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Simulated polarization diversity lidar returns from water and precipitating mixed phase clouds
Applied Optics
|August 21, 2010
Summary
Polarization lidar measurements are simulated using a cloud model, revealing how cloud properties like water content and ice crystals affect depolarization. This helps interpret lidar data for better cloud characterization.
Area of Science:
- Atmospheric Science
- Cloud Physics
- Remote Sensing
Background:
- Polarization lidar is a key tool for remote sensing of clouds.
- Understanding cloud microphysics is crucial for climate modeling.
- Previous studies have not fully explored the link between microphysics and lidar depolarization.
Purpose of the Study:
- To assess the dependence of polarization lidar returns on microphysical and thermodynamic variables.
- To simulate the growth of water and mixed-phase clouds and their impact on lidar signals.
- To investigate the influence of ice crystals on lidar depolarization in mixed-phase clouds.
Main Methods:
- Utilized a cloud model to simulate cloud evolution.
- Applied Mie theory to convert cloud properties into scattering and attenuation coefficients.
- Incorporated diffraction theory for multiple scattering corrections.
- Computed lidar depolarization from single and double scattering contributions.
Main Results:
- Lidar depolarization increases with lidar field of view and distance to cloud in water clouds.
- Depolarization is a function of cloud liquid water content, influenced by temperature.
- Ice crystals modulate liquid water content, affecting depolarization based on updraft velocity, temperature, and crystal properties.
- Minimum depolarization at cloud base increases with ice content, while peak depolarization decreases.
Conclusions:
- The modeling approach accurately simulates polarization lidar returns.
- This method provides valuable insights into cloud microphysical properties derived from lidar data.
- It serves as a valuable supplement to direct cloud measurements.
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