scholarly journals Performance and Technique of Coherent 2-μm Differential Absorption and Wind Lidar for Wind Measurement

2013 ◽  
Vol 30 (3) ◽  
pp. 429-449 ◽  
Author(s):  
Hironori Iwai ◽  
Shoken Ishii ◽  
Ryoko Oda ◽  
Kohei Mizutani ◽  
Shinya Sekizawa ◽  
...  
Keyword(s):  
Wind Velocity ◽  
Signal To Noise Ratio ◽  
Sonic Anemometer ◽  
Correlation Coefficients ◽  
Co2 Concentration ◽  
Horizontal Wind ◽  
Doppler Lidar ◽  
Differential Absorption ◽  
Velocity Measurements ◽  
Wind Lidar

Abstract A coherent 2-μm differential absorption and wind lidar (Co2DiaWiL) has been built with a high-power Q-switched Tm,Hm:YLF laser to measure CO2 concentration and radial wind speed. The performance of the Co2DiaWiL is described and analyzed, with a view to demonstrating system capabilities for remote measurements of wind velocities in the atmospheric boundary layer and free troposphere. Bias in the velocity measurements was estimated at −0.0069 m s−1 using measurements from a stationary hard target. The Co2DiaWiL achieved a velocity precision of 0.12 m s−1, derived from the magnitude of random error in radial wind velocity measurements. These measurements were made for ranges out to 20–25 km by using a horizontally fixed beam mode for average times of 1 min. Quantitative intercomparisons of 1-min averages between the Co2DiaWiL and a sonic anemometer revealed a correlation coefficient of 0.99. This study demonstrated measurements of horizontal wind profiles, by making radial wind velocity measurements with the Co2DiaWiL using conical scanning. Profile differences at higher levels could be attributed to probable large horizontal separations of the radiosondes and the low signal-to-noise ratio of the Co2DiaWiL. A pseudo-dual-Doppler technique was developed to retrieve horizontal wind components with a single-Doppler lidar and a steering mirror. Intercomparisons of the 1-min-averaged u and υ components from the pseudo-dual-Doppler lidar measurements with those from the sonic anemometer revealed correlation coefficients of 0.84 and 0.83, respectively.

scholarly journals 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

2010 ◽  
Vol 27 (10) ◽  
pp. 1652-1664 ◽  
Author(s):  
Ewan J. O’Connor ◽  
Anthony J. Illingworth ◽  
Ian M. Brooks ◽  
Christopher D. Westbrook ◽  
Robin J. Hogan ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Convective Boundary Layer ◽  
Sonic Anemometer ◽  
Horizontal Wind ◽  
Inertial Subrange ◽  
Doppler Velocity ◽  
Doppler Lidar ◽  
Convective Boundary ◽  
Dissipation Rates

Abstract A method of estimating dissipation rates from a vertically pointing Doppler lidar with high temporal and spatial resolution has been evaluated by comparison with independent measurements derived from a balloon-borne sonic anemometer. This method utilizes the variance of the mean Doppler velocity from a number of sequential samples and requires an estimate of the horizontal wind speed. The noise contribution to the variance can be estimated from the observed signal-to-noise ratio and removed where appropriate. The relative size of the noise variance to the observed variance provides a measure of the confidence in the retrieval. Comparison with in situ dissipation rates derived from the balloon-borne sonic anemometer reveal that this particular Doppler lidar is capable of retrieving dissipation rates over a range of at least three orders of magnitude. This method is most suitable for retrieval of dissipation rates within the convective well-mixed boundary layer where the scales of motion that the Doppler lidar probes remain well within the inertial subrange. Caution must be applied when estimating dissipation rates in more quiescent conditions. For the particular Doppler lidar described here, the selection of suitably short integration times will permit this method to be applicable in such situations but at the expense of accuracy in the Doppler velocity estimates. The two case studies presented here suggest that, with profiles every 4 s, reliable estimates of ε can be derived to within at least an order of magnitude throughout almost all of the lowest 2 km and, in the convective boundary layer, to within 50%. Increasing the integration time for individual profiles to 30 s can improve the accuracy substantially but potentially confines retrievals to within the convective boundary layer. Therefore, optimization of certain instrument parameters may be required for specific implementations.

