Articles | Volume 16, issue 12
https://doi.org/10.5194/gmd-16-3553-2023
https://doi.org/10.5194/gmd-16-3553-2023
Model evaluation paper
 | 
28 Jun 2023
Model evaluation paper |  | 28 Jun 2023

Self-nested large-eddy simulations in PALM model system v21.10 for offshore wind prediction under different atmospheric stability conditions

Maria Krutova, Mostafa Bakhoday-Paskyabi, Joachim Reuder, and Finn Gunnar Nielsen

Related authors

Gaussian wake model fitting in a transient event over Alpha Ventus wind farm
Maria Krutova and Mostafa Bakhoday-Paskyabi
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2023-79,https://doi.org/10.5194/wes-2023-79, 2023
Revised manuscript not accepted
Short summary
Development of an automatic thresholding method for wake meandering studies and its application to the data set from scanning wind lidar
Maria Krutova, Mostafa Bakhoday-Paskyabi, Joachim Reuder, and Finn Gunnar Nielsen
Wind Energ. Sci., 7, 849–873, https://doi.org/10.5194/wes-7-849-2022,https://doi.org/10.5194/wes-7-849-2022, 2022
Short summary

Related subject area

Atmospheric sciences
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025,https://doi.org/10.5194/gmd-18-1661-2025, 2025
Short summary
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025,https://doi.org/10.5194/gmd-18-1635-2025, 2025
Short summary
Quantifying the analysis uncertainty for nowcasting application
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025,https://doi.org/10.5194/gmd-18-1545-2025, 2025
Short summary
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025,https://doi.org/10.5194/gmd-18-1505-2025, 2025
Short summary
The MESSy DWARF (based on MESSy v2.55.2)
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025,https://doi.org/10.5194/gmd-18-1265-2025, 2025
Short summary

Cited articles

Bak, C., Zahle, F., Bitsche, R., Kim, T., Yde, A., Henriksen, L., Hansen, M., Blasques, J., Gaunaa, M., and Natarajan, A.: The DTU 10-MW Reference Wind Turbine, Danish Wind Power Research 2013, Conference, 27–28 May 2013, Fredericia, Denmark, https://orbit.dtu.dk/en/publications/the-dtu-10-mw-reference-wind-turbine (last access: 27 June 2023), 2013. a
Beare, R. J., Macvean, M. K., Holtslag, A. A., Cuxart, J., Esau, I., Golaz, J. C., Jimenez, M. A., Khairoutdinov, M., Kosovic, B., Lewellen, D., Lund, T. S., Lundquist, J. K., McCabe, A., Moene, A. F., Noh, Y., Raasch, S., and Sullivan, P.: An Intercomparison of Large-Eddy Simulations of the Stable Boundary Layer, Bound.-Lay. Meteorol., 118, 247–272, https://doi.org/10.1007/S10546-004-2820-6, 2006. a
Bratton, D. C. and Womeldorf, C. A.: The wind shear exponent: Comparing measured against simulated values and analyzing the phenomena that affect the wind shear, in: ASME 2011 5th Int. Conf. Energy Sustain. ES 2011, 7–10 August 2011 Washington, DC, USA, PARTS A, B, AND C, American Society of Mechanical Engineers Digital Collection, 2245–2251, https://doi.org/10.1115/ES2011-54823, 2011. a
Clark, T. and Farley, R.: Severe downslope windstorm calculations in two and three spatial dimensions using anelastic interactive grid nesting: A possible mechanism for gustiness, J. Atmos. Sci., 41, 329–350, 1984. a
Dimitrov, N., Natarajan, A., and Mann, J.: Effects of normal and extreme turbulence spectral parameters on wind turbine loads, Renew. Energ., 101, 1180–1193, https://doi.org/10.1016/j.renene.2016.10.001, 2017. a
Download
Short summary
Local refinement of the grid is a powerful method allowing us to reduce the computational time while preserving the accuracy in the area of interest. Depending on the implementation, the local refinement may introduce unwanted numerical effects into the results. We study the wind speed common to the wind turbine operational speeds and confirm strong alteration of the result when the heat fluxes are present, except for the specific refinement scheme used.
Share