A motion estimation algorithm was applied to image sequences produced by a horizontally scanning elastic backscatter lidar. The algorithm, a wavelet-based optical flow estimator named Typhoon, produces dense two-component vector flow fields that correspond to the apparent motion of microscale aerosol features. To validate the efficacy of this approach for the remote measurement of wind fields in the lower atmosphere, an experiment was conducted in Chico, California, in 2013 and 2014. The flow fields, estimated every 17 s, were compared with measurements from an independent Doppler lidar. Time series of wind speed and direction, statistical assessment of the 10-min averages, and examples of wind fields are presented. The comparison of 10-min averages at 100 m AGL reveals excellent correlations between estimates from the Typhoon algorithm and measurements from the Doppler lidar. Power spectra and spectral transfer functions are computed to estimate the filtering effects of the algorithm in the spatial domain.

Numerical and field experiments were conducted to test an optimized cross-correlation algorithm (CCA) for the remote sensing of two-component wind vectors from horizontally scanning elastic backscatter lidar data. Each vector is the result of applying the algorithm to a square and contiguous subset of pixels (an interrogation window) in the lidar scan area. Synthetic aerosol distributions and flow fields were used to investigate the accuracy and precision of the technique. Results indicate that in neutral static stability, when the mean flow direction over the interrogation window is relatively uniform, the random error of the estimates increases as the mean wind speed and turbulence intensity increases. In convective conditions, larger errors may occur as a result of the cellular nature of convection and the dramatic changes in wind direction that may span the interrogation window. Synthetic fields were also used to determine the significance of various image processing and numerical steps used in the CCA. Results show that an iterative approach that dynamically reduces the block size provides the largest performance gains. Finally, data from a field experiment conducted in 2013 in Chico, California, are presented. Comparisons with Doppler lidar data indicate excellent agreement for the 10-min mean wind velocity computed over a set of 150 h: the root-mean-square deviations (and slopes) for the u and υ components are 0.36 m s−1 (0.974) and 0.37 m s−1 (0.991), respectively, with correlation coefficients > 0.99.

Two-component horizontal motion vectors of aerosol features were calculated by applying a crosscorrelation algorithm to square image blocks extracted from consecutive pairs of elastic backscatter lidar scans. The resulting vector components were compared with corresponding horizontal wind components from tower-mounted sonic anemometers located at the center of the image blocks. In the analysis 180 245 pairs of vectors derived from 75 days of field data collected between 19 March and 11 June 2007 were used. Examples of time series comparisons from 4-h periods during light, strong, and changing wind conditions are presented. Mean signal-to-noise ratios (SNRs) of the block backscatter data, maxima of the cross-correlation functions (CCFs), observed wind speed, and turbulent kinetic energy (TKE) were also calculated for each velocity component comparison. The correlation between the lidar-derived motion components and sonic anemometer wind components tends to be highest during light wind conditions with low TKE. An empirical relationship is presented that enables the elimination of vectors that are likely to be significantly different than the anemometer measurement. When applied to the entire set of scans available, this quality control (QC) method increases the correlation between the two forms of measurements. Finally, the cross-correlation algorithm and QC method are applied to a mesh of locations over pairs of scans. Two examples of twodimensional and two-component vector flow fields are shown. In one case, the flow field reveals a rotational circulation associated with a vortex and, in the other case, convergence and transport near the leading edge of a density current front.

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The performance of two direct-detection atmospheric lidar systems with very different methods of generating and detecting laser radiation is compared as the result of a field experiment held in March 2015, in Chico, California. During the noncontinuous, 11-day test period, in which the systems operated side by side, the micropulse lidar was operated at its maximum pulse repetition frequency (15 kHz) and integrated elastic backscatter over the interpulse period of the analog direct-detection lidar (0.1 s). Operation at the high pulse repetition frequency resulted in second-trip echoes that contaminated portions of the data. The performance of the micropulse lidar varied with background brightness-as expected with a photon-counting receiver-yet showed equal or larger backscatter intensity signal-to-noise ratio throughout the experiment. Examples of wind fields and time series of wind vectors from both systems during the Chico experiment are presented. In addition, scans over the ocean that were collected by the micropulse lidar during a subsequent deployment on the northern California coast are presented. We conclude by reviewing the advantages and disadvantages of each system and make some suggestions to improve the design and performance of future systems. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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