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 Volume Scanning Strategies for 3D Wind Retrieval from Dual-Doppler Lidar Measurements

2010 ◽  
Vol 27 (11) ◽  
pp. 1881-1892 ◽  
Author(s):  
Susanne Drechsel ◽  
Georg J. Mayr ◽  
Michel Chong ◽  
Fotini K. Chow
Keyword(s):  
Retrieval Algorithm ◽  
Doppler Lidar ◽  
Wind Fields ◽  
Actual Measurement ◽  
Trade Off ◽  
Wind Retrieval ◽  
Scan Time ◽  
Temporal Smoothing ◽  
Spatial Coverage ◽  
Scanning Strategies

Abstract Dual-Doppler lidar volume scans for 3D wind retrieval must accommodate the conflicting goals of dense spatial coverage and short scan duration. In this work, various scanning strategies are evaluated with semisynthetic wind fields from analytical solutions and numerical simulations over flat and complex terrain using the Multiple-Doppler Synthesis and Continuity Adjustment Technique (MUSCAT) retrieval algorithm. The focus of this study is to determine how volume scan strategies affect performance of the wind retrieval algorithm. Interlaced scanning methods that take into account actual maximum measurement ranges are found to be optimal because they provide the best trade-off between retrieval accuracy, volume coverage, and scan time. A recommendation for scanning strategies is given, depending on actual measurement ranges, the variability of the wind situation, and the trade-off between spatial coverage and temporal smoothing.

scholarly journals Development and Application of a Simplified Coplane Wind Retrieval Algorithm Using Dual-Beam Airborne Doppler Radar Observations for Tropical Cyclone Prediction

2016 ◽  
Vol 144 (7) ◽  
pp. 2645-2666
Author(s):  
Christopher Melhauser ◽  
Fuqing Zhang
Keyword(s):  
Radial Velocity ◽  
Doppler Radar ◽  
Statistical Significance ◽  
Three Dimensional ◽  
Horizontal Wind ◽  
Retrieval Algorithm ◽  
Average Error ◽  
Scanning Angle ◽  
Wind Retrieval ◽  
Research Division

Abstract Based on established coplane methodology, a simplified three-dimensional wind retrieval algorithm is proposed to derive two-dimensional wind vectors from radial velocity observations by the tail Doppler radars on board the NOAA P3 hurricane reconnaissance aircraft. Validated against independent in situ flight-level and dropsonde observations before and after genesis of Hurricane Karl (2010), each component of the retrieved wind vectors near the aircraft track has an average error of approximately 1.5 m s−1, which increases with the scanning angle and distance away from the aircraft track. Simulated radial velocities derived from a convection-permitting simulation of Karl are further used to systematically quantify errors of the simplified coplane algorithm. The accuracy of the algorithm is strongly dependent on the time between forward and backward radar scans and to a lesser extent, the zero vertical velocity assumption at large angles relative to a plane parallel with the aircraft wings. A proof-of-concept experiment assimilating the retrieved wind vectors with an ensemble Kalman filter shows improvements in track and intensity forecasts similar to assimilating radial velocity super observations or the horizontal wind vectors from the analysis retrievals provided by the Hurricane Research Division of NOAA. Future work is needed to systematically evaluate this simplified coplane algorithm with proper error characteristics for TC initialization and prediction through a large number of events to establish statistical significance.

scholarly journals Retrieving horizontally resolved wind fields using multi-static meteor radar observations

2018 ◽  
Author(s):  
Gunter Stober ◽  
Jorge L. Chau ◽  
Juha Vierinen ◽  
Christoph Jacobi ◽  
Sven Wilhelm
Keyword(s):  
Continuous Wave ◽  
Lower Thermosphere ◽  
Horizontal Wind ◽  
Retrieval Algorithm ◽  
Meteor Radar ◽  
Wind Fields ◽  
Wind Retrieval ◽  
Radar Network ◽  
Frequency Agile ◽  
Kinematic Properties

