scholarly journals Scan strategies for wind profiling with Doppler lidar – An LES-based evaluation

2021 ◽  
Author(s):  
Charlotte Rahlves ◽  
Frank Beyrich ◽  
Siegfried Raasch
Keyword(s):  
Wind Speed ◽  
Zenith Angle ◽  
Interval Length ◽  
Horizontal Wind ◽  
Detailed Knowledge ◽  
Doppler Lidar ◽  
Convective Boundary ◽  
Retrieval Error ◽  
True Value ◽  
Relevant Effect

Abstract. Lidar scan techniques for wind profiling rely on the assumption of a horizontally homogeneous wind field and stationarity for the duration of the scan. As this condition is mostly violated in reality, detailed knowledge of the resulting measurement error is required. The objective of this study is to quantify and compare the expected error associated with Doppler-lidar wind profiling for different scan strategies and meteorological conditions by performing virtual measurements implemented in a large-eddy simulation (LES) model. Various factors influencing the lidar retrieval error are analyzed through comparison of the wind measured by the virtual lidar with the ‘true’ value generated by the LES. These factors include averaging interval length, zenith angle configuration, scan technique and instrument orientation. For the first time, ensemble simulations are used to determine the statistically expected uncertainty of the lidar error. The analysis reveals a root-mean-square deviation (RMSD) of less than 1 m s−1 for 10 min averages of wind speed measurements in a moderately convective boundary layer, while RMSD exceeds 2 m s−1 in strongly convective conditions. Unlike instrument orientation and scanning scheme, the zenith angle configuration proved to have significant effect on the retrieval error. Horizontal wind speed error is reduced when a larger zenith angle configuration is used, but is increased for measurements of vertical wind. Results suggest that the scan strategy has a relevant effect on the lidar retrieval error and that instrument configuration should be chosen depending on the quantity of interest and the flow conditions in which the measurement is performed.

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 Shipborne Wind Measurement and Motion-induced Error Correction of a Coherent Doppler Lidar over the Yellow Sea in 2014

2018 ◽  
Vol 11 (3) ◽  
pp. 1313-1331 ◽  
Author(s):  
Xiaochun Zhai ◽  
Songhua Wu ◽  
Bingyi Liu ◽  
Xiaoquan Song ◽  
Jiaping Yin
Keyword(s):  
Wind Speed ◽  
Yellow Sea ◽  
The Yellow Sea ◽  
Horizontal Wind ◽  
Measuring Error ◽  
Doppler Lidar ◽  
Random Errors ◽  
Horizontal Wind Speed ◽  
Pointing Error ◽  
Coherent Doppler Lidar

Abstract. Shipborne wind observations by a coherent Doppler lidar (CDL) have been conducted to study the structure of the marine atmospheric boundary layer (MABL) during the 2014 Yellow Sea campaign. This paper evaluates uncertainties associated with the ship motion and presents the correction methodology regarding lidar velocity measurement based on modified 4-Doppler beam swing (DBS) solution. The errors of calibrated measurement, both for the anchored and the cruising shipborne observations, are comparable to those of ground-based measurements. The comparison between the lidar and radiosonde results in a bias of −0.23 ms−1 and a standard deviation of 0.87 ms−1 for the wind speed measurement, and 2.48, 8.84∘ for the wind direction. The biases of horizontal wind speed and random errors of vertical velocity are also estimated using the error propagation theory and frequency spectrum analysis, respectively. The results show that the biases are mainly related to the measuring error of the ship velocity and lidar pointing error, and the random errors are mainly determined by the signal-to-noise ratio (SNR) of the lidar backscattering spectrum signal. It allows for the retrieval of vertical wind, based on one measurement, with random error below 0.15 ms−1 for an appropriate SNR threshold and bias below 0.02 ms−1. The combination of the CDL attitude correction system and the accurate motion correction process has the potential of continuous long-term high temporal and spatial resolution measurement for the MABL thermodynamic and turbulence process.

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 Uncertainty model for dual-Doppler retrievals of wind speed and wind direction

2020 ◽  
Author(s):  
Nikola Vasiljević ◽  
Michael Courtney ◽  
Anders Tegtmeier Pedersen
Keyword(s):  
Wind Speed ◽  
Elevation Angle ◽  
Velocity Estimation ◽  
Horizontal Wind ◽  
Doppler Lidar ◽  
Horizontal Wind Speed ◽  
Uncertainty Model ◽  
Lidar Measurements ◽  
Python Package ◽  
Propagation Of Uncertainties

Abstract. In this paper we present an analytical model for estimating the uncertainty of the horizontal wind speed based on dual-Doppler lidar measurements. The model follows the propagation of uncertainties method and takes into account the uncertainty of radial velocity estimation, azimuth and elevation pointing angles, and ranging. The model is achieved by coupling ranging and elevation angle to uncertainty of the probed wind speed through a simple power-law shear model. The model has been implemented in Python and made freely available through as the Python package YADDUM.

