-2026-143, 2026
Preprint under review for WES
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Offshore wind farms create wind shadows that reduce energy for nearby farms. Traditional weather simulations require weeks of computing time, making extensive testing impractical. We developed a fast tool that estimates these wind shadows in seconds using turbine positions and local wind data. It closely matches detailed simulations for current and future North Sea layouts and is applicable in the Baltic Sea, enabling planners to evaluate many options quickly.
Nathalia Correa-Sánchez, Xiaoli Guo Larsén, Eleonora Dallan, Marco Borga, and Francesco Marra
Wind Energ. Sci., 11, 2961–2985, https://doi.org/10.5194/wes-11-2961-2026, https://doi.org/10.5194/wes-11-2961-2026, 2026
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This research presents the first use of the simplified metastatistical extreme value approach for wind extremes, extending it to wind energy applications. We use a categorical framework that combines climate, roughness, and topography to evaluate convection-permitted models. We find that model formulation drives inter-model uncertainties, rather than surface conditions. Convection-permitted models' uncertainty analysis improves the reliability of extreme wind estimates for design parameters.
Jens Peter Schøler, Frederik Peder Weilmann Rasmussen, M. Paul van der Laan, Alfredo Peña, and Pierre-Elouan Réthoré
Wind Energ. Sci., 11, 2869–2893, https://doi.org/10.5194/wes-11-2869-2026, https://doi.org/10.5194/wes-11-2869-2026, 2026
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As offshore wind farms are built closer together, predicting how they affect each other becomes critical. We compared two AI approaches for this task, training both on cheap approximate data before refining them with expensive high-accuracy simulations. One predicts wake boundaries better, while the other estimates wind speeds more accurately, offering complementary tools for future wind farm design.
Georgios Deskos, Jiali Wang, Sanjay Arwade, Murray Fisher, Brian Hirth, Xiaoli Guo Larsén, Julie K. Lundquist, Andrew Myers, Weichiang Pang, William J. Pringle, Robert Rogers, Miguel Sanchez-Gomez, Chao Sun, Atsushi Yamaguchi, and Paul Veers
Wind Energ. Sci., 11, 2749–2782, https://doi.org/10.5194/wes-11-2749-2026, https://doi.org/10.5194/wes-11-2749-2026, 2026
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Wind energy is expanding into regions exposed to tropical cyclones, where extreme winds and waves can damage turbines and disrupt energy production. We reviewed observations, simulations, engineering standards, and risk quantification frameworks to identify the most important gaps. Today's design rules, originally built for milder storms, do not capture cyclone hazards. Closing these gaps requires better offshore measurements, improved models, and risk-informed design standards.
Sinem Uluocak, Andreas Rott, Alfredo Peña, and Martin Kühn
EGUsphere, https://doi.org/10.5194/egusphere-2026-825, https://doi.org/10.5194/egusphere-2026-825, 2026
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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Wind lidar turbulence measurements are limited by large probe volume of lidar, which attenuates turbulence scales smaller than the probe volume. This process is known as probe volume averaging. This wind tunnel study enabled an experimental investigation of probe volume averaging for the first time, using 32 distinct probe volumes over integral length scale ratios. The study demonstrated the capability of lidar to measure along-wind turbulence statistics.
Keeta Chapman-Smith, Xiaoli Guo Larsén, and Mark Laier Brodersen
Wind Energ. Sci., 11, 1889–1912, https://doi.org/10.5194/wes-11-1889-2026, https://doi.org/10.5194/wes-11-1889-2026, 2026
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This study presents a method to estimate wind speeds that could occur in a 50-year period. The 50-year wind speed is calculated for three regions: Taiwan, Japan, and the east coast of the US. The method performs well in Taiwan and Japan, which can be attributed to the large dataset size located in a limited spatial area. The east coast of the US performs less well due to the smaller dataset size and wider spatial region that they cover.
