Articles | Volume 10, issue 10
https://doi.org/10.5194/wes-10-2217-2025
© 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-10-2217-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Oct 2025
Research article |
| 17 Oct 2025
| 17 Oct 2025
Data assimilation of generic boundary layer flows for wind turbine applications – an LES study
Linus Wrba
CORRESPONDING AUTHOR
Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
Antonia Englberger
Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
Andreas Dörnbrack
Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
Gerard Kilroy
Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
Norman Wildmann
Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
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Jeffrey D. Thayer, Gerard Kilroy, and Norman Wildmann
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-38, https://doi.org/10.5194/wes-2025-38, 2025
Revised manuscript accepted for WES
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With increasing wind energy in the German energy grid, it is crucial to better understand how different types of weather (including thunderstorms) can impact wind turbines and the surrounding atmosphere. We find rapid wind changes associated with the leading edge of thunderstorm outflows within the height range of wind turbines that would quickly increase wind power output, with longer-lasting changes in the near-surface atmosphere that would affect subsequent wind turbine operations.
Norman Wildmann and Laszlo Györy
EGUsphere, https://doi.org/10.5194/egusphere-2025-241, https://doi.org/10.5194/egusphere-2025-241, 2025
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Fast temperature sensors are deployed on drones to accurately measure temperature changes and fluctuations in the atmosphere. Compared to standard sensors, these new sensors showed better accuracy, especially in rapidly changing temperatures. Over 100 drone flights confirmed the sensors' ability to measure temperature fast enough to compare to standard meteorological instruments. This new method provides valuable data for understanding atmospheric energy balance.
Theresa Harlass, Rebecca Dischl, Stefan Kaufmann, Raphael Märkl, Daniel Sauer, Monika Scheibe, Paul Stock, Tiziana Bräuer, Andreas Dörnbrack, Anke Roiger, Hans Schlager, Ulrich Schumann, Magdalena Pühl, Tobias Schripp, Tobias Grein, Linda Bondorf, Charles Renard, Maxime Gauthier, Mark Johnson, Darren Luff, Paul Madden, Peter Swann, Denise Ahrens, Reetu Sallinen, and Christiane Voigt
Atmos. Chem. Phys., 24, 11807–11822, https://doi.org/10.5194/acp-24-11807-2024, https://doi.org/10.5194/acp-24-11807-2024, 2024
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Emissions from aircraft have a direct impact on our climate. Here, we present airborne and ground-based measurement data of nitrogen oxides that were collected in the exhaust of an Airbus aircraft. We study the impact of burning fossil and sustainable aviation fuel on nitrogen oxide emissions at different engine settings related to combustor temperature, pressure and fuel flow. Further, we compare observations with engine emission models.
Rebecca Dischl, Daniel Sauer, Christiane Voigt, Theresa Harlaß, Felicitas Sakellariou, Raphael Märkl, Ulrich Schumann, Monika Scheibe, Stefan Kaufmann, Anke Roiger, Andreas Dörnbrack, Charles Renard, Maxime Gauthier, Peter Swann, Paul Madden, Darren Luff, Mark Johnson, Denise Ahrens, Reetu Sallinen, Tobias Schripp, Georg Eckel, Uwe Bauder, and Patrick Le Clercq
Atmos. Chem. Phys., 24, 11255–11273, https://doi.org/10.5194/acp-24-11255-2024, https://doi.org/10.5194/acp-24-11255-2024, 2024
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In-flight measurements of aircraft emissions burning 100 % sustainable aviation fuel (SAF) show reduced particle number concentrations up to 41 % compared to conventional jet fuel. Particle emissions are dependent on engine power setting, flight altitude, and fuel composition. Engine models show a good correlation with measurement results. Future increased prevalence of SAF can positively influence the climate impact of aviation.