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 Validating Precision Estimates in Horizontal Wind Measurements from a Doppler Lidar

2016 ◽  
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 ◽  
Horizontal Wind ◽  
Retrieval Algorithm ◽  
Doppler Lidar ◽  
Wind Fields ◽  
Wind Retrieval ◽  
Turbulence Effects

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. For this study, the lidar was configured to execute an 8-beam plan-position-indicator (PPI) scan once every 12 minutes during the 6 week deployment period. Several wind retrieval trials were conducted using different schemes for estimating the uncertainty 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 uncertainty was determined by direct calculation of radial velocity standard deviation along each pointing direction and range gate of the PPI scan. By contrast, setting the radial velocity uncertainty to the radial velocity precision (thereby ignoring turbulence effects) resulted in wind speed and direction precisions that were biased far too low and poor indicators of data quality.

scholarly journals Estimation of the Motion-Induced Horizontal-Wind-Speed Standard Deviation in an Offshore Doppler Lidar

2018 ◽  
Vol 10 (12) ◽  
pp. 2037 ◽  
Author(s):  
Miguel Gutiérrez-Antuñano ◽  
Jordi Tiana-Alsina ◽  
Andreu Salcedo ◽  
Francesc Rocadenbosch
Keyword(s):  
Standard Deviation ◽  
Wind Speed ◽  
Turbulence Intensity ◽  
Horizontal Wind ◽  
Doppler Lidar ◽  
Horizontal Wind Speed ◽  
Recursive Procedure ◽  
Scanning Pattern ◽  
The Impact ◽  
Speed Standard Deviation

This work presents a new methodology to estimate the motion-induced standard deviation and related turbulence intensity on the retrieved horizontal wind speed by means of the velocity-azimuth-display algorithm applied to the conical scanning pattern of a floating Doppler lidar. The method considers a ZephIR™300 continuous-wave focusable Doppler lidar and does not require access to individual line-of-sight radial-wind information along the scanning pattern. The method combines a software-based velocity-azimuth-display and motion simulator and a statistical recursive procedure to estimate the horizontal wind speed standard deviation—as a well as the turbulence intensity—due to floating lidar buoy motion. The motion-induced error is estimated from the simulator’s side by using basic motional parameters, namely, roll/pitch angular amplitude and period of the floating lidar buoy, as well as reference wind speed and direction measurements at the study height. The impact of buoy motion on the retrieved wind speed and related standard deviation is compared against a reference sonic anemometer and a reference fixed lidar over a 60-day period at the IJmuiden test site (the Netherlands). Individual case examples and an analysis of the overall campaign are presented. After the correction, the mean deviation in the horizontal wind speed standard deviation between the reference and the floating lidar was improved by about 70%, from 0.14 m/s (uncorrected) to −0.04 m/s (corrected), which makes evident the goodness of the method. Equivalently, the error on the estimated turbulence intensity (3–20 m/s range) reduced from 38% (uncorrected) to 4% (corrected).

scholarly journals Shipborne Wind Measurement and Motion-induced Error Correction by Coherent Doppler Lidar over Yellow Sea in 2014

2017 ◽  
Author(s):  
Xiaochun Zhai ◽  
Songhua Wu ◽  
Bingyi Liu ◽  
Xiaoquan Song ◽  
Jiaping Yin
Keyword(s):  
Standard Deviation ◽  
Wind Speed ◽  
Yellow Sea ◽  
Horizontal Wind ◽  
Measuring Error ◽  
Doppler Lidar ◽  
Random Errors ◽  
Horizontal Wind Speed ◽  
Pointing Error ◽  
Coherent Doppler Lidar

