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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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AMT | Articles | Volume 12, issue 12
Atmos. Meas. Tech., 12, 6319–6340, 2019
https://doi.org/10.5194/amt-12-6319-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue: TROPOMI on Sentinel-5 Precursor: first year in operation (AMT/ACP...

Atmos. Meas. Tech., 12, 6319–6340, 2019
https://doi.org/10.5194/amt-12-6319-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 02 Dec 2019

Research article | 02 Dec 2019

The role of aerosol layer height in quantifying aerosol absorption from ultraviolet satellite observations

Jiyunting Sun et al.

Data sets

OMI/Aura Near UV Aerosol Optical Depth and Single Scattering Albedo 1-orbit L2 Swath 13x24 km V003 O. O. Torres https://doi.org/10.5067/Aura/OMI/DATA2004

OMI/Aura Surface Reflectance Climatology L3 Global Gridded 0.5 degree x 0.5 degree V3 Q. Kleipool https://doi.org/10.5067/Aura/OMI/DATA3006

MODIS Atmosphere L2 Aerosol Product. NASA MODIS Adaptive Processing System R. Levy, C. Hsu, et al. https://doi.org/10.5067/MODIS/MOD04_L2.006

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Short summary
Single scattering albedo (SSA) is critical for reducing uncertainties in radiative forcing assessment. This paper presents two methods to retrieve SSA from satellite observations of the near-UV absorbing aerosol index (UVAI). The first is physically based radiative transfer simulations; the second is a statistically based machine learning algorithm. The result of the latter is encouraging. Both methods show that the ALH is necessary to quantitatively interpret aerosol absorption from UVAI.
Single scattering albedo (SSA) is critical for reducing uncertainties in radiative forcing...
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