scholarly journals Simulation of frequency discrimination for spaceborne Doppler wind lidar (Ⅱ)：Study on the retrieval of atmospheric wind speed for Rayleigh channel based on Fabry-Perot interferometer

2014 ◽  
Vol 63 (14) ◽  
pp. 140703
Author(s):  
Zhang Ri-Wei ◽  
Sun Xue-Jin ◽  
Yan Wei ◽  
Zhao Jian ◽  
Liu Lei ◽  
...  
Keyword(s):  
Wind Speed ◽  
Frequency Discrimination ◽  
Rayleigh Channel ◽  
Fabry Perot ◽  
Wind Lidar ◽  
Doppler Wind Lidar

Simulation of Frequency Discrimination and Retrieval of Wind Speed for the Bistatic Doppler Wind Lidar

Optik ◽  
2019 ◽  
Vol 179 ◽  
pp. 796-803
Author(s):  
Shaohui Li ◽  
Xuejin Sun ◽  
Riwei Zhang ◽  
Chuanliang Zhang
Keyword(s):  
Wind Speed ◽  
Frequency Discrimination ◽  
Wind Lidar ◽  
Doppler Wind Lidar

Analysis of Doppler Wind Lidar Detecting Data Based on Fabry-Perot Etalon

2011 ◽  
Vol 38 (3) ◽  
pp. 0314002 ◽  
Author(s):  
王国成 Wang Guocheng ◽  
孙东松 Sun Dongsong ◽  
杜洪亮 Du Hongliang ◽  
舒志峰 Shu Zhifeng ◽  
唐磊 Tang Lei ◽  
...  
Keyword(s):  
Fabry Perot ◽  
Wind Lidar ◽  
Doppler Wind Lidar

scholarly journals Relationship between wind observation accuracy and the ascending node of the sun-synchronous orbit for the Aeolus-type spaceborne Doppler wind lidar

2021 ◽  
Vol 14 (7) ◽  
pp. 4787-4803
Author(s):  
Chuanliang Zhang ◽  
Xuejin Sun ◽  
Wen Lu ◽  
Yingni Shi ◽  
Naiying Dou ◽  
...  
Keyword(s):  
Laser Pulse ◽  
Pulse Energy ◽  
Laser Pulse Energy ◽  
Background Radiation ◽  
The Sun ◽  
Wind Observation ◽  
Rayleigh Channel ◽  
Wind Lidar ◽  
The Impact ◽  
Doppler Wind Lidar

Abstract. The launch and operation of the first spaceborne Doppler wind lidar (DWL), Aeolus, is of great significance for observing the global wind field. Aeolus operates on a sun-synchronous dawn–dusk orbit to minimize the negative impact of solar background radiation (SBR) on wind observation accuracy. Future spaceborne DWLs may not operate on sun-synchronous dawn–dusk orbits due to their observational purposes. The impact of the local time of ascending node (LTAN) crossing of sun-synchronous orbits on the wind observation accuracy was studied in this paper by proposing two given Aeolus-type spaceborne DWLs operating on the sun-synchronous orbits with LTANs of 15:00 and 12:00 LT. On these two new orbits, the increments of the averaged SBR received by the new spaceborne DWLs range from 39 to 56 mW m−2 sr−1 nm−1 under cloud-free skies near the summer and winter solstices, which will lead to uncertainties of 0.19 and 0.27 m s−1 in the increment of the averaged Rayleigh channel wind observations for 15:00 and 12:00 LT orbits using the instrument parameters of Aeolus with 30 measurements per observation and 20 laser pulses per measurement. This demonstrates that Aeolus operating on the sun-synchronous dawn–dusk orbit is the optimal observation scenario, and the random error caused by the SBR will be larger on other sun-synchronous orbits. Increasing the laser pulse energy of the new spaceborne DWLs is used to lower the wind observation uncertainties, and a method to quantitatively design the laser pulse energy according to the specific accuracy requirements is proposed in this study based on the relationship between the signal-to-noise ratio and the uncertainty of the response function of the Rayleigh channel. The laser pulse energies of the two new spaceborne DWLs should be set to 70 mJ based on the statistical results obtained using the method. The other instrument parameters should be the same as those of Aeolus. Based on the proposed parameters, the accuracies of about 77.19 % and 74.71 % of the bins of the two new spaceborne DWLs would meet the accuracy requirements of the European Space Agency (ESA) for Aeolus. These values are very close to the 76.46 % accuracy of an Aeolus-type spaceborne DWL when it is free of the impact of the SBR. Moreover, the averaged uncertainties of the two new spaceborne DWLs are 2.62 and 2.69 m s−1, which perform better than that of Aeolus (2.77 m s−1).

scholarly journals Improved methane emission estimates using AVIRIS-NG and an Airborne Doppler Wind Lidar