Abstract. Shipborne wind observations by the Coherent Doppler Lidar (CDL) have been conducted to study the structure of the Marine Atmospheric Boundary Layer (MABL) during the 2014 Yellow Sea campaign. This paper evaluates uncertainties associated with the ship motion and presents the correction methodology regarding lidar velocity measurement based on modified 4-Doppler Beam Swing (DBS) solution. The errors of calibrated measurement, both for the anchored and the cruising shipborne observations, are comparable to those of ground-based measurements. The comparison between the lidar and radiosonde gives the bias −0.1 ms−1 and the standard deviation 0.75 ms−1 for the wind speed measurement, and shows the bias and the standard deviation for the wind direction measurement. The biases and random errors of horizontal wind speed are also estimated using the error propagation theory and frequency spectrum analysis, respectively. The results show that the biases are mainly related to the measuring error of the ship velocity, and lidar pointing error and the random errors are mainly determined by the Signal-to-Noise Ratio (SNR) of lidar backscattering spectral signal. It allows for the retrieval of vertical wind, based on one measurement, with random error below 0.15 ms−1 for appropriate SNR threshold and bias below 0.02 ms−1. The combination of the CDL attitude correction system and the accurate motion correction process has the potential of continuous long-term high temporal and spatial resolution measurement for MABL thermodynamic and turbulence process.

scholarly journals Development and Experimental Testing of a Rotary Direct Wind Lidar System Based on Fabry.Perot Interferometer Technology-=SUP=-*-=/SUP=-

2021 ◽  
Vol 129 (6) ◽  
pp. 765
Author(s):  
Hao Yang ◽  
Zhiyuan Fang ◽  
Ye Cao ◽  
Xu Deng ◽  
Chenbo Xie ◽  
...  
Keyword(s):  
Wind Speed ◽  
Laser Frequency ◽  
Horizontal Wind ◽  
Doppler Lidar ◽  
Lidar System ◽  
Horizontal Wind Speed ◽  
Height Range ◽  
Speed Measurement ◽  
Fabry Perot ◽  
Wind Speed Measurement

A 532-nm Rayleigh--Mie Doppler lidar system based on three-channel Fabry--Perot interferometer (FPI) technology was developed to measure wind speed from the bottom of the troposphere to the top of the stratosphere. An FPI transmittance calibration experiment and laser frequency stability experiments were carried out, resulting in the accuracy of the emitted laser frequency falling within .8 MHz. In addition, multiple sets of radial wind speed detection experiments were conducted during day and night, and the results of horizontal wind speed detection experiments were compared with those from balloon radiosonde. Results showed that, although the signal-to-noise ratio is not high, due to factors such as the size of the telescope aperture and the low optical coupling efficiency of the system, the overall performance of the verification system is good. When the spatiotemporal resolution of a single radial wind speed measurement is 2 min and 75 m, the system has the ability to detect the wind field in the height range of 16 km. In the height range of roughly 2 km to 12 km, the horizontal wind speed of the system and the balloon radiosonde were compared, revealing a direct correlation between the data that exceeded 0.8. Thus, the accuracy of the system.s wind speed measurement results was fully verified. Keywords: Doppler lidar; rotary direct wind measurement; Fabry-Perot interferometer; Rayleigh-Mie scattering.

scholarly journals Winds in the Lower Cloud Level on the Nightside of Venus from VIRTIS-M (Venus Express) 1.74 μm Images

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 186
Author(s):  
Dmitry A. Gorinov ◽  
Ludmila V. Zasova ◽  
Igor V. Khatuntsev ◽  
Marina V. Patsaeva ◽  
Alexander V. Turin
Keyword(s):  
Wind Speed ◽  
Meridional Wind ◽  
Equatorial Region ◽  
Hadley Cell ◽  
Horizontal Wind ◽  
Simultaneous Increase ◽  
Volcanic Area ◽  
Infrared Thermal Imaging ◽  
Latitude Range ◽  
Lower Cloud

The horizontal wind velocity vectors at the lower cloud layer were retrieved by tracking the displacement of cloud features using the 1.74 µm images of the full Visible and InfraRed Thermal Imaging Spectrometer (VIRTIS-M) dataset. This layer was found to be in a superrotation mode with a westward mean speed of 60–63 m s−1 in the latitude range of 0–60° S, with a 1–5 m s−1 westward deceleration across the nightside. Meridional motion is significantly weaker, at 0–2 m s−1; it is equatorward at latitudes higher than 20° S, and changes its direction to poleward in the equatorial region with a simultaneous increase of wind speed. It was assumed that higher levels of the atmosphere are traced in the equatorial region and a fragment of the poleward branch of the direct lower cloud Hadley cell is observed. The fragment of the equatorward branch reveals itself in the middle latitudes. A diurnal variation of the meridional wind speed was found, as east of 21 h local time, the direction changes from equatorward to poleward in latitudes lower than 20° S. Significant correlation with surface topography was not found, except for a slight decrease of zonal wind speed, which was connected to the volcanic area of Imdr Regio.

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