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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Main Authors: Wenhao Zhang, Hui Xu, Lili Zhang
Format: Article
Language:English
Published: MDPI AG 2019-05-01
Series:Remote Sensing
Subjects:
AHI
Online Access:https://www.mdpi.com/2072-4292/11/9/1108
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spelling doaj-fe4d0e4035664d89aaad27a80d5f7c4e2020-11-25T02:07:59ZengMDPI AGRemote Sensing2072-42922019-05-01119110810.3390/rs11091108rs11091108Assessment of Himawari-8 AHI Aerosol Optical Depth Over LandWenhao Zhang0Hui Xu1Lili Zhang2Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, ChinaEarth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20740, USAInstitute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, ChinaThis 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.https://www.mdpi.com/2072-4292/11/9/1108aerosol optical depthHimawari-8AHIAERONEassessment
collection DOAJ
language English
format Article
sources DOAJ
author Wenhao Zhang
Hui Xu
Lili Zhang
spellingShingle Wenhao Zhang
Hui Xu
Lili Zhang
Assessment of Himawari-8 AHI Aerosol Optical Depth Over Land
Remote Sensing
aerosol optical depth
Himawari-8
AHI
AERONE
assessment
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
series Remote Sensing
issn 2072-4292
publishDate 2019-05-01
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.
topic aerosol optical depth
Himawari-8
AHI
AERONE
assessment
url https://www.mdpi.com/2072-4292/11/9/1108
work_keys_str_mv AT wenhaozhang assessmentofhimawari8ahiaerosolopticaldepthoverland
AT huixu assessmentofhimawari8ahiaerosolopticaldepthoverland
AT lilizhang assessmentofhimawari8ahiaerosolopticaldepthoverland
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