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Water Cloud Detection with Circular Polarization Lidar: A Semianalytic Monte Carlo Simulation Approach

Wiqas Ahmad, Kai Zhang, Yicheng Tong, Da Xiao, Lingyun Wu, Dong Liu

2022Sensors10 citationsDOIOpen Access PDF

Abstract

This work presents polarization property studies of water clouds using a circular polarization lidar through a simulation approach. The simulation approach is based on a polarized, semianalytic Monte Carlo method under multiple-scattering conditions and considers three types of water clouds (namely homogeneous, inhomogeneous and partially inhomogeneous). The simulation results indicate that the layer-integrated circular depolarization ratios show similar variation trends as those of layer-integrated linear depolarization ratios. The Mishchenko-Hovenier relationship is validated to correlate the simulated layer-integrated circular and linear depolarization ratios. In addition, the cloud droplet effective radius, extinction coefficient, lidar field-of-view (FOV) and height of the cloud bottom are all found to affect the layer-integrated depolarization ratio. The current work theoretically indicates that a circular polarization lidar can efficiently perform measurements of water clouds, enjoying the advantage of higher sensitivity compared to a traditional linear polarization lidar. Hence, it should be of interest to researchers in fields of polarization lidar applications.

Topics & Concepts

Monte Carlo methodLidarCloud computingPolarization (electrochemistry)Remote sensingCircular polarizationComputer scienceEnvironmental sciencePhysicsOpticsGeologyStatisticsMathematicsChemistryOperating systemMicrostripPhysical chemistryAtmospheric aerosols and cloudsMeteorological Phenomena and SimulationsPrecipitation Measurement and Analysis