Articles | Volume 7, issue 4
https://doi.org/10.5194/wes-7-1441-2022
https://doi.org/10.5194/wes-7-1441-2022
Research article
 | 
13 Jul 2022
Research article |  | 13 Jul 2022

High-resolution offshore wind resource assessment at turbine hub height with Sentinel-1 synthetic aperture radar (SAR) data and machine learning

Louis de Montera, Henrick Berger, Romain Husson, Pascal Appelghem, Laurent Guerlou, and Mauricio Fragoso

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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-2021-35', Anonymous Referee #1, 11 May 2021
    • AC1: 'Reply on RC1', Louis de Montera, 22 Jun 2021
  • RC2: 'Comment on wes-2021-35', Anonymous Referee #2, 05 Jul 2021
    • AC2: 'Reply on RC2', Louis de Montera, 12 Jul 2021

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Louis de Montera on behalf of the Authors (29 Sep 2021)  Author's response   Author's tracked changes   Manuscript 
ED: Reconsider after major revisions (13 Oct 2021) by Joachim Peinke
ED: Referee Nomination & Report Request started (10 Jan 2022) by Andrea Hahmann
RR by Anonymous Referee #1 (15 Jan 2022)
RR by Anonymous Referee #3 (16 Feb 2022)
ED: Reconsider after major revisions (03 Mar 2022) by Andrea Hahmann
AR by Louis de Montera on behalf of the Authors (22 Apr 2022)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (08 May 2022) by Andrea Hahmann
RR by Anonymous Referee #3 (18 May 2022)
ED: Publish subject to minor revisions (review by editor) (23 May 2022) by Andrea Hahmann
AR by Louis de Montera on behalf of the Authors (30 May 2022)  Author's response   Author's tracked changes   Manuscript 
ED: Publish subject to technical corrections (05 Jun 2022) by Andrea Hahmann
ED: Publish subject to technical corrections (24 Jun 2022) by Joachim Peinke (Chief editor)
AR by Louis de Montera on behalf of the Authors (28 Jun 2022)  Manuscript 
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Short summary
A novel method for estimating offshore wind resources at turbine hub height with synthetic aperture radar (SAR) satellites is presented. The machine learning algorithm uses as input geometrical parameters of the SAR sensors and parameters related to atmospheric stability. It is trained with Doppler wind lidar vertical profiles. The extractable wind power accuracy up to 200 m is within 3 %, and SAR can resolve the coastal wind gradient, unlike the Weather Research and Forecasting numerical mode.
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