Johannes Kistner, Lars Neuhaus, and Norman Wildmann
Atmos. Meas. Tech., 17, 4941–4955, https://doi.org/10.5194/amt-17-4941-2024, https://doi.org/10.5194/amt-17-4941-2024, 2024
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We use a fleet of multicopter drones to measure wind. To improve the accuracy of this wind measurement and to evaluate this improvement, we conducted experiments with the drones in a wind tunnel under various conditions. This wind tunnel can generate different kinds and intensities of wind. Here we measured with the drones and with other sensors as a reference and compared the results. We were able to improve our wind measurement and show how accurately it works in different situations.
Raphael Satoru Märkl, Christiane Voigt, Daniel Sauer, Rebecca Katharina Dischl, Stefan Kaufmann, Theresa Harlaß, Valerian Hahn, Anke Roiger, Cornelius Weiß-Rehm, Ulrike Burkhardt, Ulrich Schumann, Andreas Marsing, Monika Scheibe, Andreas Dörnbrack, Charles Renard, Maxime Gauthier, Peter Swann, Paul Madden, Darren Luff, Reetu Sallinen, Tobias Schripp, and Patrick Le Clercq
Atmos. Chem. Phys., 24, 3813–3837, https://doi.org/10.5194/acp-24-3813-2024, https://doi.org/10.5194/acp-24-3813-2024, 2024
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In situ measurements of contrails from a large passenger aircraft burning 100 % sustainable aviation fuel (SAF) show a 56 % reduction in contrail ice crystal numbers compared to conventional Jet A-1. Results from a climate model initialized with the observations suggest a significant decrease in radiative forcing from contrails. Our study confirms that future increased use of low aromatic SAF can reduce the climate impact from aviation.
Andreas Forstmaier, Jia Chen, Florian Dietrich, Juan Bettinelli, Hossein Maazallahi, Carsten Schneider, Dominik Winkler, Xinxu Zhao, Taylor Jones, Carina van der Veen, Norman Wildmann, Moritz Makowski, Aydin Uzun, Friedrich Klappenbach, Hugo Denier van der Gon, Stefan Schwietzke, and Thomas Röckmann
Atmos. Chem. Phys., 23, 6897–6922, https://doi.org/10.5194/acp-23-6897-2023, https://doi.org/10.5194/acp-23-6897-2023, 2023
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Large cities emit greenhouse gases which contribute to global warming. In this study, we measured the release of one important green house gas, methane, in Hamburg. Multiple sources that contribute to methane emissions were located and quantified. Methane sources were found to be mainly caused by human activity (e.g., by release from oil and gas refineries). Moreover, potential natural sources have been located, such as the Elbe River and lakes.
Tamino Wetz and Norman Wildmann
Wind Energ. Sci., 8, 515–534, https://doi.org/10.5194/wes-8-515-2023, https://doi.org/10.5194/wes-8-515-2023, 2023
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In the present study, for the first time, the SWUF-3D fleet of multirotors is deployed for field measurements on an operating 2 MW wind turbine (WT) in complex terrain. The fleet of multirotors has the potential to fill the meteorological gap of observations in the near wake of WTs with high-temporal and high-spatial-resolution wind vector measurements plus temperature, humidity and pressure. The flow up- and downstream of the WT is measured simultaneously at multiple spatial positions.
Benjamin Witschas, Sonja Gisinger, Stephan Rahm, Andreas Dörnbrack, David C. Fritts, and Markus Rapp
Atmos. Meas. Tech., 16, 1087–1101, https://doi.org/10.5194/amt-16-1087-2023, https://doi.org/10.5194/amt-16-1087-2023, 2023
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In this paper, a novel scan technique is applied to an airborne coherent Doppler wind lidar, enabling us to measure the vertical wind speed and the horizontal wind speed along flight direction simultaneously with a horizontal resolution of about 800 m and a vertical resolution of 100 m. The performed observations are valuable for gravity wave characterization as they allow us to calculate the leg-averaged momentum flux profile and, with that, the propagation direction of excited gravity waves.
