Wind speed reconstruction from mono-static wind lidar eliminating the effect of turbulence

2021 ◽  
Vol 13 (6) ◽  
pp. 063301
Author(s):  
Peter Rosenbusch ◽  
Paul Mazoyer ◽  
Laurie Pontreau ◽  
Pierre Etienne Allain ◽  
Jean-Pierre Cariou
Keyword(s):  
Wind Speed ◽  
Wind Lidar

scholarly journals Weibull Wind-Speed Distribution Parameters Derived from a Combination of Wind-Lidar and Tall-Mast Measurements Over Land, Coastal and Marine Sites

2015 ◽  
Vol 159 (2) ◽  
pp. 329-348 ◽  
Author(s):  
Sven-Erik Gryning ◽  
Rogier Floors ◽  
Alfredo Peña ◽  
Ekaterina Batchvarova ◽  
Burghard Brümmer
Keyword(s):  
Wind Speed ◽  
Speed Distribution ◽  
Wind Speed Distribution ◽  
Distribution Parameters ◽  
Wind Lidar

scholarly journals Doppler wind lidar activities at Cabauw

2021 ◽  
Author(s):  
Steven Knoop ◽  
Fred Bosveld ◽  
Marijn de Haij ◽  
Arnoud Apituley
Keyword(s):  
Wind Speed ◽  
Wind Profile ◽  
Continuous Wave ◽  
Wind Farms ◽  
Data Availability ◽  
Horizontal Wind ◽  
Horizontal Wind Speed ◽  
Low Clouds ◽  
Wind Measurements ◽  
Wind Lidar

<p>Atmospheric motion and turbulence are essential parameters for weather and topics related to air quality. Therefore, wind profile measurements play an important role in atmospheric research and meteorology. One source of wind profile data are Doppler wind lidars, which are laser-based remote sensing instruments that measure wind speed and wind direction up to a few hundred meters or even a few kilometers. Commercial wind lidars use the laser wavelength of 1.5 µm and therefore backscatter is mainly from aerosols while clear air backscatter is minimal, limiting the range to the boundary layer typically.</p><p>We have carried out a two-year intercomparison of the ZephIR 300M (ZX Lidars) short-range wind lidar and tall mast wind measurements at Cabauw [1]. We have focused on the (height-dependent) data availability of the wind lidar under various meteorological conditions and the data quality through a comparison with in situ wind measurements at several levels in the 213m tall meteorological mast. We have found an overall availability of quality-controlled wind lidar data of 97% to 98 %, where the missing part is mainly due to precipitation events exceeding 1 mm/h or fog or low clouds below 100 m. The mean bias in the horizontal wind speed is within 0.1 m/s with a high correlation between the mast and wind lidar measurements, although under some specific conditions (very high wind speed, fog or low clouds) larger deviations are observed. This instrument is being deployed within North Sea wind farms.</p><p>Recently, a scanning long-range wind lidar Windcube 200S (Leosphere/Vaisala) has been installed at Cabauw, as part of the Ruisdael Observatory program [2]. The scanning Doppler wind lidars will provide detailed measurements of the wind field, aerosols and clouds around the Cabauw site, in coordination with other instruments, such as the cloud radar.</p><p>[1] Knoop, S., Bosveld, F. C., de Haij, M. J., and Apituley, A.: A 2-year intercomparison of continuous-wave focusing wind lidar and tall mast wind measurements at Cabauw, Atmos. Meas. Tech., 14, 2219–2235, 2021</p><p>[2] https://ruisdael-observatory.nl/</p>

scholarly journals Comparison of Large Eddy Simulations of a convective boundary layer with wind LIDAR measurements

2012 ◽  
Vol 8 (1) ◽  
pp. 83-86 ◽  
Author(s):  
J. G. Pedersen ◽  
M. Kelly ◽  
S.-E. Gryning ◽  
R. Floors ◽  
E. Batchvarova ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Geostrophic Wind ◽  
Large Eddy Simulations ◽  
Horizontal Wind ◽  
Convective Boundary ◽  
Horizontal Wind Speed ◽  
Large Eddy ◽  
Lidar Measurements ◽  
Wind Lidar

Abstract. Vertical profiles of the horizontal wind speed and of the standard deviation of vertical wind speed from Large Eddy Simulations of a convective atmospheric boundary layer are compared to wind LIDAR measurements up to 1400 m. Fair agreement regarding both types of profiles is observed only when the simulated flow is driven by a both time- and height-dependent geostrophic wind and a time-dependent surface heat flux. This underlines the importance of mesoscale effects when the flow above the atmospheric surface layer is simulated with a computational fluid dynamics model.

scholarly journals Airborne Wind Lidar Measurements of Vertical and Horizontal Winds for the Investigation of Orographically Induced Gravity Waves