Xiaoli Guo Larsén, Marc Imberger, and Rogier Floors
Wind Energ. Sci., 11, 1853–1869, https://doi.org/10.5194/wes-11-1853-2026, https://doi.org/10.5194/wes-11-1853-2026, 2026
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This study delivers a method and datasets for a global offshore atlas for turbulence intensity from a height of 10 m to 200 m. The method innovatively includes both two-dimensional and three-dimensional turbulence, along with stability, wave age and height. Results show satisfactory agreement with measurements and data from the literature.
Oscar García-Santiago, Jake Badger, Andrea N. Hahmann, Patrick J. H. Volker, Søren Ott, M. Paul van der Laan, and Mark Kelly
EGUsphere, https://doi.org/10.5194/egusphere-2026-2144, https://doi.org/10.5194/egusphere-2026-2144, 2026
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We improve how weather models represent the turbulence generated by wind turbines within and behind wind farms. Rather than adding this turbulence only at grid squares with turbine locations, the new method transports it through the wake as it moves downwind. Tests against high-resolution simulations of an idealised wind farm showed better agreement in wake turbulence and more accurate reductions in wind speed, providing a more realistic picture of wake effects across the wind farm.
Sara Müller, Xiaoli Guo Larsén, and Fei Hu
Wind Energ. Sci., 11, 961–981, https://doi.org/10.5194/wes-11-961-2026, https://doi.org/10.5194/wes-11-961-2026, 2026
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Wind farms are being developed in areas prone to tropical cyclones. However, it remains unclear whether turbulence models in current design standards, such as the Mann uniform shear model, are suitable for these conditions. For the first time, the Mann model is assessed in depth using high-frequency measurements from four typhoons. Larger-than-predicted spectral energy is found at small wavenumbers in the outer cyclone and, in some cases, in the crosswind component in the inner cyclone.
Branko Kosović, Sukanta Basu, Jacob Berg, Larry K. Berg, Sue E. Haupt, Xiaoli G. Larsén, Joachim Peinke, Richard J. A. M. Stevens, Paul Veers, and Simon Watson
Wind Energ. Sci., 11, 509–555, https://doi.org/10.5194/wes-11-509-2026, https://doi.org/10.5194/wes-11-509-2026, 2026
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Most human activity happens in the layer of the atmosphere which extends a few hundred meters to a couple of kilometers above the surface of the Earth. The flow in this layer is turbulent. Turbulence impacts wind power production and turbine lifespan. Optimizing wind turbine performance requires understanding how turbulence affects both wind turbine efficiency and reliability. This paper points to gaps in our knowledge that need to be addressed to effectively utilize wind resources.
Nathalia Correa-Sánchez, Xiaoli Guo Larsén, Giorgia Fosser, Eleonora Dallan, Marco Borga, and Francesco Marra
Wind Energ. Sci., 10, 2551–2561, https://doi.org/10.5194/wes-10-2551-2025, https://doi.org/10.5194/wes-10-2551-2025, 2025
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We examined the power spectra of wind speed in three convection-permitting models in central Europe and found that these models have a better representation of wind variability characteristics than standard wind datasets like the New European Wind Atlas, due to different simulation approaches, providing more reliable extreme wind predictions.
Etienne Cheynet, Jan Markus Diezel, Hilde Haakenstad, Øyvind Breivik, Alfredo Peña, and Joachim Reuder
Wind Energ. Sci., 10, 733–754, https://doi.org/10.5194/wes-10-733-2025, https://doi.org/10.5194/wes-10-733-2025, 2025
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This study analyses wind speed data at heights up to 500 m to support the design of future large offshore wind turbines and airborne wind energy systems. We compared three wind models (ERA5, NORA3, and NEWA) with lidar measurements at five sites using four performance metrics. ERA5 and NORA3 performed equally well offshore, with NORA3 typically outperforming the other two models onshore. More generally, the optimal choice of model depends on site, altitude, and evaluation criteria.