Hans-Christoph Lachnitt, Peter Hoor, Daniel Kunkel, Martina Bramberger, Andreas Dörnbrack, Stefan Müller, Philipp Reutter, Andreas Giez, Thorsten Kaluza, and Markus Rapp
Atmos. Chem. Phys., 23, 355–373, https://doi.org/10.5194/acp-23-355-2023, https://doi.org/10.5194/acp-23-355-2023, 2023
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We present an analysis of high-resolution airborne measurements during a flight of the DEEPWAVE 2014 campaign in New Zealand. The focus of this flight was to study the effects of enhanced mountain wave activity over the Southern Alps. We discuss changes in the upstream and downstream distributions of N2O and CO and show that these changes are related to turbulence-induced trace gas fluxes which have persistent effects on the trace gas composition in the lower stratosphere.
Norman Wildmann and Tamino Wetz
Atmos. Meas. Tech., 15, 5465–5477, https://doi.org/10.5194/amt-15-5465-2022, https://doi.org/10.5194/amt-15-5465-2022, 2022
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Multicopter uncrewed aerial systems (UAS, also known as drones) are very easy to use systems for collecting data in the lowest part of the atmosphere. Wind and turbulence are parameters that are particularly important for understanding the dynamics in the atmosphere. Only with three-dimensional measurements of the wind can a full understanding can be achieved. In this study, we show how even the vertical wind through the UAS can be measured with good accuracy.
Julian Quimbayo-Duarte, Johannes Wagner, Norman Wildmann, Thomas Gerz, and Juerg Schmidli
Geosci. Model Dev., 15, 5195–5209, https://doi.org/10.5194/gmd-15-5195-2022, https://doi.org/10.5194/gmd-15-5195-2022, 2022
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The ultimate objective of this model evaluation is to improve boundary layer flow representation over complex terrain. The numerical model is tested against observations retrieved during the Perdigão 2017 field campaign (moderate complex terrain). We observed that the inclusion of a forest parameterization in the numerical model significantly improves the representation of the wind field in the atmospheric boundary layer.
Andreas Luther, Julian Kostinek, Ralph Kleinschek, Sara Defratyka, Mila Stanisavljević, Andreas Forstmaier, Alexandru Dandocsi, Leon Scheidweiler, Darko Dubravica, Norman Wildmann, Frank Hase, Matthias M. Frey, Jia Chen, Florian Dietrich, Jarosław Nȩcki, Justyna Swolkień, Christoph Knote, Sanam N. Vardag, Anke Roiger, and André Butz
Atmos. Chem. Phys., 22, 5859–5876, https://doi.org/10.5194/acp-22-5859-2022, https://doi.org/10.5194/acp-22-5859-2022, 2022
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Coal mining is an extensive source of anthropogenic methane emissions. In order to reduce and mitigate methane emissions, it is important to know how much and where the methane is emitted. We estimated coal mining methane emissions in Poland based on atmospheric methane measurements and particle dispersion modeling. In general, our emission estimates suggest higher emissions than expected by previous annual emission reports.
Sven Krautwurst, Konstantin Gerilowski, Jakob Borchardt, Norman Wildmann, Michał Gałkowski, Justyna Swolkień, Julia Marshall, Alina Fiehn, Anke Roiger, Thomas Ruhtz, Christoph Gerbig, Jaroslaw Necki, John P. Burrows, Andreas Fix, and Heinrich Bovensmann
Atmos. Chem. Phys., 21, 17345–17371, https://doi.org/10.5194/acp-21-17345-2021, https://doi.org/10.5194/acp-21-17345-2021, 2021
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Quantification of anthropogenic CH4 emissions remains challenging, but it is essential for near-term climate mitigation strategies. We use airborne remote sensing observations to assess bottom-up estimates of coal mining emissions from one of Europe's largest CH4 emission hot spots located in Poland. The analysis reveals that emissions from small groups of shafts can be disentangled, but caution is advised when comparing observations to commonly reported annual emissions.