2017 ◽  
Vol 34 (6) ◽  
pp. 1371-1386 ◽  
Author(s):  
Benjamin Witschas ◽  
Stephan Rahm ◽  
Andreas Dörnbrack ◽  
Johannes Wagner ◽  
Markus Rapp
Keyword(s):  
Wind Speed ◽  
Gravity Waves ◽  
Power Spectra ◽  
Horizontal Resolution ◽  
Vertical Wind ◽  
Horizontal Wind ◽  
Horizontal Wind Speed ◽  
Lidar Measurements ◽  
Vertical Wind Speed ◽  
Wind Lidar

AbstractAirborne coherent Doppler wind lidar measurements, acquired during the Gravity Wave Life-Cycle (GW-LCYCLE) I field campaign performed from 2 to 14 December 2013 in Kiruna, Sweden, are used to investigate internal gravity waves (GWs) induced by flow across the Scandinavian Mountains. Vertical wind speed is derived from lidar measurements with a mean bias of less than 0.05 m s−1 and a standard deviation of 0.2 m s−1 by correcting horizontal wind projections onto the line-of-sight direction by means of ECMWF wind data. The horizontal wind speed and direction are retrieved from lidar measurements by applying a velocity–azimuth display scan and a spectral accumulation technique, leading to a horizontal resolution of about 9 km along the flight track and a vertical resolution of 100 m, respectively. Both vertical and horizontal wind measurements are valuable for characterizing GW properties as demonstrated by means of a flight performed on 13 December 2013 acquired during weather conditions favorable for orographic GW excitation. Wavelet power spectra of the vertical wind speed indicate that the horizontal GW wavelengths lay mainly between 10 and 30 km and that the GW amplitude above the mountain ridge decreases with increasing altitude. Additionally, the perturbations of the horizontal wind speed are analyzed, showing horizontal wavelengths in the excitation region of 100–125 km with upwind-tilted wave fronts. By means of elevation power spectra, it is revealed that vertical wind power spectra are dominated by the short-wave elevation part, whereas horizontal wind perturbations are dominated by the long-wave part.

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>

scholarly journals Wind speed vector restoration algorithm

2018 ◽  
Vol 176 ◽  
pp. 06012 ◽  
Author(s):  
Nikolay Baranov ◽  
Gleb Petrov ◽  
Ilia Shiriaev
Keyword(s):  
Signal Processing ◽  
Wind Speed ◽  
Data Processing ◽  
Restoration Algorithm ◽  
Continuous Scanning ◽  
Scanning Lidar ◽  
Wind Lidar ◽  
Processing Software ◽  
Parameters Calculation

Impulse wind lidar (IWL) signal processing software developed by JSC «BANS» recovers full wind speed vector by radial projections and provides wind parameters information up to 2 km distance. Increasing accuracy and speed of wind parameters calculation signal processing technics have been studied in this research. Measurements results of IWL and continuous scanning lidar were compared. Also, IWL data processing modeling results have been analyzed.

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>

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.

The Role of Wind Speed and Wind Shear for Banner Cloud Formation

2019 ◽  
Vol 77 (4) ◽  
pp. 1199-1212
Author(s):  
Volkmar Wirth ◽  
Pascal Bubel ◽  
Joachim Eichhorn ◽  
Elmar Schömer ◽  
Tobias Kremer ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Shear ◽  
Cloud Formation ◽  
Line Of Sight ◽  
Vortical Structures ◽  
Ambient Wind ◽  
Large Eddy ◽  
Flow Geometry ◽  
Wind Lidar

Abstract Banner clouds are clouds that appear to be attached to the leeward face of a steep mountain. This paper investigates the role of wind speed and wind shear for the formation of banner clouds. Large-eddy simulations are performed to simulate the flow of dry air past an idealized pyramid-shaped mountain. The potential for cloud formation is diagnosed through the Lagrangian vertical parcel displacement, which in the case of a banner cloud shows a plume of large values in the lee of the mountain. In addition, vortical structures are visualized through streamlines and their curvature. A series of sensitivity experiments indicates that both the flow and the banner cloud occurrence are largely independent of the ambient wind speed U. On the other hand, the shear of the ambient wind has a profound impact on the location of the stagnation point on the windward face as well as on the flow geometry in the lee of the mountain. The relevant measure for shear is H/Hs, where H denotes the height of the mountain and Hs = U/Uz is the scale height of the shear (with Uz denoting the scale of the shear). The simulations are also used to compute the line-of-sight velocity component seen by a hypothetical Doppler wind lidar positioned in the lee of the mountain; the analysis suggests that such sensitivities can potentially be detected using modern wind lidar technology.

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