Vol. 38, issue 07, article # 5

Sherstobitov A. M., Banakh V. A., Smalikho I. N., Falits A. V. Testing of electro-optical unit of fiber-optic pulsed coherent Doppler lidar LRV-2. // Optika Atmosfery i Okeana. 2025. V. 38. No. 07. P. 541–550. DOI: 10.15372/AOO20250705 [in Russian].
Copy the reference to clipboard
Abstract:

Turbulent processes in the atmospheric boundary layer have not been fully studied yet. The most effective tool for studying these processes is a pulsed coherent Doppler lidar (PCDL). In the work, the second version of the electro-optical unit of a PCDL LVR-2 created at the Laboratory of Wave Propagation of V.E. Zuev Institute of Atmospheric Optics, Siberian Branch, Russian Academy of Sciences, is tested. The correctness of wind radial velocity (RV) estimates by LVR-2 during its operation in the “short” pulse mode is verified in an experiment with a Stream Line lidar. The errors in RV estimates by LRV-2 are analyzed. A possibility of using RV estimates by LRV-2 made in the vertical sounding mode to estimate the kinetic energy dissipation rate of wind turbulence by the vertical velocity spectral density method is shown. The results can be used to create techniques for testing PCDLs and determining the efficiency of such lidars in estimating atmospheric turbulence parameters.

Keywords:

pulsed coherent Doppler lidar, radial velocity, spectra of turbulent fluctuations of vertical wind velocity

Figures:
References:

1. Ando T., Kameyama S., Asaka K., Hirano Y., Tanaka H., Inokuchi H. All fiber coherent Doppler LIDAR for wind sensing // MRS Online Proc. Lib. 2008. V. 1076. P. 1076-K04–05. DOI: 10.1557/PROC-1076-K04-05.
2. Pierson G., Davies F., Collier C. An analysis of performance of the UFAM pulsed Doppler lidar for the observing the boundary layer // J. Atmos. Ocean. Technol. 2009. V. 26, N 2. P. 240–250. DOI: 10.1175/ 2008JTECHA1128.1.
3. Patent KNR 10204314(B), MPK G01N15/00, G01S17/95. All-optical-fiber coherent Doppler wind lidar signal processing system / Zhou Jun, Lu Dong, Zhu Hailong, Wang Guofeng, Hao Liyun; zayavitel' NANJING ZHONGKE SHENGUANG SCIENCE & TECHNOLOGY CO LTD. 2.01.2013
4. Lidar WindCube 400S. URL: https://www.vaisala.com/en/products/weather-environmental-sensors/wind-cube-general (data obrashcheniya: 03.02.2025)
5. Lidar WindPrintTM S4000. URL: http://www.seaglet.com/en/product.aspx?t1=100 (data obrashcheniya: 03.02.2025).
6. Smalikho I.N., Banakh V.A., Sherstobitov A.M. Opredelenie otnosheniya signal/shum iz isxodnyx dannyx, izmeryaemyx impul'snym kogerentnym doplerovskim lidarom v usloviyax nestatsionarnogo shuma // Optika atmosf. i okeana. 2024. V. 37, N 3. P. 234–243. DOI: 10.15372/AOO20240307; Smalikho I.N., Banakh V.A., Sherstobitov A.M. Estimation of Signal-to-Noise Ratio from Pulsed Coherent Doppler Lidar Measurements under Nonstationary Noise // Atmos. Ocean. Opt. 2024. V. 37, N 3. P. 373–381.
7. Banta R.M., Pichugina Y.L., Brewer W.A. Turbulent velocity-variance profiles in the stable boundary layer generated by a nocturnal low-level jet // J. Atmos. Sci. 2006. V. 63. P. 2700–2719. DOI: 10.1175/JAS3776.1.
8. O’Connor E.J., Illingworth A.J., Brooks I.M., West-brook C.D., Hogan R.J., Davies F., Brooks B.J. A method for estimating the kinetic energy dissipation rate from a vertically pointing Doppler lidar, and independent evaluation from balloon-borne in situ measurements // J. Atmos. Ocean. Technol. 2010. V. 27, N 10. P. 1652–1664. DOI: 10.1175/2010JTECHA1455.1.
9. Sathe A., Mann J. A review of turbulence measurements using ground-based wind lidars // Atmos. Meas. Tech. 2013. V. 6, N 11. P. 3147–3167. DOI: 10.5194/amt-6-3147-2013.
10. Sathe A., Mann J., Vasiljevic N., Lea G. A six-beam method to measure turbulence statistics using ground-based wind lidars // Atmos. Meas. Tech. 2015. V. 8. P. 729–740. DOI: 10.5194/amt-8-729-2015.
11. Newman J.F., Klein P.M., Wharton S., Sathe A., Bonin T.A., Chilson P.B., Muschinski A. Evaluation of three lidar scanning strategies for turbulence measurements // Atmos. Meas. Tech. 2016. V. 9. P. 1993–2013. DOI: 10.5194/amt-9-1993-2016.
12. Bonin T.A., Choukulkar A., Brewer W.A., Sandberg S.P., Weickmann A.M., Pichugina Y., Banta R.M., Oncley S.P., Wolfe D.E. Evaluation of turbulence measurement techniques from a single Doppler lidar // Atmos. Meas. Tech. 2017. V. 10. P. 3021–3039. DOI: 10.5194/amt-2017-35.
13. Bodini N., Lundquist J.K., Newsom R.K. Estimation of turbulence dissipation rate and its variability from sonic anemometer and wind Doppler lidar during the XPIA field campaign // Atmos. Meas. Tech. 2018. V. 11. P. 4291–4308. DOI: 10.5194/amt-11-4291-2018.
14. Banakh V.A., Smalikho I.N., Falits A.V., Sherstobitov A.M. Estimating the parameters of wind turbulence from spectra of radial velocity measured by a pulsed Doppler lidar // Remote Sens. 2021. V. 13, N 11. DOI: 10.3390/rs13112071.
15. Liu Z., Barlow J.F., Chan P.-W., Chi Hung Fung J., Li Y., Ren C., Wai Leung Mak H., Ng Edward. A review of progress and applications of pulsed Doppler wind LiDARs // Remote Sens. 2019. V. 11, N 21. P. 2522. DOI: 10.3390/rs11212522.
16. Generator algoritmov BPF na yazyke Verilog HDL. URL: http://www.spiral.net/hardware/dftgen.html (data obrashcheniya: 15.12.2018)
17. Banah V.A., Smaliho I.N. Kogerentnye doplerovskie vetrovye lidary v turbulentnoi atmosfere. Tomsk: Izd-vo IOA SO RAN, 2013. 304 p.