Etienne Cheynet, Martin Flügge, Joachim Reuder, Jasna B. Jakobsen, Yngve Heggelund, Benny Svardal, Pablo Saavedra Garfias, Charlotte Obhrai, Nicolò Daniotti, Jarle Berge, Christiane Duscha, Norman Wildmann, Ingrid H. Onarheim, and Marte Godvik
Atmos. Meas. Tech., 14, 6137–6157, https://doi.org/10.5194/amt-14-6137-2021, https://doi.org/10.5194/amt-14-6137-2021, 2021
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The COTUR campaign explored the structure of wind turbulence above the ocean to improve the design of future multi-megawatt offshore wind turbines. Deploying scientific instruments offshore is both a financial and technological challenge. Therefore, lidar technology was used to remotely measure the wind above the ocean from instruments located on the seaside. The experimental setup is tailored to the study of the spatial correlation of wind gusts, which governs the wind loading on structures.
Julian Kostinek, Anke Roiger, Maximilian Eckl, Alina Fiehn, Andreas Luther, Norman Wildmann, Theresa Klausner, Andreas Fix, Christoph Knote, Andreas Stohl, and André Butz
Atmos. Chem. Phys., 21, 8791–8807, https://doi.org/10.5194/acp-21-8791-2021, https://doi.org/10.5194/acp-21-8791-2021, 2021
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Abundant mining and industrial activities in the Upper Silesian Coal Basin lead to large emissions of the potent greenhouse gas methane. This study quantifies these emissions with continuous, high-precision airborne measurements and dispersion modeling. Our emission estimates are in line with values reported in the European Pollutant Release and Transfer Register (E-PRTR 2017) but significantly lower than values reported in the Emissions Database for Global Atmospheric Research (EDGAR v4.3.2).
Tamino Wetz, Norman Wildmann, and Frank Beyrich
Atmos. Meas. Tech., 14, 3795–3814, https://doi.org/10.5194/amt-14-3795-2021, https://doi.org/10.5194/amt-14-3795-2021, 2021
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A fleet of quadrotors is presented as a system to measure the spatial distribution of atmospheric boundary layer flow. The big advantage of this approach is that multiple and flexible measurement points in space can be sampled synchronously. The algorithm to calculate the horizontal wind is based on the principle of aerodynamic drag and the related quadrotor dynamics. The validation reveals that an average accuracy of < 0.3 m s−1 for the wind speed and < 8° for the wind direction was achieved.
Wolfgang Woiwode, Andreas Dörnbrack, Inna Polichtchouk, Sören Johansson, Ben Harvey, Michael Höpfner, Jörn Ungermann, and Felix Friedl-Vallon
Atmos. Chem. Phys., 20, 15379–15387, https://doi.org/10.5194/acp-20-15379-2020, https://doi.org/10.5194/acp-20-15379-2020, 2020
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The lowermost-stratosphere moist bias in ECMWF analyses and 12 h forecasts is diagnosed for the Arctic winter-spring 2016 period by using two-dimensional GLORIA water vapor observations. The bias is already present in the initial conditions (i.e., the analyses), and sensitivity forecasts on time scales of < 12 h show hardly any sensitivity to modified spatial resolution and output frequency.
Antonia Englberger, Julie K. Lundquist, and Andreas Dörnbrack
Wind Energ. Sci., 5, 1623–1644, https://doi.org/10.5194/wes-5-1623-2020, https://doi.org/10.5194/wes-5-1623-2020, 2020
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Wind turbines rotate clockwise. The rotational direction of the rotor interacts with the nighttime veering wind, resulting in a rotational-direction impact on the wake. In the case of counterclockwise-rotating blades the streamwise velocity in the wake is larger in the Northern Hemisphere whereas it is smaller in the Southern Hemisphere.
