An Analysis of the Performance of the UFAM Pulsed Doppler Lidar for Observing the Boundary Layer

Pearson, Guy N.; Davies, F.; Collier, C. G.

doi:10.1175/2008jtecha1128.1

Cited by 298 publications

(279 citation statements)

References 23 publications

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“…Previous intercomparisons of DL and RWP winds have generally shown good agreement Pearson et al, 2009;Shaw et al, 2003). These intercomparisons, however, were always based on temporally shortterm measurement periods.…”

Section: E Päschke Et Al: a 1-year Comparison Of Wind Profile Measumentioning

confidence: 75%

“…A translation of this error into the corresponding error for the horizontal wind resulted in an error of less than 0.11-0.27 m s −1 for a 30 min measurement period, depending on the beam pointing sequence (fivebeam or three-beam pointing Doppler beam swinging (DBS) configuration). Pearson et al (2009) compared wind measurements from a 9 min Doppler lidar scan and 10 min averaged 1290 MHz radar data for four different times which also showed a very good level of agreement, except for somewhat less well correlated wind speed data, which was attributed to insects or ground clutter contamination. A month-long field study has been carried out in the Salt Lake Valley (Shaw et al, 2003).…”

Section: E Päschke Et Al: a 1-year Comparison Of Wind Profile Measumentioning

confidence: 88%

“…For reliable Doppler velocity estimates with an approximate precision of < 30 cm s −1 the manufacturer of the StreamLine Doppler lidar suggests using a threshold SNR of −18.2 dB (0.015), see also Fig. 2c in Pearson et al (2009). Note that this precision value describes the performance of the Doppler estimator which depends on both the instrument (detector noise) and the natural atmospheric variability within the resolution volume.…”

Section: Snr Thresholding Techniquementioning

confidence: 99%

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An assessment of the performance of a 1.5 μm Doppler lidar for operational vertical wind profiling based on a 1-year trial

Päschke¹,

Leinweber²,

Lehmann³

2015

Atmos. Meas. Tech.

106

153

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Abstract. We present the results of a 1-year quasioperational testing of the 1.5 µm StreamLine Doppler lidar developed by Halo Photonics from 2 October 2012 to 2 October 2013. The system was configured to continuously perform a velocity-azimuth display scan pattern using 24 azimuthal directions with a constant beam elevation angle of 75 • . Radial wind estimates were selected using a rather conservative signal-to-noise ratio based threshold of −18.2 dB (0.015). A 30 min average profile of the wind vector was calculated based on the assumption of a horizontally homogeneous wind field through a Moore-Penrose pseudoinverse of the overdetermined linear system. A strategy for the quality control of the retrieved wind vector components is outlined for ensuring consistency between the Doppler lidar wind products and the inherent assumptions employed in the wind vector retrieval. Quality-controlled lidar measurements were compared with independent reference data from a collocated operational 482 MHz radar wind profiler running in a four-beam Doppler beam swinging mode and winds from operational radiosonde measurements. The intercomparison results reveal a particularly good agreement between the Doppler lidar and the radar wind profiler, with root mean square errors ranging between 0.5 and 0.7 m s −1 for wind speed and between 5 and 10 • for wind direction. The median of the half-hourly averaged wind speed for the intercomparison data set is 8.2 m s −1 , with a lower quartile of 5.4 m s −1 and an upper quartile of 11.6 m s −1 .

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Section: E Päschke Et Al: a 1-year Comparison Of Wind Profile Measumentioning

confidence: 75%

Section: E Päschke Et Al: a 1-year Comparison Of Wind Profile Measumentioning

confidence: 88%

Section: Snr Thresholding Techniquementioning

confidence: 99%

See 1 more Smart Citation

An assessment of the performance of a 1.5 μm Doppler lidar for operational vertical wind profiling based on a 1-year trial

Päschke¹,

Leinweber²,

Lehmann³

2015

Atmos. Meas. Tech.

106

153

View full text Add to dashboard Cite

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“…The Lidar system is capable of recording raw data, making it possible to reprocess the data to provide time series with different gate lengths and frequencies. The system is operated with a collimated output beam, and the full width at half maximum (FWHM) is about 35 m. The instrument is described in more detail in Pearson et al [12]. In the following sections, a brief description of the site will be provided before the setup of the instruments and the methodology of the analysis will be explained.…”

Section: Methodsmentioning

confidence: 99%

Wind in Complex Terrain—Lidar Measurements for Evaluation of CFD Simulations

et al. 2018

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Abstract:Computational Fluid Dynamics (CFD) is widely used to predict wind conditions for wind energy production purposes. However, as wind power development expands into areas of even more complex terrain and challenging flow conditions, more research is needed to investigate the ability of such models to describe turbulent flow features. In this study, the performance of a hybrid Reynolds-Averaged Navier-Stokes (RANS)/Large Eddy Simulation (LES) model in highly complex terrain has been investigated. The model was compared with measurements from a long range pulsed Lidar, which first were validated with sonic anemometer data. The accuracy of the Lidar was considered to be sufficient for validation of flow model turbulence estimates. By reducing the range gate length of the Lidar a slight additional improvement in accuracy was obtained, but the availability of measurements was reduced due to the increased noise floor in the returned signal. The DES model was able to capture the variations of velocity and turbulence along the line-of-sight of the Lidar beam but overestimated the turbulence level in regions of complex flow.

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“…Lane et al, 2013). The instrument sensitivity depends on the amount of aerosol present and the velocity measurement uncertainty is related to the strength of the backscattered signal (Pearson et al, 2009). It typically takes a second or more to measure each line of sight with sufficient sensitivity and therefore the temporal resolution of the wind measurement is often of the order of tens of seconds, which is not sufficient for gusts (e.g.…”

Section: Introductionmentioning

confidence: 99%

Untitled

2017

Quart J Royal Meteoro Soc

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A new methodology is proposed for scaling Doppler lidar observations of wind gusts to make them comparable with those observed at a meteorological mast. Doppler lidars can then be used to measure wind gusts in regions and heights where traditional meteorological mast measurements are not available. This novel method also provides estimates for wind gusts at arbitrary gust durations, including those shorter than the temporal resolution of the Doppler lidar measurements. The input parameters for the scaling method are the measured wind-gust speed as well as the mean and standard deviation of the horizontal wind speed. The method was tested using WindCube V2 Doppler lidar measurements taken next to a 100 m high meteorological mast. It is shown that the method can provide realistic Doppler lidar estimates of the gust factor, i.e. the ratio of the wind-gust speed to the mean wind speed. The method reduced the bias in the Doppler lidar gust factors from 0.07 to 0.03 and can be improved further to reduce the bias by using a realistic estimate of turbulence. Wind gust measurements are often prone to outliers in the time series, because they represent the maximum of a (moving-averaged) horizontal wind speed. To assure the data quality in this study, we applied a filtering technique based on spike detection to remove possible outliers in the Doppler lidar data. We found that the spike detection-removal method clearly improved the wind-gust measurements, both with and without the scaling method. Spike detection also outperformed the traditional Doppler lidar quality assurance method based on carrier-to-noise ratio, by removing additional unrealistic outliers present in the time series.

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An Analysis of the Performance of the UFAM Pulsed Doppler Lidar for Observing the Boundary Layer

Cited by 298 publications

References 23 publications

An assessment of the performance of a 1.5 μm Doppler lidar for operational vertical wind profiling based on a 1-year trial

An assessment of the performance of a 1.5 μm Doppler lidar for operational vertical wind profiling based on a 1-year trial

Wind in Complex Terrain—Lidar Measurements for Evaluation of CFD Simulations

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