Articles | Volume 17, issue 6
https://doi.org/10.5194/amt-17-1837-2024
https://doi.org/10.5194/amt-17-1837-2024
Research article
 | 
02 Apr 2024
Research article |  | 02 Apr 2024

Directly measuring the power-law exponent and kinetic energy of atmospheric turbulence using coherent Doppler wind lidar

Jinhong Xian, Chao Lu, Xiaoling Lin, Honglong Yang, Ning Zhang, and Li Zhang

Related authors

Characteristics of Boundary Layer Turbulence Energy Budget in Shenzhen Area Based on Coherent Wind Lidar Observations
Jinhong Xian, Zongxu Qiu, Huayan Rao, Zhigang Cheng, Xiaoling Lin, Chao Lu, Honglong Yang, and Ning Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2025-157,https://doi.org/10.5194/egusphere-2025-157, 2025
Short summary
Turbulent energy budget analysis based on coherent wind lidar observations
Jinhong Xian, Zongxu Qiu, Hongyan Luo, Yuanyuan Hu, Xiaoling Lin, Chao Lu, Yan Yang, Honglong Yang, and Ning Zhang
Atmos. Chem. Phys., 25, 441–457, https://doi.org/10.5194/acp-25-441-2025,https://doi.org/10.5194/acp-25-441-2025, 2025
Short summary

Related subject area

Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Instruments and Platforms
Spectral performance analysis of the Fizeau interferometer on board ESA's Aeolus wind lidar satellite
Michael Vaughan, Kevin Ridley, Benjamin Witschas, Oliver Lux, Ines Nikolaus, and Oliver Reitebuch
Atmos. Meas. Tech., 18, 2149–2181, https://doi.org/10.5194/amt-18-2149-2025,https://doi.org/10.5194/amt-18-2149-2025, 2025
Short summary
Tracking traveling ionospheric disturbances through Doppler-shifted AM radio transmissions
Claire C. Trop, James LaBelle, Philip J. Erickson, Shun-Rong Zhang, David McGaw, and Terrence Kovacs
Atmos. Meas. Tech., 18, 1909–1925, https://doi.org/10.5194/amt-18-1909-2025,https://doi.org/10.5194/amt-18-1909-2025, 2025
Short summary
Chilean Observation Network De Meteor Radars (CONDOR): multi-static system configuration and wind comparison with co-located lidar
Zishun Qiao, Alan Z. Liu, Gunter Stober, Javier Fuentes, Fabio Vargas, Christian L. Adami, and Iain M. Reid
Atmos. Meas. Tech., 18, 1091–1104, https://doi.org/10.5194/amt-18-1091-2025,https://doi.org/10.5194/amt-18-1091-2025, 2025
Short summary
ScintPi measurements of low-latitude ionospheric irregularity drifts using the spaced-receiver technique and SBAS signals
Josemaria Gomez Socola, Fabiano S. Rodrigues, Isaac G. Wright, Igo Paulino, and Ricardo Buriti
Atmos. Meas. Tech., 18, 909–919, https://doi.org/10.5194/amt-18-909-2025,https://doi.org/10.5194/amt-18-909-2025, 2025
Short summary
The Atmospheric Sounder Spectrometer by Infrared Spectral Technology (ASSIST): Instrument design and signal processing
Vincent Michaud-Belleau, Michel Gaudreau, Jean Lacoursière, Éric Boisvert, Lalaina Ravelomanantsoa, David D. Turner, and Luc Rochette
EGUsphere, https://doi.org/10.5194/egusphere-2024-3617,https://doi.org/10.5194/egusphere-2024-3617, 2025
Short summary

Cited articles

Banakh, V. and Smalikho, I.: Coherent Doppler Wind Lidars in a Turbulent Atmosphere, Artech House Publishers, Boston, London, ISBN 9781608076673, 2013. 
Banakh, V. A., Smalikho, I. N., Falits, A. V., and Sherstobitov, A. M.: Estimating the Parameters of Wind Turbulence from Spectra of Radial Velocity Measured by a Pulsed Doppler Lidar, Remote Sens., 13, 2071, https://doi.org/10.3390/rs13112071, 2021. 
Bonin, T. A., Newman, J. F., Klein, P. M., Chilson, P. B., and Wharton, S.: Improvement of vertical velocity statistics measured by a Doppler lidar through comparison with sonic anemometer observations, Atmos. Meas. Tech., 9, 5833–5852, https://doi.org/10.5194/amt-9-5833-2016, 2016. 
Bonin, T. A., Choukulkar, A., Brewer, W. A., Sandberg, S. P., Weickmann, A. M., Pichugina, Y. L., Banta, R. M., Oncley, S. P., and Wolfe, D. E.: Evaluation of turbulence measurement techniques from a single Doppler lidar, Atmos. Meas. Tech., 10, 3021–3039, https://doi.org/10.5194/amt-10-3021-2017, 2017. 
Branlard, E., Pedersen, A. T., Mann, J., Angelou, N., Fischer, A., Mikkelsen, T., Harris, M., Slinger, C., and Montes, B. F.: Retrieving wind statistics from average spectrum of continuous-wave lidar, Atmos. Meas. Tech., 6, 1673–1683, https://doi.org/10.5194/amt-6-1673-2013, 2013. 
Download
Short summary
Improving the monitoring capability of atmospheric turbulence can help unravel the mystery of turbulence. Based on some assumptions, scientists have proposed various detection methods. However, these assumptions limit their applicability. We abandoned these assumptions and proposed a more accurate method, revealing some new results. Our method can provide more accurate three-dimensional features of turbulence, which will have a huge driving effect on the development of turbulence.
Share