Nonlinear Processes in Geophysics
Nonlinear Processes in Geophysics
NPG
Articles | Volume 30, issue 4
Articles | Volume 30, issue 4
https://doi.org/10.5194/npg-30-553-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/npg-30-553-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 30, issue 4
Research article
 | 
29 Nov 2023
Research article |  | 29 Nov 2023

Downscaling of surface wind forecasts using convolutional neural networks

Florian Dupuy, Pierre Durand, and Thierry Hedde

Viewed

Total article views: 2,098 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,688 342 68 2,098 75 61
  • HTML: 1,688
  • PDF: 342
  • XML: 68
  • Total: 2,098
  • BibTeX: 75
  • EndNote: 61
Views and downloads (calculated since 22 Jun 2023)
Cumulative views and downloads (calculated since 22 Jun 2023)

Viewed (geographical distribution)

Total article views: 2,098 (including HTML, PDF, and XML) Thereof 2,001 with geography defined and 97 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 31 Mar 2025
Download
Short summary
Forecasting near-surface winds over complex terrain requires high-resolution numerical weather prediction models, which drastically increase the duration of simulations and hinder them in running on a routine basis. A faster alternative is statistical downscaling. We explore different ways of calculating near-surface wind speed and direction using artificial intelligence algorithms based on various convolutional neural networks in order to find the best approach for wind downscaling.
Read more
Share