Fog droplet distribution functions for lidar.

Area of Science:

• Atmospheric optics
• Remote sensing

Background:

• Lidar data interpretation for fog is hindered by approximations in Mie scattering cross sections and unclear droplet size distribution functions.
• Accurate fog characterization is crucial for various applications, including aviation and climate modeling.

Purpose of the Study:

• To develop a method for generating fog droplet size distribution functions from experimental data.
• To improve the accuracy of lidar-based fog analysis by utilizing refined Mie scattering cross sections and derived distribution functions.

Main Methods:

• Generation of droplet size distribution functions directly from experimental data.
• Application of newly available Mie scattering cross sections for calculating optical properties.
• Analysis of singly scattered ruby laser pulses for backscattering and extinction coefficients.

Main Results:

• The developed method successfully generates distribution functions from experimental data.
• Calculated backscattering and extinction coefficients show improved accuracy for fog.
• The study identifies the required experimental lidar accuracies for precise determination of fog droplet size distribution.

Conclusions:

• The developed method overcomes previous limitations in lidar fog interpretation.
• Accurate determination of fog droplet size distribution is achievable with specific experimental lidar accuracies.
• This research advances the capability of remote sensing techniques for atmospheric studies.