Extracting vertical winds from simulated clouds with ground-based coherent Doppler lidar.

The performance of mean velocity estimators is determined by computer simulations for solid-state coherent Doppler lidar measurements of wind fields at a cloud interface with deterministic profiles of velocity and aerosol backscatter. Performance of the velocity estimates is characterized by the standard deviation about the estimated mean and the bias referenced to the input velocity. A new class of estimators are required for cloud conditions, as traditional techniques result in biased estimates. We consider data with high signal energy that produces negligible random outliers.