Impact of the Dust Aerosol Model on the VIIRS Aerosol Optical Depth (AOD) Product across China

The Visible Infrared Imaging Radiometer Suite (VIIRS) has been observing aerosol optical depth (AOD), which is a critical parameter in air pollution and climate change, for more than 7 years since 2012. Due to limited and uneven distribution of the Aerosol Robotic Network (AERONET) station in China,...

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Published in:Remote Sensing
Main Authors: Yang Wang, Liangfu Chen, Jinyuan Xin, Xinhui Wang
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2020
Subjects:
AOD
Online Access:https://doi.org/10.3390/rs12060991
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spelling ftmdpi:oai:mdpi.com:/2072-4292/12/6/991/ 2023-08-20T03:59:13+02:00 Impact of the Dust Aerosol Model on the VIIRS Aerosol Optical Depth (AOD) Product across China Yang Wang Liangfu Chen Jinyuan Xin Xinhui Wang agris 2020-03-19 application/pdf https://doi.org/10.3390/rs12060991 EN eng Multidisciplinary Digital Publishing Institute Atmospheric Remote Sensing https://dx.doi.org/10.3390/rs12060991 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 12; Issue 6; Pages: 991 AOD VIIRS validation dust aerosol model CARE-China Ångström exponent Text 2020 ftmdpi https://doi.org/10.3390/rs12060991 2023-07-31T23:15:33Z The Visible Infrared Imaging Radiometer Suite (VIIRS) has been observing aerosol optical depth (AOD), which is a critical parameter in air pollution and climate change, for more than 7 years since 2012. Due to limited and uneven distribution of the Aerosol Robotic Network (AERONET) station in China, the independent data from the Campaign on Atmospheric Aerosol Research Network of China (CARE-China) was used to evaluate the National Oceanic and Atmospheric Administration (NOAA) VIIRS AOD products in six typical sites and analyze the influence of the aerosol model selection process in five subregions, particularly for dust. Compared with ground-based observations, the performance of all retrievals (except the Shapotou (SPT) site) is similar to other previous studies on a global scale. However, the results illustrate that the AOD retrievals with the dust model showed poor consistency with a regression equation as y = 0.312x + 0.086, while the retrievals obtained from the other models perform much better with a regression equation as y = 0.783x + 0.119. The poor AOD retrieval with the dust model was also verified by a comparison with the Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol product. The results show they have a lower correlation coefficient (R) and a higher mean relative error (MRE) when the aerosol model used in the retrieval is identified as dust. According to the Ultraviolet Aerosol Index (UVAI), the frequency of dust type over southern China is inconsistent with the actual atmospheric condition. In addition, a comparison of ground-based Ångström exponent (α) values yields an unexpected result that the dust model percentage exceed 40% when α < 1.0, and the mean α shows a high value of ~0.75. Meanwhile, the α peak value (~1.1) of the “dust” model determined by a satellite retravel algorithm indicate there is some problem in the dust model selection process. This mismatching of the aerosol model may partly explain the low accuracy at the SPT and the systemic biases in regional and global ... Text Aerosol Robotic Network MDPI Open Access Publishing Remote Sensing 12 6 991
institution Open Polar
collection MDPI Open Access Publishing
op_collection_id ftmdpi
language English
topic AOD
VIIRS
validation
dust aerosol model
CARE-China
Ångström exponent
spellingShingle AOD
VIIRS
validation
dust aerosol model
CARE-China
Ångström exponent
Yang Wang
Liangfu Chen
Jinyuan Xin
Xinhui Wang
Impact of the Dust Aerosol Model on the VIIRS Aerosol Optical Depth (AOD) Product across China
topic_facet AOD
VIIRS
validation
dust aerosol model
CARE-China
Ångström exponent
description The Visible Infrared Imaging Radiometer Suite (VIIRS) has been observing aerosol optical depth (AOD), which is a critical parameter in air pollution and climate change, for more than 7 years since 2012. Due to limited and uneven distribution of the Aerosol Robotic Network (AERONET) station in China, the independent data from the Campaign on Atmospheric Aerosol Research Network of China (CARE-China) was used to evaluate the National Oceanic and Atmospheric Administration (NOAA) VIIRS AOD products in six typical sites and analyze the influence of the aerosol model selection process in five subregions, particularly for dust. Compared with ground-based observations, the performance of all retrievals (except the Shapotou (SPT) site) is similar to other previous studies on a global scale. However, the results illustrate that the AOD retrievals with the dust model showed poor consistency with a regression equation as y = 0.312x + 0.086, while the retrievals obtained from the other models perform much better with a regression equation as y = 0.783x + 0.119. The poor AOD retrieval with the dust model was also verified by a comparison with the Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol product. The results show they have a lower correlation coefficient (R) and a higher mean relative error (MRE) when the aerosol model used in the retrieval is identified as dust. According to the Ultraviolet Aerosol Index (UVAI), the frequency of dust type over southern China is inconsistent with the actual atmospheric condition. In addition, a comparison of ground-based Ångström exponent (α) values yields an unexpected result that the dust model percentage exceed 40% when α < 1.0, and the mean α shows a high value of ~0.75. Meanwhile, the α peak value (~1.1) of the “dust” model determined by a satellite retravel algorithm indicate there is some problem in the dust model selection process. This mismatching of the aerosol model may partly explain the low accuracy at the SPT and the systemic biases in regional and global ...
format Text
author Yang Wang
Liangfu Chen
Jinyuan Xin
Xinhui Wang
author_facet Yang Wang
Liangfu Chen
Jinyuan Xin
Xinhui Wang
author_sort Yang Wang
title Impact of the Dust Aerosol Model on the VIIRS Aerosol Optical Depth (AOD) Product across China
title_short Impact of the Dust Aerosol Model on the VIIRS Aerosol Optical Depth (AOD) Product across China
title_full Impact of the Dust Aerosol Model on the VIIRS Aerosol Optical Depth (AOD) Product across China
title_fullStr Impact of the Dust Aerosol Model on the VIIRS Aerosol Optical Depth (AOD) Product across China
title_full_unstemmed Impact of the Dust Aerosol Model on the VIIRS Aerosol Optical Depth (AOD) Product across China
title_sort impact of the dust aerosol model on the viirs aerosol optical depth (aod) product across china
publisher Multidisciplinary Digital Publishing Institute
publishDate 2020
url https://doi.org/10.3390/rs12060991
op_coverage agris
genre Aerosol Robotic Network
genre_facet Aerosol Robotic Network
op_source Remote Sensing; Volume 12; Issue 6; Pages: 991
op_relation Atmospheric Remote Sensing
https://dx.doi.org/10.3390/rs12060991
op_rights https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.3390/rs12060991
container_title Remote Sensing
container_volume 12
container_issue 6
container_start_page 991
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