2016
DOI: 10.3390/rs8090782
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An Inter-Comparison Study of Multi- and DBS Lidar Measurements in Complex Terrain

Abstract: Wind measurements using classical profiling lidars suffer from systematic measurement errors in complex terrain. Moreover, their ability to measure turbulence quantities is unsatisfactory for wind-energy applications. This paper presents results from a measurement campaign during which multiple WindScanners were focused on one point next to a reference mast in complex terrain. This multi-lidar (ML) technique is also compared to a profiling lidar using the Doppler beam swinging (DBS) method. First-and second-or… Show more

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Cited by 63 publications
(70 citation statements)
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“…On the other hand, Mann [45] found strong effects of stability on spectra over the Great Belt, Denmark, up to over 16 m·s −1 , albeit at a height of 70 m. When the high-frequency range of the N400 wind spectrum is attenuated using the ABSA model presented in Equation (26), the slope of the high-frequency part of the modified spectrum is sharper than measured, as seen in Figure 9. Similar observations have been reported by e.g., Pauscher et al [7] with the long-range WindScanner system or e.g., Angelou et al [46] with the short-range WindScanner system. The discrepancies between the modelled ABSA and the measured one may be due to fluctuations of the wind direction and the use of multiple scanning beams to retrieve the horizontal wind components.…”
Section: Wind Spectra Comparisonsupporting
confidence: 78%
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“…On the other hand, Mann [45] found strong effects of stability on spectra over the Great Belt, Denmark, up to over 16 m·s −1 , albeit at a height of 70 m. When the high-frequency range of the N400 wind spectrum is attenuated using the ABSA model presented in Equation (26), the slope of the high-frequency part of the modified spectrum is sharper than measured, as seen in Figure 9. Similar observations have been reported by e.g., Pauscher et al [7] with the long-range WindScanner system or e.g., Angelou et al [46] with the short-range WindScanner system. The discrepancies between the modelled ABSA and the measured one may be due to fluctuations of the wind direction and the use of multiple scanning beams to retrieve the horizontal wind components.…”
Section: Wind Spectra Comparisonsupporting
confidence: 78%
“…For the standard deviation, the squared correlation coefficient is also significantly large and equal to 0.95, but a systematic discrepancy is observed between the lidar data and the sonic anemometer data, which is expected and attributed to the spatial averaging effect. The results presented in Figures 5 and 6 are not surprising, as a similar comparison with sonic data has already been done in the past by Pauscher et al [7]. Nevertheless, the comparison given herein shows that the wind data recorded by the multi-lidar system in the Bjørnafjord and presented in the following are reliable.…”
Section: Preliminary Comparison With a Sonic Anemometer On Landmentioning
confidence: 46%
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“…Among the project deliverables, the methodology for WindScanner-based field experiments (which we report in the present paper) was developed based on the previous extensive work done under the WindScanner.dk project (see Vasiljević et al, 2016a;Sjöholm et al, 2014). The methodology was brought in to be tested and was further improved in a campaign held in Kassel (Germany) during the summer of 2014 (Pauscher et al, 2016;Vasiljević et al, 2016a). Perdigão 2015 was a last demonstration campaign within the WindScanner.eu project that served as the preparation for the larger experiment conducted within the NEWA project (New European Wind Atlas, The NEWA project aims to improve wind resource modeling for different site conditions.…”
Section: Perdigão-2015 Implementation Of Methodologymentioning
confidence: 99%
“…To minimise the different volume averaging effects and to comply with other comparisons of LiDAR measurements and met mast anemometers [29][30][31][32][33], we applied filtering in clustered temporal segments of ∆T = 10 min. We have deliberately refrained a data availability pre-filtering for the calculation of the 10 min average velocity and velocity standard deviation.…”
Section: Evaluation Of Filtering Based On Staring Measurementsmentioning
confidence: 99%