The atmospheric backscatter signal measured by a volume imaging lidar is dependent, in part, on the number of aerosol particles in the measurement volume. When the false color image is created by combining a number of lidar returns over a range of angles, atmospheric aerosol structures can be visualized.

For example, this figure shows an aerosol structure below a cumulus cloud. The magnitude of the return ranges from blue, white, yellow, and pink, where blue is the weakest signal and pink is the strongest. The cloud is pink and the plume is white and yellow. Also notice the white structures on the bottom and right, these structures show surface plumes containing aerosol generated by white caps.
For example, this figure shows an aerosol structure below a cumulus cloud. The magnitude of the return ranges from blue, white, yellow, and pink, where blue is the weakest signal and pink is the strongest. The cloud is pink and the plume is white and yellow. Also notice the white structures on the bottom and right, these structures show surface plumes containing aerosol generated by white caps.
The movement of aerosol structures can be seen during a sequence of horizontal lidar scans. NEVIL can complete a scan across 100 m in approximately 2 seconds. When the spatial correlation function is calculated for two scans separated in time, the peak of the correlation function is spatially shifted by a distance that is proportional to the wind speed. Using a Gaussian model, the wind speed can be objectively determined.
The movement of aerosol structures can be seen during a sequence of horizontal lidar scans. NEVIL can complete a scan across 100 m in approximately 2 seconds. When the spatial correlation function is calculated for two scans separated in time, the peak of the correlation function is spatially shifted by a distance that is proportional to the wind speed. Using a Gaussian model, the wind speed can be objectively determined.
This figure shows a series of correlation measurements and the Gaussian models fit to the data. The bottom line line plots shows the measurement for different time separations (0, 2, 4,6, 8, and 10 seconds). In this case Gaussian fit shows that the radial and cross speeds are 11.9 and 7.3 m/s respectively.
This figure shows a series of correlation measurements and the Gaussian models fit to the data. The bottom line line plots shows the measurement for different time separations (0, 2, 4,6, 8, and 10 seconds). In this case Gaussian fit shows that the radial and cross speeds are 11.9 and 7.3 m/s respectively.
If the lidar is aimed at a shallow elevation angle and scanned in azimuth, a wind profile can be generated. The figure above shows a wind measurement made off Pt. Sur CA in 2006. In addition to wind speed and direction, the wind variance profile is shown. As the time separation between scans increases, the width of the correlation function increases and this rate of increase is modeled providing an estimate the wind variance.
If the lidar is aimed at a shallow elevation angle and scanned in azimuth, a wind profile can be generated. The figure above shows a wind measurement made off Pt. Sur CA in 2006. In addition to wind speed and direction, the wind variance profile is shown. As the time separation between scans increases, the width of the correlation function increases and this rate of increase is modeled providing an estimate the wind variance.