Alina Fiehn, Julian Kostinek, Maximilian Eckl, Theresa Klausner, Michał Gałkowski, Jinxuan Chen, Christoph Gerbig, Thomas Röckmann, Hossein Maazallahi, Martina Schmidt, Piotr Korbeń, Jarosław Neçki, Pawel Jagoda, Norman Wildmann, Christian Mallaun, Rostyslav Bun, Anna-Leah Nickl, Patrick Jöckel, Andreas Fix, and Anke Roiger
Atmos. Chem. Phys., 20, 12675–12695, https://doi.org/10.5194/acp-20-12675-2020, https://doi.org/10.5194/acp-20-12675-2020, 2020
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A severe reduction of greenhouse gas emissions is necessary to fulfill the Paris Agreement. We use aircraft- and ground-based in situ observations of trace gases and wind speed from two flights over the Upper Silesian Coal Basin, Poland, for independent emission estimation. The derived methane emission estimates are within the range of emission inventories, carbon dioxide estimates are in the lower range and carbon monoxide emission estimates are slightly higher than emission inventory values.
Antonia Englberger, Andreas Dörnbrack, and Julie K. Lundquist
Wind Energ. Sci., 5, 1359–1374, https://doi.org/10.5194/wes-5-1359-2020, https://doi.org/10.5194/wes-5-1359-2020, 2020
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At night, the wind direction often changes with height, and this veer affects structures near the surface like wind turbines. Wind turbines usually rotate clockwise, but this rotational direction interacts with veer to impact the flow field behind a wind turbine. If another turbine is located downwind, the direction of the upwind turbine's rotation will affect the downwind turbine.
Cited articles
Abkar, M. and Porté-Agel, F.: Influence of atmospheric stability on wind-turbine wakes: A large-eddy simulation study, Physics of fluids, 27, 035104, https://doi.org/10.1063/1.4913695, 2015. a
Aitken, M. L., Kosović, B., Mirocha, J. D., and Lundquist, J. K.: Large eddy simulation of wind turbine wake dynamics in the stable boundary layer using the Weather Research and Forecasting Model, Journal of Renewable and Sustainable Energy, 6, https://doi.org/10.1063/1.4885111, 2014. a
Arcucci, R., D'Amore, L., Pistoia, J., Toumi, R., and Murli, A.: On the variational data assimilation problem solving and sensitivity analysis, Journal of Computational Physics, 335, 311–326, 2017. a
Bastankhah, M., Mohammadi, M. M., Lees, C., Diaz, G. P. N., Buxton, Oliver, R. H., and Ivanell, S.: A fast-running physics-based wake model for a semi-infinite wind farm, Journal of Fluid Mechanics, 985, A43, https://doi.org/10.1017/jfm.2024.282, 2024. a
Bhaganagar, K. and Debnath, M.: Implications of Stably Stratified Atmospheric Boundary Layer Turbulence on the Near-Wake Structure of Wind Turbines, Energies, 7, 5740–5763, https://doi.org/10.3390/en7095740, 2014. a, b, c, d
Chanprasert, W., Sharma, R. N., Cater, J. E., and Norris, S. E.: Large Eddy Simulation of wind turbine wake interaction in directionally sheared inflows, Renewable Energy, 201, 1096–1110, 2022. a
Deardorff, J. W.: Stratocumulus-capped mixed layers derived from a three-dimensional model, Boundary-layer meteorology, 18, 495–527, 1980. a
Dörnbrack, A.: Transient Tropopause Waves, Journal of the Atmospheric Sciences, 81, 1647–1668, 2024. a
Dudhia, J.: Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model, Journal of Atmospheric Sciences, 46, 3077–3107, 1989. a