Abstract. Recently, the MMARIA (Multi-static, multi-frequency Agile Radar for Investigations of the Atmosphere) concept of a multi-static VHF meteor radar network to derive horizontally resolved wind fields in the mesosphere/lower thermosphere was introduced. Here we present preliminary results of the MMARIA network above Eastern Germany using two transmitters located at Juliusruh and Collm, and 5 receiving links two monostatic and three multi-static). The observations are complemented during a one-week campaign, with a couple of addition continuous-wave coded transmitters, making a total of 7 multi-static links. In order to access the kinematic properties of non-homogenous wind fields we developed a wind retrieval algorithm that applies regularization to determine the non-linear wind field in the altitude range of 82–98 km. The derived horizontally resolved wind fields are compared to wind fields retrieved by a more established volume velocity processing that includes the horizontal gradients of the horizontal wind components. The potential of such observations and the new retrieval to investigate gravity waves with horizontal scales between 50–200 km is presented and discussed.

scholarly journals Improvement of wind retrieval algorithm for Rayleigh Doppler lidar

2012 ◽  
Vol 61 (3) ◽  
pp. 030702
Author(s):  
Shen Fa-Hua ◽  
Shu Zhi-Feng ◽  
Sun Dong-Song ◽  
Wang Zhong-Chun ◽  
Xue Xiang-Hui ◽  
...  
Keyword(s):  
Retrieval Algorithm ◽  
Doppler Lidar ◽  
Wind Retrieval

scholarly journals Profiling wind and greenhouse gases by infrared-laser occultation: results from end-to-end simulations in windy air

2015 ◽  
Vol 8 (7) ◽  
pp. 2813-2825 ◽  
Author(s):  
A. Plach ◽  
V. Proschek ◽  
G. Kirchengast
Keyword(s):  
Wind Speed ◽  
Greenhouse Gases ◽  
Doppler Shift ◽  
Lower Stratosphere ◽  
Infrared Laser ◽  
Retrieval Algorithm ◽  
Upper Troposphere ◽  
Wind Retrieval ◽  
End To End ◽  
Thermodynamic Variables

Abstract. The new mission concept of microwave and infrared-laser occultation between low-Earth-orbit satellites (LMIO) is designed to provide accurate and long-term stable profiles of atmospheric thermodynamic variables, greenhouse gases (GHGs), and line-of-sight (l.o.s.) wind speed with focus on the upper troposphere and lower stratosphere (UTLS). While the unique quality of GHG retrievals enabled by LMIO over the UTLS has been recently demonstrated based on end-to-end simulations, the promise of l.o.s. wind retrieval, and of joint GHG and wind retrieval, has not yet been analyzed in any realistic simulation setting. Here we use a newly developed l.o.s. wind retrieval algorithm, which we embedded in an end-to-end simulation framework that also includes the retrieval of thermodynamic variables and GHGs, and analyze the performance of both stand-alone wind retrieval and joint wind and GHG retrieval. The wind algorithm utilizes LMIO laser signals placed on the inflection points at the wings of the highly symmetric C18OO absorption line near 4767 cm−1 and exploits transmission differences from a wind-induced Doppler shift. Based on realistic example cases for a diversity of atmospheric conditions, ranging from tropical to high-latitude winter, we find that the retrieved l.o.s. wind profiles are of high quality over the lower stratosphere under all conditions, i.e., unbiased and accurate to within about 2 m s−1 over about 15 to 35 km. The wind accuracy degrades into the upper troposphere due to the decreasing signal-to-noise ratio of the wind-induced differential transmission signals. The GHG retrieval in windy air is not vulnerable to wind speed uncertainties up to about 10 m s−1 but is found to benefit in the case of higher speeds from the integrated wind retrieval that enables correction of wind-induced Doppler shift of GHG signals. Overall both the l.o.s. wind and GHG retrieval results are strongly encouraging towards further development and implementation of a LMIO mission.

scholarly journals Operational Multiple-Doppler Wind Retrieval Inferred from Long-Range Radial Velocity Measurements

2008 ◽  
Vol 47 (11) ◽  
pp. 2929-2945 ◽  
Author(s):  
Olivier Bousquet ◽  
Pierre Tabary ◽  
Jacques Parent du Châtelet
Keyword(s):  
Radial Velocity ◽  
Doppler Velocity ◽  
Velocity Measurements ◽  
Wind Fields ◽  
Pulse Rise Time ◽  
Wind Retrieval ◽  
Radar Network ◽  
Precipitation Regimes ◽  
Operational Networks ◽  
Scanning Strategies

Abstract The recent deployment of an innovative triple pulse rise time (PRT) scheme within the French operational radar network allows for the simultaneous collection of reflectivity and radial velocity measurements up to a range of 250 km with no ambiguity. This achievement brings new perspectives in terms of operational exploitation of Doppler measurements including the capability to consistently perform multiple-Doppler wind synthesis in a fully operational framework. Using real and simulated Doppler observations, the authors show that the 3D wind fields retrieved in that framework can definitely be relied upon to achieve a consistent and detailed mapping of the airflow structure in various precipitation regimes despite radar baselines averaging ∼180 km and very limited scanning strategies. This achievement could be easily transposed to other operational networks and represents a remarkable opportunity to add further value to operational Doppler velocity measurements.

