Articles | Volume 16, issue 8
https://doi.org/10.5194/acp-16-5229-2016
https://doi.org/10.5194/acp-16-5229-2016
Research article
 | 
27 Apr 2016
Research article |  | 27 Apr 2016

Downscaling surface wind predictions from numerical weather prediction models in complex terrain with WindNinja

Natalie S. Wagenbrenner, Jason M. Forthofer, Brian K. Lamb, Kyle S. Shannon, and Bret W. Butler

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Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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AR: Author's response | RR: Referee report | ED: Editor decision
AR by Natalie Wagenbrenner on behalf of the Authors (26 Mar 2016)  Author's response    Manuscript
ED: Reconsider after major revisions (10 Apr 2016) by Timothy Garrett
AR by Natalie Wagenbrenner on behalf of the Authors (10 Apr 2016)  Author's response    Manuscript
ED: Publish as is (14 Apr 2016) by Timothy Garrett
AR by Natalie Wagenbrenner on behalf of the Authors (16 Apr 2016)  Author's response    Manuscript
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Short summary
We investigated the ability of WindNinja to improve wind predictions in complex terrain. Predictions are compared with surface observations from a tall, isolated mountain. Results show that WindNinja is capable of capturing important local-scale flow features induced by mechanical and thermal effects of the underlying terrain and incorporating those terrain-driven flow features into coarse-scale weather forecasts in order to improve near-surface wind predictions in complex terrain.
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