CO(2) lidar backscatter profiles over Hawaii during fall 1988

Area of Science:

• Atmospheric Science
• Remote Sensing
• Lidar Technology

Background:

• Doppler lidar measurements provide crucial data on atmospheric aerosols and clouds.
• Understanding backscatter variations is essential for accurate atmospheric profiling.
• Previous analyses were limited by biases due to data dropouts.

Purpose of the Study:

• To analyze aerosol and cloud backscatter data using a novel technique to reduce dropout-related biases.
• To characterize typical backscatter cross sections and identify episodic events.
• To discuss the implications of these findings for the Laser Atmospheric Wind Sounder (LAWS) satellite sensor.

Main Methods:

• Utilized 24-day Doppler lidar data collected in fall 1988 at a 10.59-microm wavelength.
• Applied a new data analysis technique to mitigate biases caused by data dropouts.
• Quantified backscatter cross sections and identified contributing aerosol types.

Main Results:

• Observed significantly lower typical backscatter cross sections compared to continental U.S. averages.
• Documented episodic backscatter enhancements attributed to cirrus clouds and mineral dust.
• The new technique successfully reduced biases in the backscatter data.

Conclusions:

• The study provides valuable insights into aerosol and cloud backscatter characteristics.
• Findings highlight the importance of accounting for data dropouts in lidar analysis.
• The results have direct implications for the design and capabilities of future satellite-based wind profiling systems like LAWS.