Estimating Spatial Velocity Statistics with Coherent Doppler Lidar

2002 ◽  
Vol 19 (3) ◽  
pp. 355-366 ◽  
Author(s):  
Rod Frehlich ◽  
Larry Cornman
Keyword(s):  
Radial Velocity ◽  
Spatial Scales ◽  
Energy Dissipation Rate ◽  
Doppler Lidar ◽  
Wind Fields ◽  
Velocity Statistics ◽  
Coherent Doppler Lidar ◽  
Spatial Velocity ◽  
Large Measurement ◽  
Turbulent Velocity Field

Abstract The spatial statistics of a simulated turbulent velocity field are estimated using radial velocity estimates from simulated coherent Doppler lidar data. The structure functions from the radial velocity estimates are processed to estimate the energy dissipation rate ε and the integral length scale Li, assuming a theoretical model for isotropic wind fields. The performance of the estimates are described by their bias, standard deviation, and percentiles. The estimates of ε2/3 are generally unbiased and robust. The distribution of the estimates of Li are highly skewed; however, the median of the distribution is generally unbiased. The effects of the spatial averaging by the atmospheric movement transverse to the lidar beam during the dwell time of each radial velocity estimate are determined, as well as the error scaling as a function of the dimensions of the total measurement region. Accurate estimates of Li require very large measurement domains in order to observe a large number of independent samples of the spatial scales that define Li.

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 Coastal Wind Measurements Using a Single Scanning LiDAR

2020 ◽  
Vol 12 (8) ◽  
pp. 1347 ◽  
Author(s):  
Susumu Shimada ◽  
Jay Prakash Goit ◽  
Teruo Ohsawa ◽  
Tetsuya Kogaki ◽  
Satoshi Nakamura
Keyword(s):  
Wind Speed ◽  
Goodness Of Fit ◽  
Sonic Anemometer ◽  
Data Availability ◽  
Horizontal Wind ◽  
Research Station ◽  
Lidar Measurement ◽  
Wind Speeds ◽  
Wind Measurements ◽  
Scanning Lidar

A wind measurement campaign using a single scanning light detection and ranging (LiDAR) device was conducted at the Hazaki Oceanographical Research Station (HORS) on the Hazaki coast of Japan to evaluate the performance of the device for coastal wind measurements. The scanning LiDAR was deployed on the landward end of the HORS pier. We compared the wind speed and direction data recorded by the scanning LiDAR to the observations obtained from a vertical profiling LiDAR installed at the opposite end of the pier, 400 m from the scanning LiDAR. The best practice for offshore wind measurements using a single scanning LiDAR was evaluated by comparing results from a total of nine experiments using several different scanning settings. A two-parameter velocity volume processing (VVP) method was employed to retrieve the horizontal wind speed and direction from the radial wind speed. Our experiment showed that, at the current offshore site with a negligibly small vertical wind speed component, the accuracy of the scanning LiDAR wind speeds and directions was sensitive to the azimuth angle setting, but not to the elevation angle setting. In addition to the validations for the 10-minute mean wind speeds and directions, the application of LiDARs for the measurement of the turbulence intensity (TI) was also discussed by comparing the results with observations obtained from a sonic anemometer, mounted at the seaward end of the HORS pier, 400 m from the scanning LiDAR. The standard deviation obtained from the scanning LiDAR measurement showed a greater fluctuation than that obtained from the sonic anemometer measurement. However, the difference between the scanning LiDAR and sonic measurements appeared to be within an acceptable range for the wind turbine design. We discuss the variations in data availability and accuracy based on an analysis of the carrier-to-noise ratio (CNR) distribution and the goodness of fit for curve fitting via the VVP method.

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