Assessment of Himawari-8 AHI Aerosol Optical Depth Over Land
This study conducted the first comprehensive assessment of the aerosol optical depth (AOD) product retrieved from the observations by the Advanced Himawari Imager (AHI) onboard the Himawari-8 satellite. The AHI Level 3 AOD (Version 3.0) was evaluated using the collocated Aerosol Robotic Network (AER...
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ftdoajarticles:oai:doaj.org/article:fe4d0e4035664d89aaad27a80d5f7c4e 2023-05-15T13:06:31+02:00 Assessment of Himawari-8 AHI Aerosol Optical Depth Over Land Wenhao Zhang Hui Xu Lili Zhang 2019-05-01T00:00:00Z https://doi.org/10.3390/rs11091108 https://doaj.org/article/fe4d0e4035664d89aaad27a80d5f7c4e EN eng MDPI AG https://www.mdpi.com/2072-4292/11/9/1108 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs11091108 https://doaj.org/article/fe4d0e4035664d89aaad27a80d5f7c4e Remote Sensing, Vol 11, Iss 9, p 1108 (2019) aerosol optical depth Himawari-8 AHI AERONE assessment Science Q article 2019 ftdoajarticles https://doi.org/10.3390/rs11091108 2022-12-31T16:05:48Z This study conducted the first comprehensive assessment of the aerosol optical depth (AOD) product retrieved from the observations by the Advanced Himawari Imager (AHI) onboard the Himawari-8 satellite. The AHI Level 3 AOD (Version 3.0) was evaluated using the collocated Aerosol Robotic Network (AERONET) level 2.0 direct sun AOD measurements over the last three years (May 2016−December 2018) at 58 selected AERONET sites. A comprehensive comparison between AHI and AERONET AOD was carried out, which yielded a correlation coefficient (R) of 0.82, a slope of 0.69, and a root mean square error (RMSE) of 0.16. The results indicate a good agreement between AHI and AERONET AOD, while revealing that the AHI aerosol retrieval algorithm tends to underestimate the atmospheric aerosol load. In addition, the expected uncertainty of AHI Level 3 AOD (Version 3.0) is ± (0.1 + 0.3 × AOD). Furthermore, the performance of the AHI aerosol retrieval algorithm exhibits regional variation. The best performance is reported over East Asia (R 0.86), followed by Southeast Asia (R 0.79) and Australia (R 0.35). The monthly and seasonal comparisons between AHI and AERONET show that the best performance is found in summer (R 0.93), followed by autumn (R 0.84), winter (R 0.82), and spring (R 0.76). The worst performance was observed in March (R 0.75), while the best performance appeared in June (R 0.94). The variation in the annual mean AHI AOD on the scale of hours demonstrates that AHI can perform continuous (no less than ten hours) aerosol monitoring. Article in Journal/Newspaper Aerosol Robotic Network Directory of Open Access Journals: DOAJ Articles Remote Sensing 11 9 1108 |
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Open Polar |
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Directory of Open Access Journals: DOAJ Articles |
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English |
topic |
aerosol optical depth Himawari-8 AHI AERONE assessment Science Q |
spellingShingle |
aerosol optical depth Himawari-8 AHI AERONE assessment Science Q Wenhao Zhang Hui Xu Lili Zhang Assessment of Himawari-8 AHI Aerosol Optical Depth Over Land |
topic_facet |
aerosol optical depth Himawari-8 AHI AERONE assessment Science Q |
description |
This study conducted the first comprehensive assessment of the aerosol optical depth (AOD) product retrieved from the observations by the Advanced Himawari Imager (AHI) onboard the Himawari-8 satellite. The AHI Level 3 AOD (Version 3.0) was evaluated using the collocated Aerosol Robotic Network (AERONET) level 2.0 direct sun AOD measurements over the last three years (May 2016−December 2018) at 58 selected AERONET sites. A comprehensive comparison between AHI and AERONET AOD was carried out, which yielded a correlation coefficient (R) of 0.82, a slope of 0.69, and a root mean square error (RMSE) of 0.16. The results indicate a good agreement between AHI and AERONET AOD, while revealing that the AHI aerosol retrieval algorithm tends to underestimate the atmospheric aerosol load. In addition, the expected uncertainty of AHI Level 3 AOD (Version 3.0) is ± (0.1 + 0.3 × AOD). Furthermore, the performance of the AHI aerosol retrieval algorithm exhibits regional variation. The best performance is reported over East Asia (R 0.86), followed by Southeast Asia (R 0.79) and Australia (R 0.35). The monthly and seasonal comparisons between AHI and AERONET show that the best performance is found in summer (R 0.93), followed by autumn (R 0.84), winter (R 0.82), and spring (R 0.76). The worst performance was observed in March (R 0.75), while the best performance appeared in June (R 0.94). The variation in the annual mean AHI AOD on the scale of hours demonstrates that AHI can perform continuous (no less than ten hours) aerosol monitoring. |
format |
Article in Journal/Newspaper |
author |
Wenhao Zhang Hui Xu Lili Zhang |
author_facet |
Wenhao Zhang Hui Xu Lili Zhang |
author_sort |
Wenhao Zhang |
title |
Assessment of Himawari-8 AHI Aerosol Optical Depth Over Land |
title_short |
Assessment of Himawari-8 AHI Aerosol Optical Depth Over Land |
title_full |
Assessment of Himawari-8 AHI Aerosol Optical Depth Over Land |
title_fullStr |
Assessment of Himawari-8 AHI Aerosol Optical Depth Over Land |
title_full_unstemmed |
Assessment of Himawari-8 AHI Aerosol Optical Depth Over Land |
title_sort |
assessment of himawari-8 ahi aerosol optical depth over land |
publisher |
MDPI AG |
publishDate |
2019 |
url |
https://doi.org/10.3390/rs11091108 https://doaj.org/article/fe4d0e4035664d89aaad27a80d5f7c4e |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_source |
Remote Sensing, Vol 11, Iss 9, p 1108 (2019) |
op_relation |
https://www.mdpi.com/2072-4292/11/9/1108 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs11091108 https://doaj.org/article/fe4d0e4035664d89aaad27a80d5f7c4e |
op_doi |
https://doi.org/10.3390/rs11091108 |
container_title |
Remote Sensing |
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11 |
container_issue |
9 |
container_start_page |
1108 |
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