Alfredo Peña, Ginka G. Yankova, and Vasiliki Mallini
Wind Energ. Sci., 10, 83–102, https://doi.org/10.5194/wes-10-83-2025, https://doi.org/10.5194/wes-10-83-2025, 2025
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Lidars are vastly used in wind energy, but most users struggle when interpreting lidar turbulence measures. Here, we explain the difficulty in converting them into standard measurements. We show two ways of converting lidar to in situ turbulence measurements, both using neural networks: one of them is based on physics, while the other is purely data-driven. They show promising results when compared to high-quality turbulence measurements from a tall mast.
Sara Müller, Xiaoli Guo Larsén, and David Robert Verelst
Wind Energ. Sci., 9, 1153–1171, https://doi.org/10.5194/wes-9-1153-2024, https://doi.org/10.5194/wes-9-1153-2024, 2024
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Tropical cyclone winds are challenging for wind turbines. We analyze a tropical cyclone before landfall in a mesoscale model. The simulated wind speeds and storm structure are sensitive to the boundary parametrization. However, independent of the boundary layer parametrization, the median change in wind speed and wind direction with height is small relative to wind turbine design standards. Strong spatial organization of wind shear and veer along the rainbands may increase wind turbine loads.
Oscar García-Santiago, Andrea N. Hahmann, Jake Badger, and Alfredo Peña
Wind Energ. Sci., 9, 963–979, https://doi.org/10.5194/wes-9-963-2024, https://doi.org/10.5194/wes-9-963-2024, 2024
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This study compares the results of two wind farm parameterizations (WFPs) in the Weather Research and Forecasting model, simulating a two-turbine array under three atmospheric stabilities with large-eddy simulations. We show that the WFPs accurately depict wind speeds either near turbines or in the far-wake areas, but not both. The parameterizations’ performance varies by variable (wind speed or turbulent kinetic energy) and atmospheric stability, with reduced accuracy in stable conditions.
Jana Fischereit, Henrik Vedel, Xiaoli Guo Larsén, Natalie E. Theeuwes, Gregor Giebel, and Eigil Kaas
Geosci. Model Dev., 17, 2855–2875, https://doi.org/10.5194/gmd-17-2855-2024, https://doi.org/10.5194/gmd-17-2855-2024, 2024
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Wind farms impact local wind and turbulence. To incorporate these effects in weather forecasting, the explicit wake parameterization (EWP) is added to the forecasting model HARMONIE–AROME. We evaluate EWP using flight data above and downstream of wind farms, comparing it with an alternative wind farm parameterization and another weather model. Results affirm the correct implementation of EWP, emphasizing the necessity of accounting for wind farm effects in accurate weather forecasting.
Wei Fu, Feng Guo, David Schlipf, and Alfredo Peña
Wind Energ. Sci., 8, 1893–1907, https://doi.org/10.5194/wes-8-1893-2023, https://doi.org/10.5194/wes-8-1893-2023, 2023
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A high-quality preview of the rotor-effective wind speed is a key element of the benefits of feedforward pitch control. We model a one-beam lidar in the spinner of a 15 MW wind turbine. The lidar rotates with the wind turbine and scans the inflow in a circular pattern, mimicking a multiple-beam lidar at a lower cost. We found that a spinner-based one-beam lidar provides many more control benefits than the one on the nacelle, which is similar to a four-beam nacelle lidar for feedforward control.
Alessandro Sebastiani, James Bleeg, and Alfredo Peña
Wind Energ. Sci., 8, 1795–1808, https://doi.org/10.5194/wes-8-1795-2023, https://doi.org/10.5194/wes-8-1795-2023, 2023
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The power curve of a wind turbine indicates the turbine power output in relation to the wind speed. Therefore, power curves are critically important to estimate the production of future wind farms as well as to assess whether operating wind farms are functioning correctly. Since power curves are often measured in wind farms, they might be affected by the interactions between the turbines. We show that these effects are not negligible and present a method to correct for them.
