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Polarization Calibration Using Solar Radiation Background Signal Scattered from Dense Cirrus Clouds in the Visible and Ultraviolet Wavelength Regimes

Authors :
Zhaoyan Liu
Yongxiang Hu
Pengwang Zhai
Shan Zeng
Mark Vaughan
Sharon Rodier
Xiaomei Lu
Publication Year :
2023
Publisher :
United States: NASA Center for Aerospace Information (CASI), 2023.

Abstract

In this presentation we describe the application of a previously developed technique that is now being used to correct the daytime polarization calibration of the CALIPSO lidar. The technique leverages the fact that the solar radiation background signals from dense cirrus clouds are largely unpolarized due to the internal multiple reflections within the non-spherical ice particles and the multiple scattering that occurs among these particles. Therefore, the ratio of polarization components of the cirrus background signals provides a good estimate for the polarization gain ratio (PGR) of the lidar. Using airborne backscatter lidar measurements, this technique was demonstrated to work well in the infrared regime. However, in the visible and ultraviolet regime, the molecular contribution is too large to be ignored, and thus corrections must be applied to account for the highly polarizing characteristics of the molecular scattering. Ignoring molecular scattering contributions can cause PGR errors of 2-3% at 532 nm, where the CALIPSO lidar makes its depolarization measurement. Because of the wavelength dependence of -4 of the molecular scattering, the PGR error can be even larger at the 355 nm wavelength that will be used by ESA’s EarthCARE lidar. To correct the molecular scattering contributions to the lidar received solar background signal, a look-up table has been created using a polarization-sensitive radiative transfer model. This presentation describes the theory and implementation of the molecular scattering correction.

Subjects

Subjects :
Geosciences (General)

Details

Language :
English
Database :
NASA Technical Reports
Notes :
281945.02.03.12.73
Publication Type :
Report
Accession number :
edsnas.20230002772
Document Type :
Report