Microphysical particle parameters from extinction and backscatter lidar data by inversion with regularization:...

Area of Science:

• Atmospheric Science
• Lidar Remote Sensing
• Aerosol Physics

Background:

• Accurate characterization of tropospheric particle size distributions is essential for understanding aerosol impacts on climate and air quality.
• Current methods often rely on assumptions about particle shape or require extensive datasets, limiting routine application.

Purpose of the Study:

• To develop and validate a robust method for retrieving physical parameters of tropospheric particle size distributions from multi-wavelength lidar data.
• To assess the accuracy and limitations of the proposed inversion algorithm for routine atmospheric profiling.

Main Methods:

• Utilized multi-wavelength lidar measurements (355-1064 nm for backscatter, 355 & 532 nm for extinction).
• Employed an inversion algorithm with generalized cross-validation for regularization.
• The method does not assume particle size distribution shape and accommodates up to 20% measurement errors.

Main Results:

• Successfully retrieved effective radius, volume, and surface-area concentrations with +/-50% accuracy.
• Determined the real part of the complex refractive index to +/-0.05 and the imaginary part to +/-50%.
• Demonstrated the necessity of at least two extinction wavelengths for accurate parameter retrieval.

Conclusions:

• The proposed inversion method provides a reliable approach for routine retrieval of key aerosol physical properties from lidar data.
• The method's ability to handle measurement errors and distributional shape assumptions enhances its practical applicability in atmospheric studies.
• While effective radius, volume, and surface-area concentrations are retrieved with reasonable accuracy, number concentrations may exhibit larger uncertainties.