Spectral and Spatial Dependencies in the Validation of Satellite-Based Aerosol Optical Depth from the Geostationary Ocean Color Imager Using the Aerosol Robotic Network
The regional and global scale of aerosols in the atmosphere can be quantified using the aerosol optical depth (AOD) retrieved from satellite observations. To obtain reliable satellite AODs, conducting consistent validations and refining retrieval algorithms are crucial. AODs and Ångström exponents (...
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ftmdpi:oai:mdpi.com:/2072-4292/15/14/3621/ 2023-08-20T03:59:10+02:00 Spectral and Spatial Dependencies in the Validation of Satellite-Based Aerosol Optical Depth from the Geostationary Ocean Color Imager Using the Aerosol Robotic Network Mijeong Kim Kyunghwa Lee Myungje Choi agris 2023-07-20 application/pdf https://doi.org/10.3390/rs15143621 EN eng Multidisciplinary Digital Publishing Institute Atmospheric Remote Sensing https://dx.doi.org/10.3390/rs15143621 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 15; Issue 14; Pages: 3621 GOCI AERONET AOD AE validation Text 2023 ftmdpi https://doi.org/10.3390/rs15143621 2023-08-01T10:56:46Z The regional and global scale of aerosols in the atmosphere can be quantified using the aerosol optical depth (AOD) retrieved from satellite observations. To obtain reliable satellite AODs, conducting consistent validations and refining retrieval algorithms are crucial. AODs and Ångström exponents (AEs) measured with the aerosol robotic network (AERONET) are considered as the ground truth for satellite validations. AERONET AEs are used to collocate the wavelength of the AERONET AODs to those of the satellite AODs when there is a discordancy in their wavelengths. However, numerous validation studies have proposed different strategies by applying the AERONET AODs and AEs, and spatiotemporal collocation criteria. This study examined the impact of the wavelength and spatial collocation radius variations by comparing AODs at 550 nm derived from the geostationary ocean color imager (GOCI) with those obtained from the AERONET for the year 2016. The estimated AERONET AODs at 550 nm varied from 5.18% to 11.73% depending on the selection of AOD and AE, and the spatial collocation radii from 0 to 40 km, respectively. The longer the collocation radius and the higher the AODs, the greater the variability observed in the validation results. Overall, the selection of the spatial collocation radius had a stronger impact on the variability in the validation results obtained compared to the selection of the wavelength. The variability was also found in seasonal analysis. Therefore, it is recommended to carefully select the data wavelength and spatial collocation radius, consider seasonal effects, and provide this information when validating satellite AODs using AERONET. Text Aerosol Robotic Network MDPI Open Access Publishing Remote Sensing 15 14 3621 |
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English |
topic |
GOCI AERONET AOD AE validation |
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GOCI AERONET AOD AE validation Mijeong Kim Kyunghwa Lee Myungje Choi Spectral and Spatial Dependencies in the Validation of Satellite-Based Aerosol Optical Depth from the Geostationary Ocean Color Imager Using the Aerosol Robotic Network |
topic_facet |
GOCI AERONET AOD AE validation |
description |
The regional and global scale of aerosols in the atmosphere can be quantified using the aerosol optical depth (AOD) retrieved from satellite observations. To obtain reliable satellite AODs, conducting consistent validations and refining retrieval algorithms are crucial. AODs and Ångström exponents (AEs) measured with the aerosol robotic network (AERONET) are considered as the ground truth for satellite validations. AERONET AEs are used to collocate the wavelength of the AERONET AODs to those of the satellite AODs when there is a discordancy in their wavelengths. However, numerous validation studies have proposed different strategies by applying the AERONET AODs and AEs, and spatiotemporal collocation criteria. This study examined the impact of the wavelength and spatial collocation radius variations by comparing AODs at 550 nm derived from the geostationary ocean color imager (GOCI) with those obtained from the AERONET for the year 2016. The estimated AERONET AODs at 550 nm varied from 5.18% to 11.73% depending on the selection of AOD and AE, and the spatial collocation radii from 0 to 40 km, respectively. The longer the collocation radius and the higher the AODs, the greater the variability observed in the validation results. Overall, the selection of the spatial collocation radius had a stronger impact on the variability in the validation results obtained compared to the selection of the wavelength. The variability was also found in seasonal analysis. Therefore, it is recommended to carefully select the data wavelength and spatial collocation radius, consider seasonal effects, and provide this information when validating satellite AODs using AERONET. |
format |
Text |
author |
Mijeong Kim Kyunghwa Lee Myungje Choi |
author_facet |
Mijeong Kim Kyunghwa Lee Myungje Choi |
author_sort |
Mijeong Kim |
title |
Spectral and Spatial Dependencies in the Validation of Satellite-Based Aerosol Optical Depth from the Geostationary Ocean Color Imager Using the Aerosol Robotic Network |
title_short |
Spectral and Spatial Dependencies in the Validation of Satellite-Based Aerosol Optical Depth from the Geostationary Ocean Color Imager Using the Aerosol Robotic Network |
title_full |
Spectral and Spatial Dependencies in the Validation of Satellite-Based Aerosol Optical Depth from the Geostationary Ocean Color Imager Using the Aerosol Robotic Network |
title_fullStr |
Spectral and Spatial Dependencies in the Validation of Satellite-Based Aerosol Optical Depth from the Geostationary Ocean Color Imager Using the Aerosol Robotic Network |
title_full_unstemmed |
Spectral and Spatial Dependencies in the Validation of Satellite-Based Aerosol Optical Depth from the Geostationary Ocean Color Imager Using the Aerosol Robotic Network |
title_sort |
spectral and spatial dependencies in the validation of satellite-based aerosol optical depth from the geostationary ocean color imager using the aerosol robotic network |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2023 |
url |
https://doi.org/10.3390/rs15143621 |
op_coverage |
agris |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_source |
Remote Sensing; Volume 15; Issue 14; Pages: 3621 |
op_relation |
Atmospheric Remote Sensing https://dx.doi.org/10.3390/rs15143621 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/rs15143621 |
container_title |
Remote Sensing |
container_volume |
15 |
container_issue |
14 |
container_start_page |
3621 |
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1774717097331392512 |