Aerosol models from the AERONET data base. Application to surface reflectance validation
International audience 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...
Published in: | Atmospheric Measurement Techniques |
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Online Access: | https://uca.hal.science/hal-03471295 https://uca.hal.science/hal-03471295/document https://uca.hal.science/hal-03471295/file/amt-15-1123-2022.pdf https://doi.org/10.5194/amt-15-1123-2022 |
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ftinsu:oai:HAL:hal-03471295v1 2024-04-28T07:53:24+00:00 Aerosol models from the AERONET data base. Application to surface reflectance validation Roger, Jean-Claude Vermote, Eric Skakun, Sergii Murphy, Emilie Dubovik, Oleg Kalecinski, Natacha Korgo, Bruno Holben, Brent 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 d’Optique Atmosphérique - UMR 8518 (LOA) Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lille-Centre National de la Recherche Scientifique (CNRS) University of Ouagadougou Ouagadougou, Burkina Faso 2022-03 https://uca.hal.science/hal-03471295 https://uca.hal.science/hal-03471295/document https://uca.hal.science/hal-03471295/file/amt-15-1123-2022.pdf https://doi.org/10.5194/amt-15-1123-2022 en eng HAL CCSD European Geosciences Union info:eu-repo/semantics/altIdentifier/doi/10.5194/amt-15-1123-2022 hal-03471295 https://uca.hal.science/hal-03471295 https://uca.hal.science/hal-03471295/document https://uca.hal.science/hal-03471295/file/amt-15-1123-2022.pdf doi:10.5194/amt-15-1123-2022 http://creativecommons.org/licenses/by/ info:eu-repo/semantics/OpenAccess ISSN: 1867-1381 EISSN: 1867-8548 Atmospheric Measurement Techniques https://uca.hal.science/hal-03471295 Atmospheric Measurement Techniques, 2022, 15 (5), pp.1123-1144. ⟨10.5194/amt-15-1123-2022⟩ Aerosol model AERONET [PHYS]Physics [physics] [SDE]Environmental Sciences info:eu-repo/semantics/article Journal articles 2022 ftinsu https://doi.org/10.5194/amt-15-1123-2022 2024-04-05T00:26:21Z International audience 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. Article in Journal/Newspaper Aerosol Robotic Network Institut national des sciences de l'Univers: HAL-INSU Atmospheric Measurement Techniques 15 5 1123 1144 |
institution |
Open Polar |
collection |
Institut national des sciences de l'Univers: HAL-INSU |
op_collection_id |
ftinsu |
language |
English |
topic |
Aerosol model AERONET [PHYS]Physics [physics] [SDE]Environmental Sciences |
spellingShingle |
Aerosol model AERONET [PHYS]Physics [physics] [SDE]Environmental Sciences Roger, Jean-Claude Vermote, Eric Skakun, Sergii Murphy, Emilie Dubovik, Oleg Kalecinski, Natacha Korgo, Bruno Holben, Brent Aerosol models from the AERONET data base. Application to surface reflectance validation |
topic_facet |
Aerosol model AERONET [PHYS]Physics [physics] [SDE]Environmental Sciences |
description |
International audience 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. |
author2 |
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 d’Optique Atmosphérique - UMR 8518 (LOA) Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lille-Centre National de la Recherche Scientifique (CNRS) University of Ouagadougou Ouagadougou, Burkina Faso |
format |
Article in Journal/Newspaper |
author |
Roger, Jean-Claude Vermote, Eric Skakun, Sergii Murphy, Emilie Dubovik, Oleg Kalecinski, Natacha Korgo, Bruno Holben, Brent |
author_facet |
Roger, Jean-Claude Vermote, Eric Skakun, Sergii Murphy, Emilie Dubovik, Oleg Kalecinski, Natacha Korgo, Bruno Holben, Brent |
author_sort |
Roger, Jean-Claude |
title |
Aerosol models from the AERONET data base. Application to surface reflectance validation |
title_short |
Aerosol models from the AERONET data base. Application to surface reflectance validation |
title_full |
Aerosol models from the AERONET data base. Application to surface reflectance validation |
title_fullStr |
Aerosol models from the AERONET data base. Application to surface reflectance validation |
title_full_unstemmed |
Aerosol models from the AERONET data base. Application to surface reflectance validation |
title_sort |
aerosol models from the aeronet data base. application to surface reflectance validation |
publisher |
HAL CCSD |
publishDate |
2022 |
url |
https://uca.hal.science/hal-03471295 https://uca.hal.science/hal-03471295/document https://uca.hal.science/hal-03471295/file/amt-15-1123-2022.pdf https://doi.org/10.5194/amt-15-1123-2022 |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_source |
ISSN: 1867-1381 EISSN: 1867-8548 Atmospheric Measurement Techniques https://uca.hal.science/hal-03471295 Atmospheric Measurement Techniques, 2022, 15 (5), pp.1123-1144. ⟨10.5194/amt-15-1123-2022⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.5194/amt-15-1123-2022 hal-03471295 https://uca.hal.science/hal-03471295 https://uca.hal.science/hal-03471295/document https://uca.hal.science/hal-03471295/file/amt-15-1123-2022.pdf doi:10.5194/amt-15-1123-2022 |
op_rights |
http://creativecommons.org/licenses/by/ info:eu-repo/semantics/OpenAccess |
op_doi |
https://doi.org/10.5194/amt-15-1123-2022 |
container_title |
Atmospheric Measurement Techniques |
container_volume |
15 |
container_issue |
5 |
container_start_page |
1123 |
op_container_end_page |
1144 |
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