Evaluation of MODIS, MISR, and VIIRS daily level-3 aerosol optical depth products over land

International audience This study presents a comprehensive evaluation of eight aerosol optical depth (AOD) products from the latest MODIS C6.1 DT, DB and DTB, MISR V23, and VIIRS V1 DB dataset against the Aerosol Robotic Network (AERONET) measurements on global scale during 2012 to 2019. The latest...

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Published in:Atmospheric Research
Main Authors: Chen, Qi-Xiang, Han, Xin-Lei, Gu, Yu, Yuan, Yuan, Jiang, Jonathan H., Yang, Xue-Bo, Liou, Kuo-Nan, Tan, He-Ping
Other Authors: Centre d'études spatiales de la biosphère (CESBIO), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Format: Article in Journal/Newspaper
Language:English
Published: HAL CCSD 2022
Subjects:
Online Access:https://insu.hal.science/insu-03668297
https://doi.org/10.1016/j.atmosres.2021.105810
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spelling ftmeteofrance:oai:HAL:insu-03668297v1 2024-09-15T17:35:15+00:00 Evaluation of MODIS, MISR, and VIIRS daily level-3 aerosol optical depth products over land Chen, Qi-Xiang Han, Xin-Lei Gu, Yu Yuan, Yuan Jiang, Jonathan H. Yang, Xue-Bo Liou, Kuo-Nan Tan, He-Ping Centre d'études spatiales de la biosphère (CESBIO) Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3) Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP) Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) 2022 https://insu.hal.science/insu-03668297 https://doi.org/10.1016/j.atmosres.2021.105810 en eng HAL CCSD Elsevier info:eu-repo/semantics/altIdentifier/doi/10.1016/j.atmosres.2021.105810 insu-03668297 https://insu.hal.science/insu-03668297 BIBCODE: 2022AtmRe.26505810C doi:10.1016/j.atmosres.2021.105810 ISSN: 0169-8095 Atmospheric Research https://insu.hal.science/insu-03668297 Atmospheric Research, 2022, 265, ⟨10.1016/j.atmosres.2021.105810⟩ MODIS MISR VIIRS AERONET Aerosol optical depth Evaluation [SDU]Sciences of the Universe [physics] info:eu-repo/semantics/article Journal articles 2022 ftmeteofrance https://doi.org/10.1016/j.atmosres.2021.105810 2024-06-25T00:10:21Z International audience This study presents a comprehensive evaluation of eight aerosol optical depth (AOD) products from the latest MODIS C6.1 DT, DB and DTB, MISR V23, and VIIRS V1 DB dataset against the Aerosol Robotic Network (AERONET) measurements on global scale during 2012 to 2019. The latest MODIS DB products are found to be superior over DT in most cases. MODIS DTB products generally have a better performance than either DT or DB. VIIRS shows the best overall performance on global and regional scale while MISR has a systematic underestimation in moderate and high AOD conditions. Median AOD bias shows distinct regional dependence with the biggest divergence between satellite AOD products appearing in Asia. All these AOD products tend to have better performance in high latitude region and poorer performance in the tropics likely due to the complex aerosol condition and common high cloud cover in the tropics. Time series stability evaluation shows a distinct temporal pattern of statistics, in which the observation number and median AOD bias tend to be high in summer while low in winter and correlation R has a reversing trend. Among these products, VIIRS V1 DB has the highest time series stability of bias. Influence of aerosol loading, particle size, land use, elevation, and precipitable water and temperature on AOD retrievals is broadly consistent between products. High aerosol loading, small particle size, bright surface, high altitude, and high precipitable water and temperature tend to decrease the retrieval accuracy, e.g. lower expected error (EE) within ratio and larger median bias. The latest AOD products need to be furthermore improved under extreme conditions like very fine aerosols, elevated terrain and high precipitable water and temperature. Article in Journal/Newspaper Aerosol Robotic Network Météo-France: HAL Atmospheric Research 265 105810
institution Open Polar
collection Météo-France: HAL
op_collection_id ftmeteofrance
language English
topic MODIS
MISR
VIIRS
AERONET
Aerosol optical depth
Evaluation
[SDU]Sciences of the Universe [physics]
spellingShingle MODIS
MISR
VIIRS
AERONET
Aerosol optical depth
Evaluation
[SDU]Sciences of the Universe [physics]
Chen, Qi-Xiang
Han, Xin-Lei
Gu, Yu
Yuan, Yuan
Jiang, Jonathan H.
