Articles | Volume 17, issue 6
https://doi.org/10.5194/amt-17-1837-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-17-1837-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Directly measuring the power-law exponent and kinetic energy of atmospheric turbulence using coherent Doppler wind lidar
Jinhong Xian
School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
Shenzhen National Climate Observatory, Meteorological Bureau of Shenzhen Municipality, Shenzhen 518040, China
Chao Lu
Shenzhen National Climate Observatory, Meteorological Bureau of Shenzhen Municipality, Shenzhen 518040, China
Xiaoling Lin
Shenzhen National Climate Observatory, Meteorological Bureau of Shenzhen Municipality, Shenzhen 518040, China
Honglong Yang
CORRESPONDING AUTHOR
Shenzhen National Climate Observatory, Meteorological Bureau of Shenzhen Municipality, Shenzhen 518040, China
Ning Zhang
CORRESPONDING AUTHOR
School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
Key Laboratory of Urban Meteorology, China Meteorological Administration, Beijing 100089, China
Li Zhang
Shenzhen National Climate Observatory, Meteorological Bureau of Shenzhen Municipality, Shenzhen 518040, China
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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.
Byzova, N. L., Ivanov, V. N., and Garger, E. K.: Turbulence in Atmospheric Boundary Layer, Gidrometeoizdat, Leningrad, ISBN 9785286001514, 1989.
Chan, P. W. and Lee, Y. F.: Application of Short-Range Lidar in Wind Shear Alerting, J. Atmos. Ocean. Techn., 29, 207–220, https://doi.org/10.1175/JTECH-D-11-00086.1, 2012.
Chellali, F., Khellaf, A., and Belouchrani, A.: Application of time-frequency representation in the study of the cyclical behavior of wind speed in Algeria: wavelet transform, Stoch. Env. Res. Risk A., 24, 1233–1239, https://doi.org/10.1007/s00477-010-0388-x, 2010.
Choukulkar, A., Brewer, W. A., Sandberg, S. P., Weickmann, A., Bonin, T. A., Hardesty, R. M., Lundquist, J. K., Delgado, R., Iungo, G. V., Ashton, R., Debnath, M., Bianco, L., Wilczak, J. M., Oncley, S., and Wolfe, D.: Evaluation of single and multiple Doppler lidar techniques to measure complex flow during the XPIA field campaign, Atmos. Meas. Tech., 10, 247–264, https://doi.org/10.5194/amt-10-247-2017, 2017.
Frehlich, R. and Cornman, L.: Estimating spatial velocity statistics with coherent Doppler lidar, J. Atmos. Ocean. Techn., 19, 355–366, https://doi.org/10.1175/1520-0426-19.3.355, 2002.
Frehlich, R. and Kelley, N.: Measurements of Wind and Turbulence Profiles With Scanning Doppler Lidar for Wind Energy Applications, IEEE J. Sel. Top. Appl., 1, 42–47, https://doi.org/10.1109/JSTARS.2008.2001758, 2008.
Gottschall, J. and Peinke, J.: How to improve the estimation of power curves for wind turbines, Environ. Res. Lett., 3, 015005, https://doi.org/10.1088/1748-9326/3/1/015005, 2008.
Jin, X., Song, X. Q., Yang, Y. W., Wang, M. A., Shao, S. Y., and Zheng, H. T.: Estimation of turbulence parameters in the atmospheric boundary layer of the Bohai Sea, China, by coherent Doppler lidar and mesoscale model, Opt. Express, 30, 13263–13277, https://doi.org/10.1364/OE.455079, 2022.
Kolmogorov, A. N.: Energy dissipation in locally isotropic turbulence, Dokl. Akad. Nauk SSSR, 32, 19–21, 1941.
Kolmogorov, A. N.: Dissipation of energy in the locally isotropic turbulence, P. Roy. Soc. Lond. A Mat., 434A, 15–17, 1991.
Mann, J., Peña, A., Bingöl, F., Wagner, R., and Courtney, M. S.: Lidar Scanning of Momentum Flux in and above the Atmospheric Surface Layer, J. Atmos. Ocean. Techn., 27, 959–976, https://doi.org/10.1175/2010JTECHA1389.1, 2010.