scholarly journals Cross-contamination effect on turbulence spectra from Doppler beam swinging wind lidar

2020 ◽  
Vol 5 (2) ◽  
pp. 519-541 ◽  
Author(s):  
Felix Kelberlau ◽  
Jakob Mann
Keyword(s):  
Wind Velocity ◽  
Time Lag ◽  
Turbulence Models ◽  
Horizontal Wind ◽  
Cross Contamination ◽  
Turbulence Spectra ◽  
Contamination Effect ◽  
Turbulence Velocity ◽  
Wind Lidar ◽  
Velocity Spectra

Abstract. Turbulence velocity spectra are of high importance for the estimation of loads on wind turbines and other built structures, as well as for fitting measured turbulence values to turbulence models. Spectra generated from reconstructed wind vectors of Doppler beam swinging (DBS) wind lidars differ from spectra based on one-point measurements. Profiling wind lidars have several characteristics that cause these deviations, namely cross-contamination between the three velocity components, averaging along the lines of sight and the limited sampling frequency. This study focuses on analyzing the cross-contamination effect. We sample wind data in a computer-generated turbulence box to predict lidar-derived turbulence spectra for three wind directions and four measurement heights. The data are then processed with the conventional method and with the method of squeezing that reduces the longitudinal separation distances between the measurement locations of the different lidar beams by introducing a time lag into the data processing. The results are analyzed and compared to turbulence velocity spectra from field measurements with a Windcube V2 wind lidar and ultrasonic anemometers as reference. We successfully predict lidar-derived spectra for all test cases and found that their shape is dependent on the angle between the wind direction and the lidar beams. With conventional processing, cross-contamination affects all spectra of the horizontal wind velocity components. The method of squeezing improves the spectra to an acceptable level only for the case of the longitudinal wind velocity component and when the wind blows parallel to one of the lines of sight. The analysis of the simulated spectra described here improves our understanding of the limitations of turbulence measurements with DBS profiling wind lidar.

scholarly journals Doppler lidar at Observatoire de Haute Provence for wind profiling up to 75 km altitude: performance evaluation and observations

2019 ◽  
Author(s):  
Sergey M. Khaykin ◽  
Alain Hauchecorne ◽  
Robin Wing ◽  
Philippe Keckhut ◽  
Sophie Godin-Beekmann ◽  
...  
Keyword(s):  
Middle Atmosphere ◽  
Direct Detection ◽  
Horizontal Wind ◽  
Doppler Lidar ◽  
Qualitative Comparison ◽  
Horizontal Wind Speed ◽  
Early Validation ◽  
Wind Lidar ◽  
Wind Profiles ◽  
Hourly Observation

Abstract. A direct-detection Rayleigh-Mie Doppler lidar for measuring horizontal wind speed in the middle atmosphere has been deployed at Observatoire de Haute Provence (OHP) in southern France since 1993. After a recent upgrade, the instrument gained the capacity of wind profiling between 5 and 75 km altitude with high vertical and temporal resolution. The lidar comprises a monomode Nd:Yag laser emitting at 532 nm, three telescope assemblies, and a double-edge Fabry-Perot interferometer for detection of the Doppler shift in the backscattered light. In this article, we describe the instrument design, recap retrieval methodology and provide an updated error estimate for horizontal wind. The evaluation of the wind lidar performance is done using a series of twelve time-coordinated radiosoundings conducted at OHP. A point-by-point intercomparison shows a remarkably small average bias of 0.1 m/s between the lidar and the radiosonde wind profiles with a standard deviation of 2.2 m/s. We report examples of a weekly and an hourly observation series, reflecting various dynamical events in the middle atmosphere, such as a Sudden Stratospheric Warming event in January 2019 and an occurrence of a stationary gravity wave, generated by the flow over the Alps. A qualitative comparison between the wind profiles from the lidar and the ECMWF Integrated Forecast System is also discussed. Finally, we present an example of early validation of the ESA Aeolus space-borne wind lidar using its ground-based predecessor.

