Study on Influencing Factors of the Information Content of Satellite Remote-Sensing Aerosol Vertical Profiles Using Oxygen A-Band

Aerosol vertical distribution is decisive and hard to be constrained. It is of great significance for the study of atmospheric climate and environment. Oxygen absorption A-bands (755-775 nm) provide a unique opportunity to acquire vertical aerosol profiles from satellites over a large spatial coverage. To investigate the ability of O-2 A-bands in retrieving aerosol vertical distribution, the dependence of retrieval on satellite observation geometry, spectral resolution, signal-to-noise ratio (SNR), size distribution, and a priori knowledge is quantified using information content theory. This work uses the radiative transfer model UNL to simulate four aerosol modes and the instrument noise model. The simulations show that a small scattering angle leads to an increase in the total amount of observed aerosol profile information, with the degrees freedom of signal (DFS) of a single band increasing from 0.4 to 0.85 at high spectral resolution (0.01 nm). The total DFS value of O-2 A-bands varies accordingly between 1.2-2.3 to 3.8-5.1 when the spectral resolution increases from 1 nm to 0.01 nm. The spectral resolution has a greater impact on DFS value than the impact from SNR (an improvement of roughly 41-53% resulted from the change in spectral resolution and the SNR led to 13-18%). The retrieval is more sensitive to aerosols with a coarse-dominated mode. The improvement in spectral resolution on information acquisition is demonstrated using the DFS and the posterior error at various previous errors and resolutions.

Automated summary

The distribution of aerosols in the atmosphere is critical and difficult to measure accurately. The use of oxygen absorption A-bands offers a unique opportunity to retrieve vertical aerosol profiles from satellite observations. In this study, the impact of various factors on aerosol retrieval, such as satellite observation geometry, spectral resolution, signal-to-noise ratio, particle size distribution, and prior knowledge, is quantified using information content theory. The results show that smaller scattering angles and higher spectral resolution result in increased information content, with the spectral resolution having a greater impact than the signal-to-noise ratio. Coarse-dominated aerosols are more sensitive to retrieval. The improvement in spectral resolution is demonstrated using information content metrics and error analysis.