Articles | Volume 24, issue 7
https://doi.org/10.5194/acp-24-4047-2024
https://doi.org/10.5194/acp-24-4047-2024
Research article
 | 
04 Apr 2024
Research article |  | 04 Apr 2024

Extending the wind profile beyond the surface layer by combining physical and machine learning approaches

Boming Liu, Xin Ma, Jianping Guo, Renqiang Wen, Hui Li, Shikuan Jin, Yingying Ma, Xiaoran Guo, and Wei Gong

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Latest update: 22 Jun 2024
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Short summary
Accurate wind profile estimation, especially for the lowest few hundred meters of the atmosphere, is of great significance for the weather, climate, and renewable energy sector. We propose a novel method that combines the power-law method with the random forest algorithm to extend wind profiles beyond the surface layer. Compared with the traditional algorithm, this method has better stability and spatial applicability and can be used to obtain the wind profiles on different land cover types.
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