Cloud Aerosol Transport System (CATS) 1064 nm Calibration and Validation

Area of Science:

• Atmospheric Science
• Remote Sensing
• Lidar Technology

Background:

• The Cloud-Aerosol Transport System (CATS) lidar, aboard the International Space Station (ISS), provided atmospheric backscatter profiles from 2015 to 2017.
• CATS offered a high signal-to-noise ratio at 1064 nm, surpassing previous space-based lidars and enabling direct calibration.
• Accurate calibration is crucial for interpreting atmospheric data from space-borne instruments.

Purpose of the Study:

• To demonstrate the feasibility of directly calibrating the CATS 1064 nm lidar channel using atmospheric data.
• To establish reliable calibration methods for both nighttime and daytime CATS measurements.
• To validate CATS data through comparisons with other lidar systems and models.

Main Methods:

• Nighttime calibration involved scaling CATS data to a model of expected atmospheric backscatter between 22-26 km AMSL, using MERRA-2 and CALIOP data.
• Daytime calibration utilized comparisons with nighttime measurements of attenuated total backscatter (iATB) from opaque cirrus clouds.
• Validation included coincident comparisons with the Cloud Physics Lidar (CPL) and ground-based PollyXT lidars, as well as CALIOP.

Main Results:

• Nighttime CATS 1064 nm attenuated total backscatter (ATB) uncertainties were estimated at ~9%, with median relative uncertainty within layers at 7%.
• Daytime CATS 1064 nm ATB exhibited a median relative uncertainty of 21%, with calibration technique uncertainties estimated at 16-18%.
• CATS data showed good agreement with CPL, PollyXT, and CALIOP across various atmospheric conditions and calibration methods.

Conclusions:

• The study successfully demonstrated direct atmospheric calibration of the CATS 1064 nm channel, proving the atmospheric normalization technique's viability.
• CATS Version 3-00 data provide reliable atmospheric backscatter profiles, with quantified uncertainties for both nighttime and daytime measurements.
• The validated CATS data contribute valuable insights into atmospheric composition and dynamics for climate research.