Design, Verification and Use of a Novel Ground-Based Elastic Lidar Simulator

Lidar is a powerful tool for observing vertical distributions and properties of atmospheric components including aerosols, clouds and trace gases. Observations of aerosol physical and optical properties are important for understanding key questions related to climate and air quality. Additionally, rapid detection of aerosol events such volcanic ash emissions, dust storms and wild?re smoke can be important for informing decision makers.

A wide range of lidar instruments are available depending on the desired application. Well established lidar research networks such as EARLINET have developed robust standards for lidar instrumentation and retrievals. If the goal is to optimize instrument designs for speci?c applications, a exible and realistic method to simulate real-world performance is required.

This thesis presents a novel, ground-based elastic lidar simulator that can be utilized to inform the design of future instruments. The framework is based around the single scattering lidar equation. It incorporates key lidar parameters such as laser power, receiver area and laser wavelength, and also models the impact of the molecular atmosphere on lidar signals. The simulator is veri?ed extensively through applying inversions to the simulated outputs and comparing these with retrieved pro?les from existing systems. Finally, a range of hypothetical new system designs are investigated for feasibility in different atmospheric scenarios using simulations of the signal-to-noise ratio, with a view towards understanding how lower speci?cation systems might perform in different applications.

Results showed that simulated range-corrected signals were calculated to be within a standard deviation of the measurements received from a well-characterised EARLINET system. Further comparisons with other systems identi?ed key discrepancies which arose, the reasons behind which were explored. The key areas for future work were identi?ed, included informing design of future lidar systems and understanding their ability to classify aerosols.