Iterative method to determine an averaged backscatter-to-extinction ratio in cirrus clouds.

Area of Science:

• Atmospheric Science
• Cloud Physics
• Remote Sensing

Background:

• Cirrus clouds play a crucial role in Earth's radiative balance.
• Accurate retrieval of cloud optical properties, such as extinction coefficient and backscatter-to-extinction ratio, is essential for climate modeling.
• Lidar (Light Detection and Ranging) is a key remote sensing technique for profiling atmospheric properties.

Purpose of the Study:

• To develop and validate an iterative method for simultaneously determining the backscatter-to-extinction ratio and extinction coefficient in cirrus clouds.
• To establish the signal-to-noise ratio requirements for achieving a specific error tolerance in the retrieved parameters.

Main Methods:

• The proposed method utilizes an iterative approach based on Klett's inversion algorithm.
• The inversion process is constrained by the total optical depth of the cirrus cloud.
• The method's performance is evaluated using simulated lidar signals and an experimental lidar dataset.

Main Results:

• The iterative method successfully determines both the backscatter-to-extinction ratio and extinction coefficient simultaneously.
• A signal-to-noise ratio greater than 3 at cloud top is identified as a requirement for achieving an error below 20% in the backscatter-to-extinction ratio.
• Validation with simulated and experimental data demonstrates the method's applicability.

Conclusions:

• The developed iterative method provides a robust approach for retrieving key cirrus cloud optical properties from lidar measurements.
• The findings highlight the importance of signal quality for accurate remote sensing of cloud parameters.
• This method can enhance the understanding of cirrus cloud radiative effects and improve climate models.