Nonlinear averaging noise reduction method for differential absorption Lidar data on water vapor isotopes

The water vapor isotopic ratio is a natural tracer for understanding the atmospheric exchanges and changes within air masses. Differential Absorption Lidar (DiAL) method is commonly implemented for a number of ground-based and airborne greenhouse gas measurement applications. However, to measure water vapor isotope concentrations, the DIAL's spectral window is in the 2μm range for direct detection. In this configuration, other sources of random noise can be neglected in front of detection noise, which increases with range, especially as the non-main isotope is very rare in the atmosphere. We therefore intend to reduce noise contribution with a non-constant Scheimpflug-like averaging for an example of data set from a 5-hours measurement campaign in the Paris region.