2021 ◽  
Author(s):  
Andrew Thorpe ◽  
Christopher O’Handley ◽  
George Emmitt ◽  
Philip Decola ◽  
Francesca Hopkins ◽  
...  
Keyword(s):  
Wind Speed ◽  
Emission Rate ◽  
Sonic Anemometer ◽  
Surface Measurement ◽  
Emission Rates ◽  
Ch4 Emission ◽  
Near Surface ◽  
Wind Measurements ◽  
Wind Lidar ◽  
Doppler Wind Lidar

<p>This study demonstrates the utility of combining Airborne Doppler Wind Lidar measurements and quantitative methane (CH4) retrievals from the Next Generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-NG) to estimate CH4 emission rates. In a controlled release experiment, Twin Otter Doppler Wind Lidar (TODWL) observed wind speed and direction agreed closely with sonic anemometer measurements and CH4 emission rates derived from TODWL observations were more accurate than those using the sonic during periods of stable winds. During periods exhibiting rapid shifts in wind speed and direction, estimating emission rates proved more challenging irrespective of the use of model, sonic, or TODWL wind data. Overall, TODWL was able to provide accurate wind measurements and emission rate estimates despite the variable wind conditions and excessive flight level turbulence which impacted near surface measurement density. TODWL observed winds were also used to constrain CH4 emissions at a refinery, landfill, wastewater facility, and dairy digester. At these sites, TODWL wind measurements agreed well with wind observations from nearby meteorological stations, and when combined with quantitative CH4 plume imagery, yielded emission rate estimates that were similar to those obtained using model winds.</p>

Horizontal Wind Speed motion-induced error assessment on a floating Doppler Wind lidar

2021 ◽  
Author(s):  
Andreu Salcedo-Bosch ◽  
Joan Farré-Guarné ◽  
Josep Sala-Álvarez ◽  
Javier Villares-Piera ◽  
Robin Tanamachi ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Profile ◽  
Continuous Wave ◽  
Superposition Principle ◽  
Translational Motion ◽  
Horizontal Wind ◽  
Error Assessment ◽  
Horizontal Wind Speed ◽  
Wind Lidar ◽  
Doppler Wind Lidar

<p>A wind retrieval simulator of a floating Doppler Wind Lidar (DWL) with six Degrees of Freedom (DoF) in its motion is presented. The simulator considers a continuous-wave, conically scanning, floating DWL which retrieves the local wind profile from 50 line of sight (LoS) radial velocity measurements per scan. Rotational and translational motion effects over horizontal wind speed (HWS) measurements are studied parametrically. The 6 DoF motion framework as well as the most important buoy motion equations are based on the model presented in [1].</p><p>Each rotational and translational motion is simulated as 1 second sinusoidal signal defined by an amplitude, frequency and motion phase. In order to study the problem of motion-induced error on the retrieved HWS, a dimension reduction is needed (22 variables). A consideration followed in the literature [2] to alleviate the problem is to set the same motional frequency (f=0.3 Hz) for all DoF, a wind vector with constant HWS and null vertical wind speed (VWS). Moreover, the parametric study is carried out under certain constraints in order to finally reduce the problem dimensionality to three, which enables the generation of tri-dimensional colorplots of the error on the retrieved HWS.</p><p>Simulation results show that in the presence of motion, HWS error has a strong dependency on FDWL initial scan phase. Moreover, the directions of the rotation axis and translational velocity vector (with respect to wind direction, WD) show great impact on HWS error. For translational motion, a 3 DoF superposition principle is corroborated.</p><p>The simulator is as a useful tool for understanding particular lidar motion scenarios and their contributions to HWS measurements error. However, further analysis of the effect of lidar initial scan phase is needed. Additionally, these simulations are conducted under idealized assumptions of horizontally homogeneous wind profiles in the vicinity of the FDWL. Simulations using non-homogeneous wind fields (e.g., turbulence, air mass boundaries) would give insights on how well floating lidars can be expected to retrieve the wind profile in these common scenarios.</p><p><strong>Acknowledgements</strong></p><p>This work was supported via Spanish Government–European Regional Development Funds project PGC2018-094132-B-I00 and H2020 ACTRIS-IMP (GA-871115). The European Institute of Innovation and Technology (EIT), KIC InnoEnergy project NEPTUNE (Offshore Metocean Data Mea-suring Equipment and Wind, Wave and Current Analysis and ForecastingSoftware, call FP7) supported measurements campaigns. CommSensLab isa María-de-Maeztu Unit of Excellence funded by the Agencia Estatal de Investigación (Spanish National Science Foundation). The work of Andreu Salcedo-Bosch was supported by the “Agència de Gestió d’Ajuts Universitaris i de la Recerca (AGAUR)”, Generalitat de Catalunya, under Grant no. 2020 FISDU 00455.</p><p><strong>References</strong></p><p>[1] F. Kelberlau, V. Neshaug, L. Lønseth, T. Bracchi, and J. Mann, “Taking the Motion out of Floating Lidar: Turbulence Intensity Estimates with a Continuous-Wave Wind Lidar,” Remote Sens., vol. 12, no. 898, 2020.</p><p>[2] J. Tiana-Alsina, F. Rocadenbosch, and M. A. Gutierrez-Antunano, “Vertical Azimuth Display simulator for wind-Doppler lidar error assessment,” in 2017 IEEE Int. Geosci. Remote. Se. (IGARSS). IEEE, Jul. 2017.</p>

