Impact of Monsoon-Transported Anthropogenic Aerosols and Sun-Glint on the Satellite-Derived Spectral Remote Sensing Reflectance in the Indian Ocean

Spectral remote sensing reflectance (R<sub>rs</sub>(λ), sr<sup>−1</sup>) is one of the most important products of ocean color satellite missions, where accuracy is essential for retrieval of in-water, bio-optical, and biogeochemical properties. For the Indian Ocean (IO), wher...

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Main Authors: Rongjie Liu, Jie Zhang, Tingwei Cui, Haocheng Yu
Format: Article
Language:English
Published: MDPI AG 2021-01-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/13/2/184
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spelling doaj-26605da042ea4865ad1e8ac75f07b7fc2021-01-08T00:02:54ZengMDPI AGRemote Sensing2072-42922021-01-011318418410.3390/rs13020184Impact of Monsoon-Transported Anthropogenic Aerosols and Sun-Glint on the Satellite-Derived Spectral Remote Sensing Reflectance in the Indian OceanRongjie Liu0Jie Zhang1Tingwei Cui2Haocheng Yu3First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, ChinaFirst Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, ChinaGuangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-sen University, Zhuhai 519000, ChinaCollege of Information Science and Engineering, Ocean University of China, Qingdao 266071, ChinaSpectral remote sensing reflectance (R<sub>rs</sub>(λ), sr<sup>−1</sup>) is one of the most important products of ocean color satellite missions, where accuracy is essential for retrieval of in-water, bio-optical, and biogeochemical properties. For the Indian Ocean (IO), where R<sub>rs</sub>(λ) accuracy has not been well documented, the quality of R<sub>rs</sub>(λ) products from Moderate Resolution Imaging Spectroradiometer onboard both Terra (MODIS-Terra) and Aqua (MODIS-Aqua), and Visible Infrared Imaging Radiometer Suite onboard the Suomi National Polar-Orbiting Partnership spacecraft (VIIRS-NPP), is evaluated and inter-compared based on a quality assurance (QA) system, which can objectively grade each individual R<sub>rs</sub>(λ) spectrum, with 1 for a perfect spectrum and 0 for an unusable spectrum. Taking the whole year of 2016 as an example, spatiotemporal pattern of R<sub>rs</sub>(λ) quality in the Indian Ocean is characterized for the first time, and the underlying factors are elucidated. Specifically, QA analysis of the monthly R<sub>rs</sub>(λ) over the IO indicates good quality with the average scores of 0.93 ± 0.02, 0.92 ± 0.02 and 0.92 ± 0.02 for VIIRS-NPP, MODIS-Aqua, and MODIS-Terra, respectively. Low-quality (~0.7) data are mainly found in the Bengal Bay (BB) from January to March, which can be attributed to the imperfect atmospheric correction due to anthropogenic absorptive aerosols transported by the northeasterly winter monsoon. Moreover, low-quality (~0.74) data are also found in the clear oligotrophic gyre zone (OZ) of the south IO in the second half of the year, possibly due to residual sun-glint contributions. These findings highlight the effects of monsoon-transported anthropogenic aerosols, and imperfect sun-glint removal on the R<sub>rs</sub>(λ) quality. Further studies are advocated to improve the sun-glint correction in the oligotrophic gyre zone and aerosol correction in the complex ocean–atmosphere environment.https://www.mdpi.com/2072-4292/13/2/184remote sensing reflectancedata qualitythe Indian Oceanaccuracy
collection DOAJ
language English
format Article
sources DOAJ
author Rongjie Liu
Jie Zhang
Tingwei Cui
Haocheng Yu
spellingShingle Rongjie Liu
Jie Zhang
Tingwei Cui
Haocheng Yu
Impact of Monsoon-Transported Anthropogenic Aerosols and Sun-Glint on the Satellite-Derived Spectral Remote Sensing Reflectance in the Indian Ocean
Remote Sensing
remote sensing reflectance
data quality
the Indian Ocean
accuracy
author_facet Rongjie Liu
Jie Zhang
Tingwei Cui
Haocheng Yu
author_sort Rongjie Liu
title Impact of Monsoon-Transported Anthropogenic Aerosols and Sun-Glint on the Satellite-Derived Spectral Remote Sensing Reflectance in the Indian Ocean
title_short Impact of Monsoon-Transported Anthropogenic Aerosols and Sun-Glint on the Satellite-Derived Spectral Remote Sensing Reflectance in the Indian Ocean
title_full Impact of Monsoon-Transported Anthropogenic Aerosols and Sun-Glint on the Satellite-Derived Spectral Remote Sensing Reflectance in the Indian Ocean
title_fullStr Impact of Monsoon-Transported Anthropogenic Aerosols and Sun-Glint on the Satellite-Derived Spectral Remote Sensing Reflectance in the Indian Ocean
title_full_unstemmed Impact of Monsoon-Transported Anthropogenic Aerosols and Sun-Glint on the Satellite-Derived Spectral Remote Sensing Reflectance in the Indian Ocean
title_sort impact of monsoon-transported anthropogenic aerosols and sun-glint on the satellite-derived spectral remote sensing reflectance in the indian ocean
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2021-01-01
description Spectral remote sensing reflectance (R<sub>rs</sub>(λ), sr<sup>−1</sup>) is one of the most important products of ocean color satellite missions, where accuracy is essential for retrieval of in-water, bio-optical, and biogeochemical properties. For the Indian Ocean (IO), where R<sub>rs</sub>(λ) accuracy has not been well documented, the quality of R<sub>rs</sub>(λ) products from Moderate Resolution Imaging Spectroradiometer onboard both Terra (MODIS-Terra) and Aqua (MODIS-Aqua), and Visible Infrared Imaging Radiometer Suite onboard the Suomi National Polar-Orbiting Partnership spacecraft (VIIRS-NPP), is evaluated and inter-compared based on a quality assurance (QA) system, which can objectively grade each individual R<sub>rs</sub>(λ) spectrum, with 1 for a perfect spectrum and 0 for an unusable spectrum. Taking the whole year of 2016 as an example, spatiotemporal pattern of R<sub>rs</sub>(λ) quality in the Indian Ocean is characterized for the first time, and the underlying factors are elucidated. Specifically, QA analysis of the monthly R<sub>rs</sub>(λ) over the IO indicates good quality with the average scores of 0.93 ± 0.02, 0.92 ± 0.02 and 0.92 ± 0.02 for VIIRS-NPP, MODIS-Aqua, and MODIS-Terra, respectively. Low-quality (~0.7) data are mainly found in the Bengal Bay (BB) from January to March, which can be attributed to the imperfect atmospheric correction due to anthropogenic absorptive aerosols transported by the northeasterly winter monsoon. Moreover, low-quality (~0.74) data are also found in the clear oligotrophic gyre zone (OZ) of the south IO in the second half of the year, possibly due to residual sun-glint contributions. These findings highlight the effects of monsoon-transported anthropogenic aerosols, and imperfect sun-glint removal on the R<sub>rs</sub>(λ) quality. Further studies are advocated to improve the sun-glint correction in the oligotrophic gyre zone and aerosol correction in the complex ocean–atmosphere environment.
topic remote sensing reflectance
data quality
the Indian Ocean
accuracy
url https://www.mdpi.com/2072-4292/13/2/184
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