Articles | Volume 11, issue 1
https://doi.org/10.5194/wes-11-13-2026
https://doi.org/10.5194/wes-11-13-2026
Research article
 | 
07 Jan 2026
Research article |  | 07 Jan 2026

Evaluation of a high-resolution regional climate simulation for surface and hub-height wind climatology over North America

Kyle Peco, Jiali Wang, Chunyong Jung, Gökhan Sever, Lindsay Sheridan, Jeremy Feinstein, Rao Kotamarthi, Caroline Draxl, Ethan Young, Avi Purkayastha, and Andrew Kumler

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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-2025-13', Anonymous Referee #1, 19 Mar 2025
  • RC2: 'Comment on wes-2025-13', Anonymous Referee #2, 24 Mar 2025
  • AC1: 'Comment on wes-2025-13', Kyle Peco, 03 May 2025

Peer review completion

AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload
AR by Kyle Peco on behalf of the Authors (26 Jun 2025)  Author's response 
EF by Mario Ebel (30 Jun 2025)  Manuscript   Author's tracked changes 
ED: Referee Nomination & Report Request started (21 Jul 2025) by Andrea Hahmann
RR by Anonymous Referee #1 (04 Aug 2025)
ED: Publish subject to minor revisions (review by editor) (31 Aug 2025) by Andrea Hahmann
AR by Kyle Peco on behalf of the Authors (08 Sep 2025)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (14 Sep 2025) by Andrea Hahmann
ED: Publish as is (14 Sep 2025) by Julia Gottschall (Chief editor)
AR by Kyle Peco on behalf of the Authors (20 Oct 2025)
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Short summary
This study presents a new wind dataset, generated by a convection-permitting regional climate model across North America. By validating the dataset against wind observations, we have demonstrated that this dataset captures the wind patterns over complex terrains more realistically than the European Centre for
Medium-Range Weather Forecasts (ECMWF) reanalysis version 5 (ERA5). Additionally, this study quantifies model uncertainty in wind speed, comparing it against interannual variability, to better inform wind farm siting. 
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