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...
Published in: | Atmospheric Research |
---|---|
Main Authors: | , , , , , , , |
Other Authors: | , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
HAL CCSD
2022
|
Subjects: | |
Online Access: | https://hal-insu.archives-ouvertes.fr/insu-03668297 https://doi.org/10.1016/j.atmosres.2021.105810 |
id |
ftunivnantes:oai:HAL:insu-03668297v1 |
---|---|
record_format |
openpolar |
spelling |
ftunivnantes:oai:HAL:insu-03668297v1 2023-05-15T13:06:37+02:00 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 Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP) Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-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 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://hal-insu.archives-ouvertes.fr/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://hal-insu.archives-ouvertes.fr/insu-03668297 BIBCODE: 2022AtmRe.26505810C doi:10.1016/j.atmosres.2021.105810 ISSN: 0169-8095 Atmospheric Research https://hal-insu.archives-ouvertes.fr/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 ftunivnantes https://doi.org/10.1016/j.atmosres.2021.105810 2023-03-08T01:46:07Z 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 Université de Nantes: HAL-UNIV-NANTES Atmospheric Research 265 105810 |
institution |
Open Polar |
collection |
Université de Nantes: HAL-UNIV-NANTES |
op_collection_id |
ftunivnantes |
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 Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP) Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-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 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://hal-insu.archives-ouvertes.fr/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://hal-insu.archives-ouvertes.fr/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://hal-insu.archives-ouvertes.fr/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 |
_version_ |
1766013698631008256 |