Aerosol models from the AERONET data base. Application to surface reflectance validation

Abstract. Aerosols play a critical role in radiative transfer within the atmosphere, and they have a significant impact on climate change. As part of the validation of atmospheric correction of remote sensing data affected by the atmosphere, it is critical to utilize appropriate aerosol models as ae...

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Bibliographic Details
Main Authors: Roger, Jean-Claude, Vermote, Eric, Skakun, Sergii, Murphy, Emilie, Dubovik, Oleg, Kalecinski, Natacha, Korgo, Bruno, Justice, Christopher, Holben, Brent
Other Authors: Department of Geographical Sciences College Park, University of Maryland College Park, University of Maryland System-University of Maryland System, NASA Goddard Space Flight Center (GSFC), Laboratoire de Météorologie Physique (LaMP), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)
Format: Report
Language:English
Published: HAL CCSD 2021
Subjects:
geo
Online Access:https://doi.org/10.5194/amt-2021-322
https://hal.uca.fr/hal-03471295
Description
Summary:Abstract. Aerosols play a critical role in radiative transfer within the atmosphere, and they have a significant impact on climate change. As part of the validation of atmospheric correction of remote sensing data affected by the atmosphere, it is critical to utilize appropriate aerosol models as aerosols are a main source of error. In this paper, we propose and demonstrate a framework for building and identifying an aerosol model. For this purpose, we define the aerosol model by recalculating the aerosol microphysical properties (Cvf, Cvc, %Cvf, %Cvc, rvf, rvc, σr, σc, nr440, nr650, nr850, nr1020, ni440, ni650, ni850, ni1020, %Sph) based on the optical thickness at 440 nm τ440 and the Ångström coefficient α440–870 obtained from numerous AERosol RObotic NETwork (AERONET) sites. Using aerosol microphysical properties provided by the AERONET dataset, we were able to evaluate our own retrieved microphysical properties. The associated uncertainties are up to 23 %, except for the challenging, imaginary part of the refractive index ni (about 38 %). Uncertainties of the retrieved aerosol microphysical properties were incorporated in the framework for validating surface reflectance derived from space-borne Earth observation sensors. Results indicate that the impact of aerosol microphysical properties varies 3.5 × 10−5 to 10−3 in reflectance units. Finally, the uncertainties of the microphysical properties yielded an overall uncertainty of approximately of 1 to 3 % of the retrieved surface reflectance in the MODIS red spectral band (620–670 nm), which corresponds to the specification used for atmospheric correction.