Improvement of wind retrieval algorithm for Rayleigh Doppler lidar

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.

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Validating Precision Estimates in Horizontal Wind Measurements from a Doppler Lidar

10.5194/amt-2016-312 ◽

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.

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

Journal of Atmospheric and Oceanic Technology ◽

10.1175/2010jtecha1495.1 ◽

2010 ◽

Vol 27 (11) ◽

pp. 1881-1892 ◽

Cited By ~ 7

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.

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Wind retrieval algorithm of Rayleigh Doppler lidar

Acta Physica Sinica ◽

10.7498/aps.60.060704 ◽

2011 ◽

Vol 60 (6) ◽

pp. 060704

Author(s):

Shu Zhi-Feng ◽

Dou Xian-Kang ◽

Wang Zhong-Chun ◽

Shen Fa-Hua ◽

Sun Dong-Song ◽

...

Keyword(s):

Retrieval Algorithm ◽

Doppler Lidar ◽

Wind Retrieval

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A ‘Track-Wise’ Wind Retrieval Algorithm for the CYGNSS Mission

IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium ◽

10.1109/igarss.2019.8898099 ◽

2019 ◽

Cited By ~ 1

Author(s):

Faozi Said ◽

Zorana Jelenak ◽

Jeonghwang Park ◽

Seubson Soisuvarn ◽

Paul S. Chang

Keyword(s):

Retrieval Algorithm ◽

Wind Retrieval

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

Atmospheric Measurement Techniques ◽

10.5194/amt-8-2813-2015 ◽

2015 ◽

Vol 8 (7) ◽

pp. 2813-2825 ◽

Cited By ~ 4

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.

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Depiction of complex airflow near Hong Kong International Airport using a Doppler LIDAR with a two-dimensional wind retrieval technique

Meteorologische Zeitschrift ◽

10.1127/0941-2948/2007/0220 ◽

2007 ◽

Vol 16 (5) ◽

pp. 491-504 ◽

Cited By ~ 21

Author(s):

Pak Wai Chan ◽

Ai Mei Shao

Keyword(s):

Hong Kong ◽

Two Dimensional ◽

Doppler Lidar ◽

Wind Retrieval ◽

International Airport ◽

Retrieval Technique ◽

Hong Kong International Airport

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Retrieving Winds in the Surface Layer over Land Using an Airborne Doppler Lidar

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-11-00139.1 ◽

2012 ◽

Vol 29 (4) ◽

pp. 487-499 ◽

Cited By ~ 5

Author(s):

K. S. Godwin ◽

S. F. J. De Wekker ◽

G. D. Emmitt

Keyword(s):

Surface Wind ◽

Surface Wind Speed ◽

Lower Atmosphere ◽

Doppler Lidar ◽

Near Surface ◽

Wind Retrieval ◽

Wind Speed Maximum ◽

Salinas Valley ◽

Wind Retrievals ◽

Wind Profiles

Abstract Airborne Doppler wind lidars are increasingly being used to measure winds in the lower atmosphere at higher spatial resolution than ever before. However, wind retrieval in the range gates closest to the earth’s surface remains problematic. When a laser beam from a nadir-pointing airborne Doppler wind lidar intercepts the ground, the return signal from the ground mixes with the windblown aerosol signal. As a result, winds in a layer adjacent to the surface are often unreliable and removed from wind profiles. This paper describes the problem in detail and discusses a two-step approach to improve near-surface wind retrievals. The two-step approach involves removing high-intensity ground returns and identifying and tracking aerosol radial velocities in the layer affected by ground interference. Using this approach, it is shown that additional range gates closer to the surface can be obtained, thereby further enhancing the potential of airborne Doppler lidar in atmospheric applications. The benefits of the two-step approach are demonstrated using measurements acquired over the Salinas Valley in central California. The additional range gates reveal details of the wind field that were previously not quantified with the original approach, such as a pronounced near-surface wind speed maximum.

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