Articles | Volume 8, issue 2
https://doi.org/10.5194/amt-8-729-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-8-729-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
12 Feb 2015
Research article |
| 12 Feb 2015
A six-beam method to measure turbulence statistics using ground-based wind lidars
DTU Wind Energy, Risø campus, Roskilde, Denmark
DTU Wind Energy, Risø campus, Roskilde, Denmark
N. Vasiljevic
DTU Wind Energy, Risø campus, Roskilde, Denmark
G. Lea
DTU Wind Energy, Risø campus, Roskilde, Denmark
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- Investigation of wind load on 1,000 m-high super-tall buildings based on HFFB tests B. Li et al. 10.1002/stc.2068
- Overview of recent observations and simulations from the American WAKE experimeNt (AWAKEN) field campaign P. Moriarty et al. 10.1088/1742-6596/2505/1/012049
- Measurements of wind turbulence parameters by a conically scanning coherent Doppler lidar in the atmospheric boundary layer I. Smalikho & V. Banakh 10.5194/amt-10-4191-2017
- A new scanning scheme and flexible retrieval for mean winds and gusts from Doppler lidar measurements J. Steinheuer et al. 10.5194/amt-15-3243-2022
- Cold-Air Pool Processes in the Inn Valley During Föhn: A Comparison of Four Cases During the PIANO Campaign M. Haid et al. 10.1007/s10546-021-00663-9
- Errors in radial velocity variance from Doppler wind lidar H. Wang et al. 10.5194/amt-9-4123-2016
- A Review of Progress and Applications of Pulsed Doppler Wind LiDARs Z. Liu et al. 10.3390/rs11212522
- Assessing the potential of a commercial pulsed lidar for wind characterisation at a bridge site E. Cheynet et al. 10.1016/j.jweia.2016.12.002
- How does turbulence change approaching a rotor? J. Mann et al. 10.5194/wes-3-293-2018
- Case study of a bore wind-ramp event from lidar measurements and HRRR simulations over ARM Southern Great Plains Y. Pichugina et al. 10.1063/5.0161905
- Ten Years of Boundary-Layer and Wind-Power Meteorology at Høvsøre, Denmark A. Peña et al. 10.1007/s10546-015-0079-8
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- Characterization of wind turbine flow through nacelle-mounted lidars: a review S. Letizia et al. 10.3389/fmech.2023.1261017
- Lidar Methods and Tools for Studying the Atmospheric Turbulence at the Institute of Atmospheric Optics V. Banakh 10.1134/S1024856020010042
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- Mean wind vector estimation using the velocity–azimuth display (VAD) method: an explicit algebraic solution G. Teschke & V. Lehmann 10.5194/amt-10-3265-2017
- Coupling wind LiDAR fixed and volumetric scans for enhanced characterization of wind turbulence and flow three‐dimensionality M. Puccioni et al. 10.1002/we.2865
- Comparing triple and single Doppler lidar wind measurements with sonic anemometer data based on a new filter strategy for virtual tower measurements K. Wolz et al. 10.5194/gi-13-205-2024
- Reducing the Uncertainty of Lidar Measurements in Complex Terrain Using a Linear Model Approach M. Hofsäß et al. 10.3390/rs10091465
- Improvement of vertical velocity statistics measured by a Doppler lidar through comparison with sonic anemometer observations T. Bonin et al. 10.5194/amt-9-5833-2016
- Dependence of turbulence estimations on nacelle lidar scanning strategies W. Fu et al. 10.5194/wes-8-677-2023
- Field Study of Turbulence Intensity measurement by Nacelle Mounted Lidar (NML) Z. Liang et al. 10.1088/1742-6596/2265/2/022104
- Behavior and mechanisms of Doppler wind lidar error in varying stability regimes R. Robey & J. Lundquist 10.5194/amt-15-4585-2022
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- Improving lidar turbulence estimates for wind energy J. Newman et al. 10.1088/1742-6596/753/7/072010
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- Noise filtering options for conically scanning Doppler lidar measurements with low pulse accumulation E. Päschke & C. Detring 10.5194/amt-17-3187-2024
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- Combined wind lidar and cloud radar for high-resolution wind profiling J. Dias Neto et al. 10.5194/essd-15-769-2023
- lidarwind: A Python package for retrieving wind profiles from Doppler lidar observations J. Neto & G. Castelao 10.21105/joss.04852
- Evaluation of three lidar scanning strategies for turbulence measurements J. Newman et al. 10.5194/amt-9-1993-2016
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- Long-Range WindScanner System N. Vasiljević et al. 10.3390/rs8110896
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- Turbulence characterization from a forward-looking nacelle lidar A. Peña et al. 10.5194/wes-2-133-2017
- Estimation of turbulence dissipation rate from Doppler wind lidars and in situ instrumentation for the Perdigão 2017 campaign N. Wildmann et al. 10.5194/amt-12-6401-2019
- An error reduction algorithm to improve lidar turbulence estimates for wind energy J. Newman & A. Clifton 10.5194/wes-2-77-2017
- Influence of nacelle-lidar scanning patterns on inflow turbulence characterization W. Fu et al. 10.1088/1742-6596/2265/2/022016
- Holistic scan optimization of nacelle-mounted lidars for inflow and wake characterization at the RAAW and AWAKEN field campaigns S. Letizia et al. 10.1088/1742-6596/2505/1/012048
- Field Verification of Vehicle-Mounted All-Fiber Coherent Wind Measurement Lidar Based on Four-Beam Vertical Azimuth Display Scanning X. Zhang et al. 10.3390/rs15133377
- Lidar-based Estimation of Turbulence Intensity for Controller Scheduling D. Schlipf et al. 10.1088/1742-6596/1618/3/032053
- Response of the Land‐Atmosphere System Over North‐Central Oklahoma During the 2017 Eclipse D. Turner et al. 10.1002/2017GL076908
Saved (final revised paper)
Latest update: 16 Jul 2024
Short summary
A so-called six-beam method is proposed to measure atmospheric turbulence using a ground-based wind lidar. This method is presented as an alternative to the so-called velocity azimuth display (VAD) method that is routinely used in commercial wind lidars, and which usually results in significant averaging effects of measured turbulence.
A so-called six-beam method is proposed to measure atmospheric turbulence using a ground-based...
