Articles | Volume 6, issue 3
Wind Energ. Sci., 6, 935–948, 2021
https://doi.org/10.5194/wes-6-935-2021
Wind Energ. Sci., 6, 935–948, 2021
https://doi.org/10.5194/wes-6-935-2021

Research article 16 Jun 2021

Research article | 16 Jun 2021

New methods to improve the vertical extrapolation of near-surface offshore wind speeds

Mike Optis et al.

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on wes-2021-5', Anonymous Referee #1, 05 Mar 2021
    • AC2: 'Reply on RC1', Mike Optis, 23 Mar 2021
  • RC2: 'RC2', Anonymous Referee #2, 15 Mar 2021
    • AC1: 'Reply on RC2', Mike Optis, 23 Mar 2021

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Mike Optis on behalf of the Authors (23 Mar 2021)  Author's response    Author's tracked changes    Manuscript
ED: Publish as is (01 Apr 2021) by Joachim Peinke
ED: Publish as is (15 Apr 2021) by Joachim Peinke(Chief Editor)
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Short summary
Offshore wind turbines are huge, with rotor blades soon to extend up to nearly 300 m. Accurate modeling of winds across these heights is crucial for accurate estimates of energy production. However, we lack sufficient observations at these heights but have plenty of near-surface observations. Here we show that a basic machine-learning model can provide very accurate estimates of winds in this area, and much better than conventional techniques.