Massman, W.: Handbook of Micrometeorology: A Guide for Surface Flux Measurement and Analysis, Kluwer Academic, Boston, ISBN 9781402022647, 2006.
O'Connor, E. J., Illingworth, A. J., Brooks, I. M., Westbrook, C. D., Hogan, R. J., Davies, F., and Brooks, B. J.: A Method for Estimating the Turbulent Kinetic Energy Dissipation Rate from a Vertically Pointing Doppler Lidar, and Independent Evaluation from Balloon-Borne In Situ Measurements, J. Atmos. Ocean. Techn., 27, 1652–1664, https://doi.org/10.1175/2010JTECHA1455.1, 2010.
Panofsky, H. A., Larko, D., Lipschutz, R., Stone, G., Bradley, E. F., Bowen, A. J., and Hojstrup, J.: Spectra of velocity components over complex terrain, Q. J. Roy. Meteor. Soc., 108, 215–230, https://doi.org/10.1256/smsqj.45512, 1982.
Qiu, Z. X., Xian, J. H., Yang, Y. X., Lu, C., Yang, H. L., Hu, Y. Y., Sun, J. Q., and Zhang, C. S.: Characteristics of Coastal Low-Level Jets in the Boundary Layer of the Pearl River Estuary, Journal of Marine Science and Engineering, 11, 1128, https://doi.org/10.3390/jmse11061128, 2023.
Sathe, A. and Mann, J.: A review of turbulence measurements using ground-based wind lidars, Atmos. Meas. Tech., 6, 3147–3167, https://doi.org/10.5194/amt-6-3147-2013, 2013.
Smalikho, I., Köpp, F., and Rahm, S.: Measurement of atmospheric turbulence by 2-μm Doppler lidar, J. Atmos. Ocean. Techn., 22, 1733–1747, https://doi.org/10.1175/JTECH1815.1, 2005.
Smalikho, I. N. and Banakh, V. A.: Measurements of wind turbulence parameters by a conically scanning coherent Doppler lidar in the atmospheric boundary layer, Atmos. Meas. Tech., 10, 4191–4208, https://doi.org/10.5194/amt-10-4191-2017, 2017.
Stull, R. B.: An Introduction to Boundary Layer Meteorology, Springer Netherlands, ISBN 9789027727695, 1988.
Wang, X. Y., Dai, G. Y., Wu, S. H., Zhu, P. Z., Li, Z. W., Song, X. Q., Zhang, S. P., Xu, J., Yin, J. P., Qin, S. G., and Wang, X. T.: Classification of Turbulent Mixing Driven Sources in Marine Atmospheric Boundary Layer With Use of Shipborne Coherent Doppler Lidar Observations, J. Geophys. Res.-Atmos., 128, e2023JD038918, https://doi.org/10.1029/2023JD038918, 2023.
Zeng, Q. C., Cheng, X. L., Hu, F., and Peng, Z.: Gustiness and coherent structure of strong winds and their role in dust emission and entrainment, Adv. Atmos. Sci., 27, 1–13, https://doi.org/10.1007/s00376-009-8207-3, 2010.
Zhai, X. C., Wu, S. H., and Liu, B. Y.: Doppler lidar investigation of wind turbine wake characteristics and atmospheric turbulence under different surface roughness, Opt. Express, 25, A515–A529, https://doi.org/10.1364/OE.25.00A515, 2017.
Zhou, Q. J., Li, L., Chan, P. W., Cheng, X. L., Lan, C. X., Su, J. C., He, Y. Q., and Yang, H. L.: Observational Study of Wind Velocity and Structures during Supertyphoons and Convective Gales over Land Based on a 356-m-High Meteorological Gradient Tower, J. Appl. Meteorol. Clim., 62, 103–118, https://doi.org/10.1175/JAMC-D-22-0013.1, 2023.
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.
Improving the monitoring capability of atmospheric turbulence can help unravel the mystery of...