Scheimpflug-like processing of differential absorption lidar data on water vapor

Differential Absorption Lidar (DiAL) method is widely used for a number of ground-based and airborne greenhouse gas measurement applications. However, for a direct detection in the 2µm range, other sources of random noise can be neglected in front of the detection noise which increases with ranging. We therefore propose to evaluate the effect of non-constant Scheimpflug-like averaging to reduce the signal-to-noise ratio along the line of sight, during a 5-hour measurement campaign in the Paris region.