Elliott, J. R. and Smolarkiewicz, P. K.: Eddy resolving simulations of turbulent solar convection, International Journal for Numerical Methods in Fluids, 39, 855–864, 2002. a
Englberger, A. and Dörnbrack, A.: Impact of neutral boundary-layer turbulence on wind-turbine wakes: a numerical modelling study, Boundary-Layer Meteorology, 162, 427–449, https://doi.org/10.1007/s10546-016-0208-z, 2017. a
Hansen, M. O. L.: Aerodynamics of Wind Turbines, Earthscan, ISBN 9781849770408, https://books.google.de/books?id=GVD_HDPix6YC (last access: 8 August 2025), 2013. a
Haupt, S. E., Kosović, B., Berg, L. K., Kaul, C. M., Churchfield, M., Mirocha, J., Allaerts, D., Brummet, T., Davis, S., DeCastro, A., Dettling, S., Draxl, C., Gagne, D. J., Hawbecker, P., Jha, P., Juliano, T., Lassman, W., Quon, E., Rai, R. K., Robinson, M., Shaw, W., and Thedin, R.: Lessons learned in coupling atmospheric models across scales for onshore and offshore wind energy, Wind Energ. Sci., 8, 1251–1275, https://doi.org/10.5194/wes-8-1251-2023, 2023. a, b
Heinze, R., Moseley, C., Böske, L. N., Muppa, S. K., Maurer, V., Raasch, S., and Stevens, B.: Evaluation of large-eddy simulations forced with mesoscale model output for a multi-week period during a measurement campaign, Atmos. Chem. Phys., 17, 7083–7109, https://doi.org/10.5194/acp-17-7083-2017, 2017. a, b
Hong, S.-Y. and Lim, J.-O. J.: The WRF single-moment 6-class microphysics scheme (WSM6), Asia-Pacific Journal of Atmospheric Sciences, 42, 129–151, 2006. a
Janjić, Z. I.: Nonsingular implementation of the Mellor-Yamada level 2.5 scheme in the NCEP Meso model, Office note, National Centers for Environmental Prediction (U.S.), https://repository.library.noaa.gov/view/noaa/11409 (last access: 8 August 2025), 2001. a
Jonkman, J., Butterfield, S., Musial, W., and Scott, G.: Definition of a 5-MW Reference Wind Turbine for Offshore System Development, National Renewable Energy Laboratory (NREL), Golden, CO, https://doi.org/10.2172/947422, 2009. a
Kain, J. S. and Fritsch, J. M.: A one-dimensional entraining/detraining plume model and its application in convective parameterization, Journal of Atmospheric Sciences, 47, 2784–2802, 1990. a
Kilroy, G.: Data assimilation of generic boundary-layer flows for wind-turbine applications – An LES study – WRF namelists, Zenodo [data set], https://doi.org/10.5281/zenodo.16321159, 2025. a, b
Kilroy, G., Englberger, A., Wrba, L., Bührend, L., and Wildmann, N.: Evaluation of turbulence characteristics in WRF simulations at WiValdi wind park, Journal of Physics: Conference Series, 2767, 052063, https://doi.org/10.1088/1742-6596/2767/5/052063, 2024. a
Mann, J.: The spatial structure of neutral atmospheric surface-layer turbulence, Journal of fluid mechanics, 273, 141–168, https://doi.org/10.1017/S0022112094001886, 1994. a
Maronga, B., Gryschka, M., Heinze, R., Hoffmann, F., Kanani-Sühring, F., Keck, M., Ketelsen, K., Letzel, M. O., Sühring, M., and Raasch, S.: The Parallelized Large-Eddy Simulation Model (PALM) version 4.0 for atmospheric and oceanic flows: model formulation, recent developments, and future perspectives, Geosci. Model Dev., 8, 2515–2551, https://doi.org/10.5194/gmd-8-2515-2015, 2015. a, b, c, d, e
Mellor, G. L. and Yamada, T.: Development of a turbulence closure model for geophysical fluid problems, Reviews of Geophysics, 20, 851–875, 1982. a
