Wind Energy Science
Wind Energy Science
WES
Articles | Volume 8, issue 4
Articles | Volume 8, issue 4
https://doi.org/10.5194/wes-8-621-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-8-621-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 8, issue 4
Research article
 | 
28 Apr 2023
Research article |  | 28 Apr 2023

Vertical extrapolation of Advanced Scatterometer (ASCAT) ocean surface winds using machine-learning techniques

Daniel Hatfield, Charlotte Bay Hasager, and Ioanna Karagali

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Ahsbahs, T., Nygaard, N. G., Newcombe, A., and Badger, M.: Wind farm wakes from sar and doppler radar, Remote Sens., 12, 462, https://doi.org/10.3390/rs12030462, 2020. a
Badger, M., Peña, A., Hahmann, A. N., Mouche, A. A., and Hasager, C. B.: Extrapolating satellite winds to turbine operating heights, J. Appl. Meteorol. Clim., 55, 975–991, https://doi.org/10.1175/JAMC-D-15-0197.1, 2016. a, b
Barthelmie, R. J. and Pryor, S.: Can satellite sampling of offshore wind speeds realistically represent wind speed distributions?, J. Appl. Meteorol., 42, 83–94, https://doi.org/10.1175/1520-0450(2003)042<0083:CSSOOW>2.0.CO;2, 2003. a
Belmonte Rivas, M. and Stoffelen, A.: Characterizing ERA-Interim and ERA5 surface wind biases using ASCAT, Ocean Sci., 15, 831–852, https://doi.org/10.5194/os-15-831-2019, 2019. a
Bodini, N. and Optis, M.: The importance of round-robin validation when assessing machine-learning-based vertical extrapolation of wind speeds, Wind Energ. Sci., 5, 489–501, https://doi.org/10.5194/wes-5-489-2020, 2020. a, b, c, d, e, f, g, h
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Wind observations at heights relevant to the operation of modern offshore wind farms, i.e. 100 m and more, are required to optimize their positioning and layout. Satellite wind retrievals provide observations of the wind field over large spatial areas and extensive time periods, yet their temporal resolution is limited and they are only representative at 10 m height. Machine-learning models are applied to lift these satellite winds to higher heights, directly relevant to wind energy purposes.
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