Yang, Xue-Bo
Liou, Kuo-Nan
Tan, He-Ping
Evaluation of MODIS, MISR, and VIIRS daily level-3 aerosol optical depth products over land
topic_facet MODIS
MISR
VIIRS
AERONET
Aerosol optical depth
Evaluation
[SDU]Sciences of the Universe [physics]
description International audience This study presents a comprehensive evaluation of eight aerosol optical depth (AOD) products from the latest MODIS C6.1 DT, DB and DTB, MISR V23, and VIIRS V1 DB dataset against the Aerosol Robotic Network (AERONET) measurements on global scale during 2012 to 2019. The latest MODIS DB products are found to be superior over DT in most cases. MODIS DTB products generally have a better performance than either DT or DB. VIIRS shows the best overall performance on global and regional scale while MISR has a systematic underestimation in moderate and high AOD conditions. Median AOD bias shows distinct regional dependence with the biggest divergence between satellite AOD products appearing in Asia. All these AOD products tend to have better performance in high latitude region and poorer performance in the tropics likely due to the complex aerosol condition and common high cloud cover in the tropics. Time series stability evaluation shows a distinct temporal pattern of statistics, in which the observation number and median AOD bias tend to be high in summer while low in winter and correlation R has a reversing trend. Among these products, VIIRS V1 DB has the highest time series stability of bias. Influence of aerosol loading, particle size, land use, elevation, and precipitable water and temperature on AOD retrievals is broadly consistent between products. High aerosol loading, small particle size, bright surface, high altitude, and high precipitable water and temperature tend to decrease the retrieval accuracy, e.g. lower expected error (EE) within ratio and larger median bias. The latest AOD products need to be furthermore improved under extreme conditions like very fine aerosols, elevated terrain and high precipitable water and temperature.
author2 Centre d'études spatiales de la biosphère (CESBIO)
Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3)
Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP)
Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
format Article in Journal/Newspaper
author Chen, Qi-Xiang
Han, Xin-Lei
Gu, Yu
Yuan, Yuan
Jiang, Jonathan H.
Yang, Xue-Bo
Liou, Kuo-Nan
Tan, He-Ping
author_facet Chen, Qi-Xiang
Han, Xin-Lei
Gu, Yu
Yuan, Yuan
Jiang, Jonathan H.
Yang, Xue-Bo
Liou, Kuo-Nan
Tan, He-Ping
author_sort Chen, Qi-Xiang
title Evaluation of MODIS, MISR, and VIIRS daily level-3 aerosol optical depth products over land
title_short Evaluation of MODIS, MISR, and VIIRS daily level-3 aerosol optical depth products over land
title_full Evaluation of MODIS, MISR, and VIIRS daily level-3 aerosol optical depth products over land
title_fullStr Evaluation of MODIS, MISR, and VIIRS daily level-3 aerosol optical depth products over land
title_full_unstemmed Evaluation of MODIS, MISR, and VIIRS daily level-3 aerosol optical depth products over land
title_sort evaluation of modis, misr, and viirs daily level-3 aerosol optical depth products over land
publisher HAL CCSD
publishDate 2022
url https://insu.hal.science/insu-03668297
https://doi.org/10.1016/j.atmosres.2021.105810
genre Aerosol Robotic Network
genre_facet Aerosol Robotic Network
op_source ISSN: 0169-8095
Atmospheric Research
https://insu.hal.science/insu-03668297
Atmospheric Research, 2022, 265, ⟨10.1016/j.atmosres.2021.105810⟩
op_relation info:eu-repo/semantics/altIdentifier/doi/10.1016/j.atmosres.2021.105810
insu-03668297
https://insu.hal.science/insu-03668297
BIBCODE: 2022AtmRe.26505810C
doi:10.1016/j.atmosres.2021.105810
op_doi https://doi.org/10.1016/j.atmosres.2021.105810
container_title Atmospheric Research
container_volume 265
container_start_page 105810
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