Maarten Paul van der Laan, Oscar García-Santiago, Mark Kelly, Alexander Meyer Forsting, Camille Dubreuil-Boisclair, Knut Sponheim Seim, Marc Imberger, Alfredo Peña, Niels Nørmark Sørensen, and Pierre-Elouan Réthoré
Wind Energ. Sci., 8, 819–848, https://doi.org/10.5194/wes-8-819-2023, https://doi.org/10.5194/wes-8-819-2023, 2023
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Offshore wind farms are more commonly installed in wind farm clusters, where wind farm interaction can lead to energy losses. In this work, an efficient numerical method is presented that can be used to estimate these energy losses. The novel method is verified with higher-fidelity numerical models and validated with measurements of an existing wind farm cluster.
Wei Fu, Alessandro Sebastiani, Alfredo Peña, and Jakob Mann
Wind Energ. Sci., 8, 677–690, https://doi.org/10.5194/wes-8-677-2023, https://doi.org/10.5194/wes-8-677-2023, 2023
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Nacelle lidars with different beam scanning locations and two types of systems are considered for inflow turbulence estimations using both numerical simulations and field measurements. The turbulence estimates from a sonic anemometer at the hub height of a Vestas V52 turbine are used as references. The turbulence parameters are retrieved using the radial variances and a least-squares procedure. The findings from numerical simulations have been verified by the analysis of the field measurements.
Xiaoli Guo Larsén, Marc Imberger, Ásta Hannesdóttir, and Andrea N. Hahmann
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2022-102, https://doi.org/10.5194/wes-2022-102, 2023
Revised manuscript not accepted
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We study how climate change will impact extreme winds and choice of turbine class. We use data from 18 CMIP6 members from a historic and a future period to access the change in the extreme winds. The analysis shows an overall increase in the extreme winds in the North Sea and the southern Baltic Sea, but a decrease over the Scandinavian Peninsula and most of the Baltic Sea. The analysis is inconclusive to whether higher or lower classes of turbines will be installed in the future.
Xiaoli Guo Larsén and Søren Ott
Wind Energ. Sci., 7, 2457–2468, https://doi.org/10.5194/wes-7-2457-2022, https://doi.org/10.5194/wes-7-2457-2022, 2022
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A method is developed for calculating the extreme wind in tropical-cyclone-affected water areas. The method is based on the spectral correction method that fills in the missing wind variability to the modeled time series, guided by best track data. The paper provides a detailed recipe for applying the method and the 50-year winds of equivalent 10 min temporal resolution from 10 to 150 m in several tropical-cyclone-affected regions.
Andrea N. Hahmann, Oscar García-Santiago, and Alfredo Peña
Wind Energ. Sci., 7, 2373–2391, https://doi.org/10.5194/wes-7-2373-2022, https://doi.org/10.5194/wes-7-2373-2022, 2022
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We explore the changes in wind energy resources in northern Europe using output from simulations from the Climate Model Intercomparison Project (CMIP6) under the high-emission scenario. Our results show that climate change does not particularly alter annual energy production in the North Sea but could affect the seasonal distribution of these resources, significantly reducing energy production during the summer from 2031 to 2050.
Jana Fischereit, Kurt Schaldemose Hansen, Xiaoli Guo Larsén, Maarten Paul van der Laan, Pierre-Elouan Réthoré, and Juan Pablo Murcia Leon
Wind Energ. Sci., 7, 1069–1091, https://doi.org/10.5194/wes-7-1069-2022, https://doi.org/10.5194/wes-7-1069-2022, 2022
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Wind turbines extract kinetic energy from the flow to create electricity. This induces a wake of reduced wind speed downstream of a turbine and consequently downstream of a wind farm. Different types of numerical models have been developed to calculate this effect. In this study, we compared models of different complexity, together with measurements over two wind farms. We found that higher-fidelity models perform better and the considered rapid models cannot fully capture the wake effect.
