Improvement on lidar data processing for stratospheric aerosol measurements.

Area of Science:

• Atmospheric Science
• Optical Remote Sensing
• Instrumental Physics

Background:

• Photomultiplier tubes (PMTs) are crucial for lidar detection.
• Signal-induced noise (SIN) from PMTs is a significant challenge in stratospheric aerosol lidar measurements.
• The delayed response of PMTs, characterized by a long tail (~200 microseconds), contributes to SIN.

Purpose of the Study:

• To simulate lidar signals affected by PMT-induced SIN.
• To quantify the impact of SIN on stratospheric aerosol lidar measurements.
• To develop practical methods for identifying, removing, and calibrating SIN in lidar data.

Main Methods:

• Characterization of the RCA 8852 PMT response to impulse-like light exposure.
• Computer simulation of lidar signals incorporating PMT response characteristics.
• Development and application of signal processing techniques for SIN identification and removal.
• Formulation of an improved lidar signal calibration method (matching method) accounting for SIN and background light.

Main Results:

• A long tail in the PMT response was identified, contributing to SIN.
• Computer simulations demonstrated that SIN can exceed the real signal strength at high altitudes.
• Proposed methods for SIN identification, removal, and calibration were validated using simulated and actual lidar data.

Conclusions:

• SIN from PMTs is a critical factor affecting stratospheric lidar data quality.
• The developed simulation and data processing methods effectively address PMT-induced noise.
• Improved calibration techniques incorporating SIN enhance the accuracy of stratospheric aerosol lidar measurements.