Mirocha, J. D., Kosovic, B., Aitken, M. L., and Lundquist, J. K.: Implementation of a generalized actuator disk wind turbine model into the weather research and forecasting model for large-eddy simulation applications, Journal of Renewable and Sustainable Energy, 6, 013104, https://doi.org/10.1063/1.4861061, 2014. a
Mirocha, J. D., Rajewski, D. A., Marjanovic, N., Lundquist, J. K., Kosović, B., Draxl, C., and Churchfield, M. J.: Investigating wind turbine impacts on near-wake flow using profiling lidar data and large-eddy simulations with an actuator disk model, Journal of Renewable and Sustainable Energy, 7, https://doi.org/10.1063/1.4928873, 2015. a
Mixa, T., Dörnbrack, A., and Rapp, M.: Nonlinear Simulations of Gravity Wave Tunneling and Breaking over Auckland Island, Journal of the Atmospheric Sciences, 78, 1567–1582, https://doi.org/10.1175/JAS-D-20-0230.1, 2021. a
Mlawer, E. J., Taubman, S. J., Brown, P. D., Iacono, M. J., and Clough, S. A.: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave, Journal of Geophysical Research: Atmospheres, 102, 16663–16682, 1997. a
Nakayama, H. and Takemi, T.: Development of a Data Assimilation Method Using Vibration Equation for Large-Eddy Simulations of Turbulent Boundary Layer Flows, Journal of Advances in Modeling Earth Systems, 12, e2019MS001872, https://doi.org/10.1029/2019MS001872, 2020. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t, u, v, w, x
Naughton, J., Balas, M., Gopalan, H., Gundling, C., Heinz, S., Kelly, R., Lindberg, W., Rai, R., Saini, M., and Sitaraman, J.: Turbulence and the isolated wind turbine, in: 6th AIAA theoretical fluid mechanics conference, American Institute of Aeronautics and Astronautics, 3612, https://doi.org/10.2514/6.2011-3612, 2011. a
Niu, G.-Y., Yang, Z.-L., Mitchell, K. E., Chen, F., Ek, M. B., Barlage, M., Kumar, A., Manning, K., Niyogi, D., Rosero, E., Tewari, E. and Xia, Y.: The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements, Journal of Geophysical Research: Atmospheres, 116, https://doi.org/10.1029/2010JD015139, 2011. a
Porté-Agel, F., Bastankhah, M., and Shamsoddin, S.: Wind-turbine and wind-farm flows: A review, Boundary-layer meteorology, 174, 1–59, 2020. a
Prusa, J. M., Smolarkiewicz, P. K., and Wyszogrodzki, A. A.: EULAG, a computational model for multiscale flows, Computers and Fluids, 37, 1193–1207, https://doi.org/10.1016/j.compfluid.2007.12.001, 2008. a, b
Rybchuk, A., Martínez-Tossas, L. A., Letizia, S., Hamilton, N., Scholbrock, A., Maric, E., Houck, D. R., Herges, T. G., de Velder, N. B., and Doubrawa, P.: Ensemble-Based, Large-Eddy Reconstruction of Wind Turbine Inflow in a Near-Stationary Atmospheric Boundary Layer Through Generative Artificial Intelligence, Wind Energy, 28, e70020, https://doi.org/10.1002/we.70020, 2025. a
Sanchez Gomez, M. and Lundquist, J. K.: The effect of wind direction shear on turbine performance in a wind farm in central Iowa, Wind Energ. Sci., 5, 125–139, https://doi.org/10.5194/wes-5-125-2020, 2020. a
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Liu, Z., Berner, J., Wang, W., Powers, J. G., Duda, M. G., and Barker, D. M.: A description of the advanced research WRF version 4, NCAR tech. note ncar/tn-556+ str, National Center for Atmospheric Research, 145, https://doi.org/10.5065/1dfh-6p97, 2019. a
Smolarkiewicz, P. K. and Margolin, L. O.: On forward-in-time differencing for fluids: Extension to a curvilinear framework, Monthly Weather Review, 121, 1847–1859, 1993. a
