Radar-derived precipitation climatology for wind turbine blade leading edge erosion

Letson, Frederick; Barthelmie, Rebecca J.; Pryor, Sara C.

doi:https://doi.org/10.5194/wes-5-331-2020

Articles | Volume 5, issue 1

https://doi.org/10.5194/wes-5-331-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Wind Energy Science Conference 2019

https://doi.org/10.5194/wes-5-331-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 5, issue 1

Research article

|

06 Mar 2020

Research article |

| 06 Mar 2020

Radar-derived precipitation climatology for wind turbine blade leading edge erosion

Frederick Letson, Rebecca J. Barthelmie, and Sara C. Pryor

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Final revised paper (published on 06 Mar 2020)
Preprint (discussion started on 13 Aug 2019)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Erosion of Wind Turbine Blade Leading Edge by Precipitation', Anonymous Referee #1, 02 Oct 2019
RC2: 'Review', Anonymous Referee #2, 17 Oct 2019
EC1: 'Please answer reviewers comments', Julio J. Melero, 17 Oct 2019
AC1: 'Authors' Response to Reviewers', Frederick Letson, 08 Nov 2019

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Frederick Letson on behalf of the Authors (08 Nov 2019) Author's response

ED: Referee Nomination & Report Request started (20 Nov 2019) by Julio J. Melero

RR by Anonymous Referee #2 (24 Nov 2019)

ED: Publish as is (29 Nov 2019) by Julio J. Melero

ED: Publish as is (02 Dec 2019) by Joachim Peinke (Chief editor)

AR by Frederick Letson on behalf of the Authors (04 Dec 2019)

Short summary

Wind turbine blade leading edge erosion (LEE) is potentially a significant source of energy loss and expense for wind farm operators. This study presents a novel approach to characterizing LEE potential from precipitation across the contiguous USA based on publicly available National Weather Service dual-polarization RADAR data. The approach is described in detail and illustrated using six locations distributed across parts of the USA that have substantial wind turbine deployments.