Wind Energy Science
Wind Energy Science
WES
Articles | Volume 11, issue 10
Articles | Volume 11, issue 10
https://doi.org/10.5194/wes-11-3823-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-11-3823-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 11, issue 10
Research article
 | 
09 Oct 2026
Research article |  | 09 Oct 2026

Identification of optimal ERA5 model level for wind resource assessments in mountainous terrain

Juan Contreras, Nicole van Lipzig, Esteban Samaniego, and Daniela Ballari

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Short summary
We researched how to improve wind speed estimates for wind resource assessments in the Andes mountains of Ecuador. Instead of relying only on near-ground data from a global reanalysis dataset, we tested wind speeds from higher levels in the atmosphere and combined them with masts measurements through a machine learning model. This strongly improved accuracy and reduced energy calculation errors, offering a more reliable and affordable way to obtain data for planning wind power in complex terrain.
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