Experimental validation of D parameter model for droplet sizing using off-axis lidar measurements

Area of Science:

• Atmospheric optics
• Remote sensing

Background:

• Accurate characterization of fog droplet size distribution is crucial for understanding atmospheric processes and improving visibility models.
• Lidar techniques offer non-intrusive methods for probing atmospheric properties.

Purpose of the Study:

• To investigate the retrieval of liquid droplet size distribution in fog using the backscattering lidar depolarization parameter.
• To evaluate the influence of scattering angles and refractive index on droplet size estimation.

Main Methods:

• Utilized a polarimetric off-axis lidar to measure backscattering depolarization ratios at various angles for water and mineral oil fogs.
• Employed constrained linear inversion, incorporating Mie theory calculations of depolarization parameters, to estimate effective droplet sizes.
• Validated the inversion scheme using Mie theory calculations as a kernel.

Main Results:

• Demonstrated that the circular depolarization parameter near the backscattering angle correlates with the forward-scattering diffraction peak.
• Showed that droplet size retrieval is sensitive to the choice of scattering angles and the refractive index of the droplets.
• Achieved consistency between lidar-derived droplet size distributions and in situ measurements.

Conclusions:

• Polarimetric lidar measurements of depolarization parameters provide a viable method for retrieving fog droplet size distributions.
• The developed constrained linear inversion scheme, supported by Mie theory, accurately estimates droplet sizes.
• Scattering angle selection and knowledge of droplet refractive index are important for accurate remote sensing of fog microphysics.