Smolarkiewicz, P. K. and Margolin, L. G.: On Forward-in-Time Differencing for Fluids: an Eulerian/Semi-Lagrangian Non-Hydrostatic Model for Stratified Flows, Atmosphere-Ocean, 35, 127–152, https://doi.org/10.1080/07055900.1997.9687345, 1997. a
Smolarkiewicz, P. K. and Margolin, L. G.: MPDATA: A Finite-Difference Solver for Geophysical Flows, Journal of Computational Physics, 140, 459–480, https://doi.org/10.1006/jcph.1998.5901, 1998. a, b
Smolarkiewicz, P. K. and Pudykiewicz, J. A.: A class of semi-Lagrangian approximations for fluids, Journal of Atmospheric Sciences, 49, 2082–2096, 1992. a
Spille-Kohoff, A. and Kaltenbach, H.-J.: Generation of turbulent inflow data with a prescribed shear-stress profile, in: DNS/LES Progress and challenges, Proceedings of the Third AFOSR International Conference on DNS/LES, 319 pp., https://apps.dtic.mil/sti/tr/pdf/ADP013648.pdf (last access: 8 August 2025), 2001. a
Stauffer, D. R. and Seaman, N. L.: Use of four-dimensional data assimilation in a limited-area mesoscale model. Part I: Experiments with synoptic-scale data, Monthly Weather Review, 118, 1250–1277, 1990. a
Stipa, S., Ajay, A., Allaerts, D., and Brinkerhoff, J.: TOSCA – an open-source, finite-volume, large-eddy simulation (LES) environment for wind farm flows, Wind Energ. Sci., 9, 297–320, https://doi.org/10.5194/wes-9-297-2024, 2024. a, b, c, d
Stull, R. B.: An introduction to boundary layer meteorology, Kluwer Academic Publishers, https://doi.org/10.1007/978-94-009-3027-8, 2003. a
Veers, P., Bottasso, C. L., Manuel, L., Naughton, J., Pao, L., Paquette, J., Robertson, A., Robinson, M., Ananthan, S., Barlas, T., Bianchini, A., Bredmose, H., Horcas, S. G., Keller, J., Madsen, H. A., Manwell, J., Moriarty, P., Nolet, S., and Rinker, J.: Grand challenges in the design, manufacture, and operation of future wind turbine systems, Wind Energ. Sci., 8, 1071–1131, https://doi.org/10.5194/wes-8-1071-2023, 2023. a
Vollmer, L., Steinfeld, G., Heinemann, D., and Kühn, M.: Estimating the wake deflection downstream of a wind turbine in different atmospheric stabilities: an LES study, Wind Energ. Sci., 1, 129–141, https://doi.org/10.5194/wes-1-129-2016, 2016. a, b, c
Wharton, S. and Lundquist, J. K.: Atmospheric stability affects wind turbine power collection, Environmental Research Letters, 7, 014005, https://doi.org/10.1088/1748-9326/7/1/014005, 2012. a
Wildmann, N., Päschke, E., Roiger, A., and Mallaun, C.: Towards improved turbulence estimation with Doppler wind lidar velocity-azimuth display (VAD) scans, Atmos. Meas. Tech., 13, 4141–4158, https://doi.org/10.5194/amt-13-4141-2020, 2020. a
Wildmann, N., Hagen, M., and Gerz, T.: Enhanced resource assessment and atmospheric monitoring of the research wind farm WiValdi, Journal of Physics: Conference Series, 2265, 022029, https://doi.org/10.1088/1742-6596/2265/2/022029, 2022. a, b
Short summary
It is crucial to understand the loads and power production of wind turbines under different atmospheric situations (e.g., night and day changes). Computational simulations are a widely used tool to get more knowledge of the performance and the wake of wind turbines. In this study realistic velocity profiles of the atmosphere are used as input for simulations so that these simulations become more realistic. The generated flow is used as inflow for wind turbine simulations.
It is crucial to understand the loads and power production of wind turbines under different...
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