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    Multiple scattering in LiDAR measurements causes signal depolarization in water clouds. A new polarimetric model accurately predicts LiDAR signals and depolarization by considering photon scattering orders and instrument characteristics.

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    Area of Science:

    • Atmospheric optics
    • Remote sensing
    • Cloud physics

    Background:

    • Multiple scattering significantly impacts LiDAR measurements, particularly causing signal depolarization in water clouds.
    • Understanding these effects is crucial for accurate remote sensing of cloud properties.

    Purpose of the Study:

    • To develop a simplified polarimetric multiple scattering model for LiDAR.
    • To accurately simulate LiDAR signals and depolarization parameters in water clouds.

    Main Methods:

    • A polarimetric multiple scattering model using Poisson statistics for photon scattering order distribution.
    • Incorporation of aerosol properties and LiDAR characteristics (e.g., Field of View - FoV).
    • Comparison with Monte Carlo simulations for cumulus clouds and water fog.

    Main Results:

    • The model shows good agreement with Monte Carlo simulations for total LiDAR signal.
    • Accurate prediction of the depolarization parameter was achieved.
    • Validation performed for different cloud types and FoVs (1 mrad and 12 mrad).

    Conclusions:

    • The developed model provides a computationally efficient and accurate method for simulating multiple scattering effects in LiDAR.
    • This model aids in improving the interpretation of LiDAR data for cloud remote sensing.