| DOI: | 10.1002/2016JD025593
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| 论文题名: | Parameterizing surface wind speed over complex topography |
| 作者: | Helbig N.; Mott R.; van Herwijnen A.; Winstral A.; Jonas T.
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| 刊名: | Journal of Geophysical Research: Atmospheres
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| ISSN: | 2169897X
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| 出版年: | 2017
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| 卷: | 122, 期:2 | | 起始页码: | 651
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| 结束页码: | 667
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| 语种: | 英语
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| 英文关键词: | ARPS
; coarse-scale wind speed
; Gaussian random fields
; sky view factor
; statistical downscaling
; subgrid parameterization
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| Scopus关键词: | climate modeling
; climate prediction
; downscaling
; Gaussian method
; parameterization
; spatial analysis
; statistical analysis
; surface wind
; terrain
; topography
; wind velocity
; Switzerland
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| 英文摘要: | Subgrid parameterizations are used in coarse-scale meteorological and land surface models to account for the impact of unresolved topography on wind speed. While various parameterizations have been suggested, these were generally validated on a limited number of measurements in specific geographical areas. We used high-resolution wind fields to investigate which terrain parameters most affect near-surface wind speed over complex topography under neutral conditions. Wind fields were simulated using the Advanced Regional Prediction System (ARPS) on Gaussian random fields as model topographies to cover a wide range of terrain characteristics. We computed coarse-scale wind speed, i.e., a spatial average over the large grid cell accounting for influence of unresolved topography, using a previously suggested subgrid parameterization for the sky view factor. We only require correlation length of subgrid topographic features and mean square slope in the coarse grid cell. Computed coarse-scale wind speed compared well with domain-averaged ARPS wind speed. To further statistically downscale coarse-scale wind speed, we use local, fine-scale topographic parameters, namely, the Laplacian of terrain elevations and mean square slope. Both parameters showed large correlations with fine-scale ARPS wind speed. Comparing downscaled numerical weather prediction wind speed with measurements from a large number of stations throughout Switzerland resulted in overall improved correlations and distribution statistics. Since we used a large number of model topographies to derive the subgrid parameterization and the downscaling framework, both are not scale dependent nor bound to a specific geographic region. Both can readily be implemented since they are based on easy to derive terrain parameters. ©2016. American Geophysical Union. All Rights Reserved. |
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| 资源类型: | 期刊论文
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/62720
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| Appears in Collections: | 影响、适应和脆弱性
气候减缓与适应
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作者单位: | WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
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| Recommended Citation: | |
Helbig N.,Mott R.,van Herwijnen A.,et al. Parameterizing surface wind speed over complex topography[J]. Journal of Geophysical Research: Atmospheres,2017-01-01,122(2)
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