Articles | Volume 10, issue 10
https://doi.org/10.5194/wes-10-2117-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.Special issue:
Evaluating the ability of the operational High Resolution Rapid Refresh model version 3 (HRRRv3) and version 4 (HRRRv4) to forecast wind ramp events in the US Great Plains
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- Final revised paper (published on 06 Oct 2025)
- Preprint (discussion started on 09 Dec 2024)
Interactive discussion
Status: closed
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
| : Report abuse
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RC1: 'Comment on wes-2024-133', Anonymous Referee #1, 06 Jan 2025
- AC1: 'Reply on RC1', Laura Bianco, 18 Mar 2025
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RC2: 'Comment on wes-2024-133', Anonymous Referee #2, 14 Jan 2025
- AC2: 'Reply on RC2', Laura Bianco, 18 Mar 2025
Peer review completion
AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Laura Bianco on behalf of the Authors (18 Mar 2025)
Author's response
Author's tracked changes
Manuscript
ED: Referee Nomination & Report Request started (24 Mar 2025) by Alfredo Peña
RR by Anonymous Referee #1 (15 Apr 2025)

RR by Anonymous Referee #2 (16 Apr 2025)

ED: Reconsider after major revisions (22 Apr 2025) by Alfredo Peña

AR by Laura Bianco on behalf of the Authors (05 Jun 2025)
Author's response
Author's tracked changes
Manuscript
ED: Referee Nomination & Report Request started (07 Jun 2025) by Alfredo Peña
RR by Anonymous Referee #2 (30 Jun 2025)

RR by Anonymous Referee #3 (03 Jul 2025)

ED: Publish subject to technical corrections (03 Jul 2025) by Alfredo Peña

ED: Publish subject to technical corrections (09 Jul 2025) by Jakob Mann (Chief editor)

AR by Laura Bianco on behalf of the Authors (16 Jul 2025)
Author's response
Manuscript
Review of “Evaluating the ability of the operational High Resolution Rapid Refresh model version 3 (HRRRv3) and version 4 (HRRRv4) to forecast wind ramp events in the US Great Plains” by Bianco et al.
The manuscript evaluates the ability of the High Resolution Rapid Refresh (HRRR) numerical weather prediction model in forecasting wind ramp events in the U.S. Great Plains. The study focuses on two operational versions: HRRRv3 and HRRRv4. Utilizing the Ramp Tool and Metric (RT&M), it demonstrates that HRRRv4 outperforms HRRRv3 in skill, particularly in detecting up-ramp events during summer, which is vital for wind energy integration into the electric grid. The methodology includes using 10-m observational data from METAR stations and model outputs, with statistical analyses carried out for annual and seasonal variations.
The work is timely, addressing the critical need for reliable wind energy forecasting in the context of renewable energy integration. However, some areas require additional clarity or justification. The manuscript is well-written and accessible to a broad audience in meteorology and renewable energy fields.
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