Evaluation of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) Aerosol Algorithm for Himawari-8 Data

Himawari-8, operated by the Japan Meteorological Agency (JMA), is a new generation geostationary satellite that provides remote sensing data to retrieve atmospheric aerosol optical depth (AOD) at high spatial (1 km) and high temporal (10 min) resolutions. The Geostationary- National Aeronautics and...

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Published in:Remote Sensing
Main Authors: Lu She, Hankui Zhang, Weile Wang, Yujie Wang, Yun Shi
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2019
Subjects:
Online Access:https://doi.org/10.3390/rs11232771
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author Lu She
Hankui Zhang
Weile Wang
Yujie Wang
Yun Shi
author_facet Lu She
Hankui Zhang
Weile Wang
Yujie Wang
Yun Shi
author_sort Lu She
collection MDPI Open Access Publishing
container_issue 23
container_start_page 2771
container_title Remote Sensing
container_volume 11
description Himawari-8, operated by the Japan Meteorological Agency (JMA), is a new generation geostationary satellite that provides remote sensing data to retrieve atmospheric aerosol optical depth (AOD) at high spatial (1 km) and high temporal (10 min) resolutions. The Geostationary- National Aeronautics and Space Administration (NASA) Earth exchange (GeoNEX) project recently adapted the multiangle implementation of atmospheric correction (MAIAC) algorithm, originally developed for joint retrieval of AOD and surface anisotropic reflectance with the moderate resolution imaging spectroradiometer (MODIS) data, to generate Earth monitoring products from the latest geostationary satellites including Himawari-8. This study evaluated the GeoNEX Himawari-8 ~1 km MAIAC AOD retrieved over all the aerosol robotic network (AERONET) sites between 6°N–30°N and 91°E–127°E. The corresponding JMA Himawari-8 AOD products were also evaluated for comparison. We only used cloud-free and the best quality satellite AOD retrievals and compiled a total of 16,532 MAIAC-AERONET and 21,737 JMA-AERONET contemporaneous pairs of AOD values for 2017. Statistical analyses showed that both MAIAC and JMA data are highly correlated with AERONET AOD, with the correlation coefficient (R) of ~0.77, and the root mean squared error (RMSE) of ~0.16. The absolute bias of MAIAC AOD (0.02 overestimation) appears smaller than that of the JMA AOD (0.05 underestimation). In comparison with the JMA data, the time series of MAIAC AOD were more consistent with AERONET AOD values and better capture the diurnal variations of the latter. The dependence of MAIAC AOD bias on scattering angles is also discussed.
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spelling ftmdpi:oai:mdpi.com:/2072-4292/11/23/2771/ 2025-01-16T18:38:33+00:00 Evaluation of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) Aerosol Algorithm for Himawari-8 Data Lu She Hankui Zhang Weile Wang Yujie Wang Yun Shi agris 2019-11-25 application/pdf https://doi.org/10.3390/rs11232771 EN eng Multidisciplinary Digital Publishing Institute https://dx.doi.org/10.3390/rs11232771 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 11; Issue 23; Pages: 2771 GeoNEX aerosol optical depth (AOD) MAIAC validation AERONET Text 2019 ftmdpi https://doi.org/10.3390/rs11232771 2023-07-31T22:49:42Z Himawari-8, operated by the Japan Meteorological Agency (JMA), is a new generation geostationary satellite that provides remote sensing data to retrieve atmospheric aerosol optical depth (AOD) at high spatial (1 km) and high temporal (10 min) resolutions. The Geostationary- National Aeronautics and Space Administration (NASA) Earth exchange (GeoNEX) project recently adapted the multiangle implementation of atmospheric correction (MAIAC) algorithm, originally developed for joint retrieval of AOD and surface anisotropic reflectance with the moderate resolution imaging spectroradiometer (MODIS) data, to generate Earth monitoring products from the latest geostationary satellites including Himawari-8. This study evaluated the GeoNEX Himawari-8 ~1 km MAIAC AOD retrieved over all the aerosol robotic network (AERONET) sites between 6°N–30°N and 91°E–127°E. The corresponding JMA Himawari-8 AOD products were also evaluated for comparison. We only used cloud-free and the best quality satellite AOD retrievals and compiled a total of 16,532 MAIAC-AERONET and 21,737 JMA-AERONET contemporaneous pairs of AOD values for 2017. Statistical analyses showed that both MAIAC and JMA data are highly correlated with AERONET AOD, with the correlation coefficient (R) of ~0.77, and the root mean squared error (RMSE) of ~0.16. The absolute bias of MAIAC AOD (0.02 overestimation) appears smaller than that of the JMA AOD (0.05 underestimation). In comparison with the JMA data, the time series of MAIAC AOD were more consistent with AERONET AOD values and better capture the diurnal variations of the latter. The dependence of MAIAC AOD bias on scattering angles is also discussed. Text Aerosol Robotic Network MDPI Open Access Publishing Remote Sensing 11 23 2771
spellingShingle GeoNEX
aerosol optical depth (AOD)
MAIAC
validation
AERONET
Lu She
Hankui Zhang
Weile Wang
Yujie Wang
Yun Shi
Evaluation of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) Aerosol Algorithm for Himawari-8 Data
title Evaluation of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) Aerosol Algorithm for Himawari-8 Data
title_full Evaluation of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) Aerosol Algorithm for Himawari-8 Data
title_fullStr Evaluation of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) Aerosol Algorithm for Himawari-8 Data
title_full_unstemmed Evaluation of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) Aerosol Algorithm for Himawari-8 Data
title_short Evaluation of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) Aerosol Algorithm for Himawari-8 Data
title_sort evaluation of the multi-angle implementation of atmospheric correction (maiac) aerosol algorithm for himawari-8 data
topic GeoNEX
aerosol optical depth (AOD)
MAIAC
validation
AERONET
topic_facet GeoNEX
aerosol optical depth (AOD)
MAIAC
validation
AERONET
url https://doi.org/10.3390/rs11232771