Accuracy Analysis of the Fabry–Perot Etalon Based Doppler Wind Lidar

Sun, Dongsong; Zhong, Zhiqing; Zhou, Jun; Hu, Huanling; Kobayashi, T.

doi:10.1007/s10043-005-0409-z

Cited by 17 publications

(6 citation statements)

References 6 publications

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“…In the analysis of the data, the frequency resolution corresponds to the length of the FFT frame. The lidar measures the Doppler shifted frequency signal from the air/dust to determine its line-of-sight velocity, V, and is measured as 38 where f d is the Doppler shift frequency, and λ 0 is the light source center wavelength.…”

Section: Low Coherence Doppler Lidarmentioning

confidence: 99%

Dust flow analysis by low coherence Doppler lidar

Okubo

Lagrosas

Shiina

2023

Sci Rep

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Visualization of dust flow and wind dynamics near the ground surface are essential for understanding the mixing and interaction between geosphere and atmosphere near the surface. Knowing the temporal dust flow is beneficial in dealing with air pollution and health issues. Dust flows near the ground surface are difficult to monitor because of their small temporal and spatial scale. In this study, we propose a low-coherence Doppler lidar (LCDL) for measuring dust flow near the ground with high temporal and spatial resolutions of 5 ms and 1 m, respectively. We demonstrate the performance of LCDL in laboratory experiments using flour and calcium carbonate particles released into the wind tunnel. LCDL experiment results show a good agreement with anemometer measurement in wind speeds ranging from 0 to 5 m/s. The LCDL technique can reveal dust’s speed distribution, which is affected by mass and particle size. As a result, different speed distribution profiles can be used to determine dust type. The simulation results of dust flow coincide well with the experimental results.

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Section: Low Coherence Doppler Lidarmentioning

confidence: 99%

Dust flow analysis by low coherence Doppler lidar

Okubo

Lagrosas

Shiina

2023

Sci Rep

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“…Software is developed to achieve real-time signal processing and unattended operation. Some improvements had been made to the original DWL system [32]. A careful determination of the null Doppler-shift reference is necessary to get absolute winds measurements.…”

Section: System Descriptionmentioning

confidence: 99%

Fabry-Perot interferometer based Mie Doppler lidar for low tropospheric wind observation

et al. 2007

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Similar in principle to recent implementations of a lidar system at 355 nm [Opt. Lett. 25, 1231 (2000), Appl. Opt. 44, 6023 (2005)], an incoherent-detection Mie Doppler wind lidar at 1064 nm was developed and deployed in 2005 [Opt. Rev. 12, 409 (2005)] for wind measurements in the low troposphere, taking advantage of aerosol scattering for signal enhancement. We present a number of improvements made to the original 1064 nm system to increase its robustness for long-period operation. These include a multimode fiber for receiving the reference signal, a mode scrambler to allow uniform illumination over the Fabry-Perot interferometer, and a fast scannable Fabry-Perot interferometer for calibration and for the determination of outgoing laser frequency during the wind observation. With these improvements in stability, the standard deviation of peak transmission and FWHM of the Fabry-Perot interferometer was determined to be 0.49% and 0.36%, respectively. The lidar wind measurements were validated within a dynamic range of +/-40 m/s. Comparison experiments with both wind profiler radar and Vaisala wiresonde show good agreement with expected observation error. An example of 24 h continuous observations of wind field and aerosol backscatter coefficients in the boundary layer with 1 min and 30 m temporal and spatial resolution and 3 m/s tolerated wind velocity error is presented and fully demonstrates the stability and robustness of this lidar.

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“…2) For molecular signals, the slopes of two etalon filters are located in the both wings of the Rayleigh spectrum. 3,4) Because of the symmetric arrangement for both of these cases, the Doppler shift will cause an increase (a decrease) in backscattered signal intensity in one (or the other) of the edge filters. Thus, the ratio of the intensities of two edge-channel signals is sensitive to wind speed and direction, yielding better accuracy compared with the (single) edge technique.…”

Section: Introductionmentioning

confidence: 99%

System Evaluation of an Incoherent Wind Doppler LIDAR Using an Iodine Filter

Shibata

Nagasawa

Abo

et al. 2009

jjap

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This study is carried out system error evaluation of an incoherent wind Doppler LIDAR system that uses an iodine filter. Sharp slopes of an iodine filter provide better wind-measuring sensitivity than a Fabry-Perot etalon. The magnitude and sign of the Doppler shift are obtained from the ratio of the intensities of two signals arising from two slopes of an iodine absorption line. Systematic errors of wind measurement are caused mainly by the fluctuations of laser frequency and iodine absorption linewidth. The standard deviation of the zero Doppler shift is experimentally evaluated to be 1.8 MHz, which corresponds to the uncertainty in line-of-sight wind velocity of 0.5 m/s. This result shows a good agreement with the result of an experiment of the tuning stability of laser frequency with respect to the absorption line slope. Moreover, comparison of wind profiles is made between the Doppler LIDAR and concurrent radiosonde measurements. The measured horizontal wind speeds are from 8 to 21 m/s in the altitude range from 8 to 25 km, indicating a reasonable agreement between the two instruments. Experimentally, the total optical efficiency of this Doppler LIDAR system is estimated to be 4.0%, which is close to the value expected from the evaluation of each component of the instrument.

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Accuracy Analysis of the Fabry–Perot Etalon Based Doppler Wind Lidar

Cited by 17 publications

References 6 publications

Dust flow analysis by low coherence Doppler lidar

Dust flow analysis by low coherence Doppler lidar

Fabry-Perot interferometer based Mie Doppler lidar for low tropospheric wind observation

System Evaluation of an Incoherent Wind Doppler LIDAR Using an Iodine Filter

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