Assessment of Surface-Layer Coherent Structure Detection in Dual-Doppler Lidar Data Based on Virtual Measurements

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Stawiarski, C.; Träumner, K.; Kottmeier, C.; Knigge, C.; Raasch, S.: Assessment of Surface-Layer Coherent Structure Detection in Dual-Doppler Lidar Data Based on Virtual Measurements. In: Boundary-Layer Meteorology 156 (2015), Nr. 3, S. 371-393. DOI: https://doi.org/10.1007/s10546-015-0039-3

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/851

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Abstract: 
Dual-Doppler lidar has become a useful tool to investigate the wind-field structure in two-dimensional planes. However, lidar pulse width and scan duration entail significant and complex averaging in the resulting retrieved wind-field components. The effects of these processes on the wind-field structure remain difficult to investigate with in situ measurements. Based on high resolution large-eddy simulation (LES) data for the surface layer, we performed virtual dual-Doppler lidar measurements and two-dimensional data retrievals. Applying common techniques (integral length scale computation, wavelet analysis, two-dimensional clustering of low-speed streaks) to detect and quantify the length scales of the occurring coherent structures in both the LES and the virtual lidar wind fields, we found that, (i) dual-Doppler lidar measurements overestimate the correlation length due to inherent averaging processes, (ii) the wavelet analysis of lidar data produces reliable results, provided the length scales exceed a lower threshold as a function of the lidar resolution, and (iii) the low-speed streak clusters are too small to be detected directly by the dual-Doppler lidar. Furthermore, we developed and tested a method to correct the integral scale overestimation that, in addition to the dual-Doppler lidar, only requires high-resolution wind-speed variance measurements, e.g. at a tower or energy balance station.
License of this version: CC BY 4.0
Document Type: article
Publishing status: publishedVersion
Issue Date: 2015
Appears in Collections:Fakultät für Mathematik und Physik

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1 image of flag of Germany Germany 45 83.33%
2 image of flag of China China 6 11.11%
3 image of flag of United States United States 1 1.85%
4 image of flag of France France 1 1.85%
5 image of flag of Algeria Algeria 1 1.85%

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