Design and analysis of 532 nm Doppler wind lidar with Fabry-Perot etalon

2011 ◽  
Vol 23 (4) ◽  
pp. 949-953
Author(s):  
王国成 Wang Guocheng ◽  
孙东松 Sun Dongsong ◽  
杜洪亮 Du Hongliang ◽  
康健群 Kang Jianqun ◽  
唐磊 Tang Lei ◽  
...  
Keyword(s):  
Fabry Perot ◽  
Wind Lidar ◽  
532 Nm ◽  
Doppler Wind Lidar

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 Retrieval improvements for the ALADIN Airborne Demonstrator in support of the Aeolus wind product validation

2021 ◽  
Author(s):  
Oliver Lux ◽  
Christian Lemmerz ◽  
Fabian Weiler ◽  
Uwe Marksteiner ◽  
Benjamin Witschas ◽  
...  
Keyword(s):  
Direct Detection ◽  
Near Field ◽  
Measurement Range ◽  
Wind Data ◽  
Retrieval Algorithm ◽  
Random Errors ◽  
Wind Retrieval ◽  
Rayleigh Channel ◽  
Wind Lidar ◽  
Doppler Wind Lidar

Abstract. The realization of the European Space Agency’s Aeolus mission was supported by the long-standing development and field deployment of the ALADIN Airborne Demonstrator (A2D) which, since the launch of the Aeolus satellite in 2018, has been serving as a key instrument for the validation of the Atmospheric LAser Doppler INstrument (ALADIN), the first-ever Doppler wind lidar (DWL) in space. However, the validation capabilities of the A2D are compromised by deficiencies of the dual-channel receiver which, like its spaceborne counterpart, consists of a Rayleigh and a complementary Mie spectrometer for sensing the wind speed from both molecular and particulate backscatter signals, respectively. Whereas the accuracy and precision of the Rayleigh channel is limited by the spectrometer’s high alignment sensitivity, especially in the near field of the instrument, large systematic Mie wind errors are caused by aberrations of the interferometer in combination with the temporal overlap of adjacent range gates during signal readout. The two error sources are mitigated by modifications of the A2D wind retrieval algorithm. A novel quality control scheme was implemented which ensures that only backscatter return signals within a small angular range are further processed. Moreover, Mie wind results with large bias of opposing sign in adjacent range bins are vertically averaged. The resulting improvement of the A2D performance was evaluated in the context of two Aeolus airborne validation campaigns that were conducted between May and September 2019. Comparison of the A2D wind data against a high-accuracy, coherent Doppler wind lidar that was deployed in parallel on-board the same aircraft shows that the retrieval refinements considerably decrease the random errors of the A2D line-of-sight (LOS) Rayleigh and Mie winds from about 2.0 m∙s−1 to about 1.5 m∙s−1, demonstrating the capability of such a direct detection DWL. Moreover, the measurement range of the Rayleigh channel could be largely extended by up to 2 km in the instrument’s near field close to the aircraft. The Rayleigh and Mie systematic errors are below 0.5 m∙s−1 (LOS), hence allowing for an accurate assessment of the Aeolus wind errors during the September campaign. The latter revealed different biases of the L2B Rayleigh-clear and Mie-cloudy horizontal LOS (HLOS) for ascending and descending orbits as well as random errors of about 3 m∙s−1 (HLOS) for the Mie and close to 6 m∙s−1 (HLOS) for the Rayleigh winds, respectively. In addition to the Aeolus error evaluation, the present study discusses the applicability of the developed A2D algorithm modifications to the Aeolus processor, thereby offering prospects for improving the Aeolus wind data quality.

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

2005 ◽  
Vol 12 (5) ◽  
pp. 409-414 ◽  
Author(s):  
Dongsong Sun ◽  
Zhiqing Zhong ◽  
Jun Zhou ◽  
Huanling Hu ◽  
Takao Kobayashi
Keyword(s):  
Accuracy Analysis ◽  
Fabry Perot ◽  
Wind Lidar ◽  
Doppler Wind Lidar
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