scholarly journals Improvement of CO2-DIAL Signal-to-Noise Ratio Using Lifting Wavelet Transform

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2362 ◽  
Author(s):  
Chengzhi Xiang ◽  
Ge Han ◽  
Yuxin Zheng ◽  
Xin Ma ◽  
Wei Gong
Keyword(s):  
Wavelet Transform ◽  
Carbon Cycle ◽  
Signal To Noise Ratio ◽  
Co2 Concentration ◽  
Atmospheric Co2 ◽  
Signal Denoising ◽  
Differential Absorption ◽  
Lifting Wavelet Transform ◽  
Signal To Noise ◽  
Lifting Wavelet

Atmospheric CO2 plays an important role in controlling climate change and its effect on the carbon cycle. However, detailed information on the dynamics of CO2 vertical mixing remains lacking, which hinders the accurate understanding of certain key features of the carbon cycle. Differential absorption lidar (DIAL) is a promising technology for CO2 detection due to its characteristics of high precision, high time resolution, and high spatial resolution. Ground-based CO2-DIAL can provide the continuous observations of the vertical profile of CO2 concentration, which can be highly significant to gaining deeper insights into the rectification effect of CO2, the ratio of respiration photosynthesis, and the CO2 dome in urban areas. A set of ground-based CO2-DIAL systems were developed by our team and highly accurate long-term laboratory experiments were conducted. Nonetheless, the performance suffered from low signal-to-noise ratio (SNR) in field explorations because of decreasing aerosol concentrations with increasing altitude and surrounding interference according to the results of our experiments in Wuhan and Huainan. The concentration of atmospheric CO2 is derived from the difference of signals between on-line and off-line wavelengths; thus, low SNR will cause the superimposition of the final inversion error. In such a situation, an efficient and accurate denoising algorithm is critical for a ground-based CO2-DIAL system, particularly in field experiments. In this study, a method based on lifting wavelet transform (LWT) for CO2-DIAL signal denoising was proposed. This method, which is an improvement of the traditional wavelet transform, can select different predictive and update functions according to the characteristics of lidar signals, thereby making it suitable for the signal denoising of CO2-DIAL. Experiment analyses were conducted to evaluate the denoising effect of LWT. For comparison, ensemble empirical mode decomposition denoising was also performed on the same lidar signal. In addition, this study calculated the coefficient of variation (CV) at the same altitude among multiple original signals within 10 min and then performed the same calculation on the denoised signal. Finally, high-quality signal of ground-based CO2-DIAL was obtained using the LWT denoising method. The differential absorption optical depths of the denoised signals obtained via LWT were calculated, and the profile distribution information of CO2 concentration was acquired during field detection by using our developed CO2-DIAL systems.

scholarly journals Wind Measurements from Arc Scans with Doppler Wind Lidar

2015 ◽  
Vol 32 (11) ◽  
pp. 2024-2040 ◽  
Author(s):  
H. Wang ◽  
R. J. Barthelmie ◽  
A. Clifton ◽  
S. C. Pryor
Keyword(s):  
Wind Speed ◽  
Sonic Anemometer ◽  
Elevation Angle ◽  
Horizontal Wind ◽  
Horizontal Wind Speed ◽  
Energy Applications ◽  
Mean Wind Speed ◽  
Wind Measurements ◽  
Wind Lidar ◽  
Doppler Wind Lidar

AbstractDefining optimal scanning geometries for scanning lidars for wind energy applications remains an active field of research. This paper evaluates uncertainties associated with arc scan geometries and presents recommendations regarding optimal configurations in the atmospheric boundary layer. The analysis is based on arc scan data from a Doppler wind lidar with one elevation angle and seven azimuth angles spanning 30° and focuses on an estimation of 10-min mean wind speed and direction. When flow is horizontally uniform, this approach can provide accurate wind measurements required for wind resource assessments in part because of its high resampling rate. Retrieved wind velocities at a single range gate exhibit good correlation to data from a sonic anemometer on a nearby meteorological tower, and vertical profiles of horizontal wind speed, though derived from range gates located on a conical surface, match those measured by mast-mounted cup anemometers. Uncertainties in the retrieved wind velocity are related to high turbulent wind fluctuation and an inhomogeneous horizontal wind field. The radial velocity variance is found to be a robust measure of the uncertainty of the retrieved wind speed because of its relationship to turbulence properties. It is further shown that the standard error of wind speed estimates can be minimized by increasing the azimuthal range beyond 30° and using five to seven azimuth angles.

