Correlating Lidar Range Performance with Atmospheric Parameters

Wind Lidars have been increasingly integrated in various applications for their unique ability to measure the wind speed for several kilometers. They also provide a significant advantage in meteorological networks as they allow to continually measure wind speeds throughout all the boundary layer. Applications such as wind field measurements for wind farm preventative energy management or airport shear detection rely on a lidar’s measurement range. If the ability of a lidar to measure across several kilometers provides a unique advantage, the precise distance of its measurement range can vary depending on atmospheric conditions.

Indeed, the characteristics of the return signal of remote sensors depend directly on the state of the atmosphere, which is based on extinction, backscatter, temperature, and more. Though a lidar range performance can be physically defined based on its signal processing qualities, the exact relationship between the lidar measurement range and the atmospheric conditions is still unknown. Thus, this study aims to clarify and quantify the relationship between the measurement range of the lidar and various atmospheric parameters.

To this end, several tools, such as regression, predictor techniques, or conditional statistics, were used. The variables considered in this analysis are lidar range, visibility, backscatter, PM2.5, PM10, relative humidity, AOD, temperature, and hour of the day.

In this study, we established the link between the lidar measurement range and various atmospheric parameters. In particular, we demonstrated that fluctuations of such parameters alongside the night and day cycle can have an effect on the Lidar range. Further development could lead to a finer prediction of the measurement range depending on the location of the device, thus helping users to plan and predict their measurement acquisition more efficiently.