Alessandro Sebastiani, Alfredo Peña, Niels Troldborg, and Alexander Meyer Forsting
Wind Energ. Sci., 7, 875–886, https://doi.org/10.5194/wes-7-875-2022, https://doi.org/10.5194/wes-7-875-2022, 2022
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The power performance of a wind turbine is often tested with the turbine standing in a row of several wind turbines, as it is assumed that the performance is not affected by the neighbouring turbines. We test this assumption with both simulations and measurements, and we show that the power performance can be either enhanced or lowered by the neighbouring wind turbines. Consequently, we also show how power performance testing might be biased when performed on a row of several wind turbines.
Wei Fu, Alfredo Peña, and Jakob Mann
Wind Energ. Sci., 7, 831–848, https://doi.org/10.5194/wes-7-831-2022, https://doi.org/10.5194/wes-7-831-2022, 2022
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Measuring the variability of the wind is essential to operate the wind turbines safely. Lidars of different configurations have been placed on the turbines’ nacelle to measure the inflow remotely. This work found that the multiple-beam lidar is the only one out of the three employed nacelle lidars that can give detailed information about the inflow variability. The other two commercial lidars, which have two and four beams, respectively, measure only the fluctuation in the along-wind direction.
Anna Rutgersson, Erik Kjellström, Jari Haapala, Martin Stendel, Irina Danilovich, Martin Drews, Kirsti Jylhä, Pentti Kujala, Xiaoli Guo Larsén, Kirsten Halsnæs, Ilari Lehtonen, Anna Luomaranta, Erik Nilsson, Taru Olsson, Jani Särkkä, Laura Tuomi, and Norbert Wasmund
Earth Syst. Dynam., 13, 251–301, https://doi.org/10.5194/esd-13-251-2022, https://doi.org/10.5194/esd-13-251-2022, 2022
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A natural hazard is a naturally occurring extreme event with a negative effect on people, society, or the environment; major events in the study area include wind storms, extreme waves, high and low sea level, ice ridging, heavy precipitation, sea-effect snowfall, river floods, heat waves, ice seasons, and drought. In the future, an increase in sea level, extreme precipitation, heat waves, and phytoplankton blooms is expected, and a decrease in cold spells and severe ice winters is anticipated.
Marcus Reckermann, Anders Omstedt, Tarmo Soomere, Juris Aigars, Naveed Akhtar, Magdalena Bełdowska, Jacek Bełdowski, Tom Cronin, Michał Czub, Margit Eero, Kari Petri Hyytiäinen, Jukka-Pekka Jalkanen, Anders Kiessling, Erik Kjellström, Karol Kuliński, Xiaoli Guo Larsén, Michelle McCrackin, H. E. Markus Meier, Sonja Oberbeckmann, Kevin Parnell, Cristian Pons-Seres de Brauwer, Anneli Poska, Jarkko Saarinen, Beata Szymczycha, Emma Undeman, Anders Wörman, and Eduardo Zorita
Earth Syst. Dynam., 13, 1–80, https://doi.org/10.5194/esd-13-1-2022, https://doi.org/10.5194/esd-13-1-2022, 2022
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As part of the Baltic Earth Assessment Reports (BEAR), we present an inventory and discussion of different human-induced factors and processes affecting the environment of the Baltic Sea region and their interrelations. Some are naturally occurring and modified by human activities, others are completely human-induced, and they are all interrelated to different degrees. The findings from this study can largely be transferred to other comparable marginal and coastal seas in the world.
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Short summary
We studied how winds and ocean waves affect each other during a North Sea storm. Using a multiscale approach that captures processes from kilometers down to meters, we linked wind and wave models and compared the results with real measurements. Our aim was to improve current simulation methods, and the findings show that this detailed approach provides more accurate storm predictions up to 100 m height.
We studied how winds and ocean waves affect each other during a North Sea storm. Using a...
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