Wind Energy Science
Wind Energy Science
WES
Articles | Volume 11, issue 6
Articles | Volume 11, issue 6
https://doi.org/10.5194/wes-11-2257-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-11-2257-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 11, issue 6
Research article
 | 
29 Jun 2026
Research article |  | 29 Jun 2026

Performance of reanalysis and mesoscale models off the coast of Hawai'i

Lindsay M. Sheridan, Raghavendra Krishnamurthy, Tien Manh Nguyen, Yi-Leng Chen, William I. Gustafson Jr., Ye Liu, Feng Hsiao, Rob K. Newsom, Preston Spicer, Evgueni Kassianov, Mikhail Pekour, Nicola Bodini, and Mark Severy

Viewed

Total article views: 1,193 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
693 447 53 1,193 50 73
  • HTML: 693
  • PDF: 447
  • XML: 53
  • Total: 1,193
  • BibTeX: 50
  • EndNote: 73
Views and downloads (calculated since 23 Sep 2025)
Cumulative views and downloads (calculated since 23 Sep 2025)

Viewed (geographical distribution)

Total article views: 1,193 (including HTML, PDF, and XML) Thereof 1,184 with geography defined and 9 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 29 Jun 2026
Download
Short summary
Wind simulations can contain significant errors, which can lead to inaccurate estimates of wind energy generation. Using observations from a floating lidar off Hawai'i, we hypothesize and establish that distinct simulation datasets will exhibit diverse ranges of errors in this offshore environment. The most commonly used simulation dataset produces the largest wind speed biases due to underestimation of fast wind speeds and misrepresentation of how wind speed varies throughout the day and night.
Read more
Share
Altmetrics
Final-revised paper
Preprint