Two-component horizontal wind vectors from the Raman-shifted Eye-safe Aerosol Lidar (REAL)

Two-component horizontal wind vectors were calculated by applying a cross-correlation 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 at a range of 1.61 km. 180245 pairs of vectors derived from 75 days of field data collected between 19 March and 11 June 2007 were used in the analysis. Examples of time series comparisons from 4-h periods during light, strong, and changing wind conditions will be presented. The correlation between lidar-derived components and sonic anemometer components changes as a function of the mean backscatter signal-to-noise ratio (SNR) in the block area, maxima of the cross-correlation function (CCF), observed wind speed, and turbulent kinetic energy (TKE). The correlation between the lidar-derived velocity components and sonic anemometer wind components tends to be highest during light wind conditions with low TKE. Although the correlation of high frequency perturbations tends to be poor during windy and turbulent conditions, the technique is capable of sensing the mean flow. Examples of 2-dimensional, 2-component, flow fields will be presented. The NSF/NCAR REAL at California State University Chico. Streamlined flow field from 2-component vectors derived from 2 scans of the REAL and application of the cross-correlation technique. The area of the image spans 4 km by 4 km.