scholarly journals Validating precision estimates in horizontal wind measurements from a Doppler lidar

2017 ◽  
Vol 10 (3) ◽  
pp. 1229-1240 ◽  
Author(s):  
Rob K. Newsom ◽  
W. Alan Brewer ◽  
James M. Wilczak ◽  
Daniel E. Wolfe ◽  
Steven P. Oncley ◽  
...  
Keyword(s):  
Wind Speed ◽  
Radial Velocity ◽  
Sonic Anemometer ◽  
Direct Calculation ◽  
Measurement Precision ◽  
Horizontal Wind ◽  
Retrieval Algorithm ◽  
Doppler Lidar ◽  
Wind Fields ◽  
Wind Retrieval

Abstract. Results from a recent field campaign are used to assess the accuracy of wind speed and direction precision estimates produced by a Doppler lidar wind retrieval algorithm. The algorithm, which is based on the traditional velocity-azimuth-display (VAD) technique, estimates the wind speed and direction measurement precision using standard error propagation techniques, assuming the input data (i.e., radial velocities) to be contaminated by random, zero-mean, errors. For this study, the lidar was configured to execute an 8-beam plan-position-indicator (PPI) scan once every 12 min during the 6-week deployment period. Several wind retrieval trials were conducted using different schemes for estimating the precision in the radial velocity measurements. The resulting wind speed and direction precision estimates were compared to differences in wind speed and direction between the VAD algorithm and sonic anemometer measurements taken on a nearby 300 m tower.All trials produced qualitatively similar wind fields with negligible bias but substantially different wind speed and direction precision fields. The most accurate wind speed and direction precisions were obtained when the radial velocity precision was determined by direct calculation of radial velocity standard deviation along each pointing direction and range gate of the PPI scan. By contrast, when the instrumental measurement precision is assumed to be the only contribution to the radial velocity precision, the retrievals resulted in wind speed and direction precisions that were biased far too low and were poor indicators of data quality.

scholarly journals Lidar observations of atmospheric internal waves in the boundary layer of the atmosphere on the coast of Lake Baikal

2016 ◽  
Vol 9 (10) ◽  
pp. 5239-5248 ◽  
Author(s):  
Viktor A. Banakh ◽  
Igor N. Smalikho
Keyword(s):  
Boundary Layer ◽  
Wind Velocity ◽  
Internal Waves ◽  
Lake Baikal ◽  
Ground Level ◽  
Horizontal Wind ◽  
Stream Line ◽  
Western Coast ◽  
Jet Streams ◽  
Wind Lidar

Abstract. Atmospheric internal waves (AIWs) in the boundary layer of atmosphere have been studied experimentally with the use of Halo Photonics pulsed coherent Doppler wind lidar Stream Line. The measurements were carried out over 14–28 August 2015 on the western coast of Lake Baikal (51°50′47.17′′ N, 104°53′31.21′′ E), Russia. The lidar was placed at a distance of 340 m from Lake Baikal at a height of 180 m above the lake level.A total of six AIW occurrences have been revealed. This always happened in the presence of one or two (in five out of six cases) narrow jet streams at heights of approximately 200 and 700 m above ground level at the lidar location. The period of oscillations of the wave addend of the wind velocity components in four AIW events was 9 min, and in the other two it was approximately 18 and 6.5 min. The amplitude of oscillations of the horizontal wind velocity component was about 1 m s−1, while the amplitude of oscillations of the vertical velocity was 3 times smaller. In most cases, internal waves were observed for 45 min (5 wave oscillations with a period of 9 min). Only once the AIW lifetime was about 4 h.

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