Impact of Aerosol Model Selection on Water-Leaving Radiance Retrievals from Satellite Ocean Color Imagery
We examine the impact of atmospheric correction, specifically aerosol model selection, on retrieval of bio-optical properties from satellite ocean color imagery. Uncertainties in retrievals of bio-optical properties (such as chlorophyll, absorption, and backscattering coefficients) from satellite oc...
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ftmdpi:oai:mdpi.com:/2072-4292/4/12/3638/ 2023-08-20T03:59:11+02:00 Impact of Aerosol Model Selection on Water-Leaving Radiance Retrievals from Satellite Ocean Color Imagery Sean McCarthy Richard Gould James Richman Courtney Kearney Adam Lawson agris 2012-11-22 application/pdf https://doi.org/10.3390/rs4123638 EN eng Multidisciplinary Digital Publishing Institute https://dx.doi.org/10.3390/rs4123638 https://creativecommons.org/licenses/by/3.0/ Remote Sensing; Volume 4; Issue 12; Pages: 3638-3665 aerosol models normalized water-leaving radiance MODIS AERONET-OC atmospheric correction ocean color Text 2012 ftmdpi https://doi.org/10.3390/rs4123638 2023-07-31T20:30:44Z We examine the impact of atmospheric correction, specifically aerosol model selection, on retrieval of bio-optical properties from satellite ocean color imagery. Uncertainties in retrievals of bio-optical properties (such as chlorophyll, absorption, and backscattering coefficients) from satellite ocean color imagery are related to a variety of factors, including errors associated with sensor calibration, atmospheric correction, and the bio-optical inversion algorithms. In many cases, selection of an inappropriate or erroneous aerosol model during atmospheric correction can dominate the errors in the satellite estimation of the normalized water-leaving radiances (nLw), especially over turbid, coastal waters. These errors affect the downstream bio-optical properties. Here, we focus on the impact of aerosol model selection on the nLw radiance estimates by comparing Aerosol Robotic Network-Ocean Color (AERONET-OC) measurements of nLw and aerosol optical depth (AOD) to satellite-derived values from Moderate Resolution Imaging Spectroradiometer (MODIS) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS). We also apply noise to the satellite top-of-atmosphere (TOA) radiance values in the two near-infrared (NIR) wavelengths used for atmospheric correction, to assess the effect on aerosol model selection and nLw retrievals. In general, for the data sets examined, we found that as little as 1% uncertainty (noise) in the NIR TOA radiances can lead to the selection of a different pair of bounding aerosol models, thus changing nLw retrievals. We also compare aerosol size fraction retrieved from AERONET and size fraction represented by aerosol models selected during atmospheric correction. Text Aerosol Robotic Network MDPI Open Access Publishing Remote Sensing 4 12 3638 3665 |
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Open Polar |
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MDPI Open Access Publishing |
op_collection_id |
ftmdpi |
language |
English |
topic |
aerosol models normalized water-leaving radiance MODIS AERONET-OC atmospheric correction ocean color |
spellingShingle |
aerosol models normalized water-leaving radiance MODIS AERONET-OC atmospheric correction ocean color Sean McCarthy Richard Gould James Richman Courtney Kearney Adam Lawson Impact of Aerosol Model Selection on Water-Leaving Radiance Retrievals from Satellite Ocean Color Imagery |
topic_facet |
aerosol models normalized water-leaving radiance MODIS AERONET-OC atmospheric correction ocean color |
description |
We examine the impact of atmospheric correction, specifically aerosol model selection, on retrieval of bio-optical properties from satellite ocean color imagery. Uncertainties in retrievals of bio-optical properties (such as chlorophyll, absorption, and backscattering coefficients) from satellite ocean color imagery are related to a variety of factors, including errors associated with sensor calibration, atmospheric correction, and the bio-optical inversion algorithms. In many cases, selection of an inappropriate or erroneous aerosol model during atmospheric correction can dominate the errors in the satellite estimation of the normalized water-leaving radiances (nLw), especially over turbid, coastal waters. These errors affect the downstream bio-optical properties. Here, we focus on the impact of aerosol model selection on the nLw radiance estimates by comparing Aerosol Robotic Network-Ocean Color (AERONET-OC) measurements of nLw and aerosol optical depth (AOD) to satellite-derived values from Moderate Resolution Imaging Spectroradiometer (MODIS) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS). We also apply noise to the satellite top-of-atmosphere (TOA) radiance values in the two near-infrared (NIR) wavelengths used for atmospheric correction, to assess the effect on aerosol model selection and nLw retrievals. In general, for the data sets examined, we found that as little as 1% uncertainty (noise) in the NIR TOA radiances can lead to the selection of a different pair of bounding aerosol models, thus changing nLw retrievals. We also compare aerosol size fraction retrieved from AERONET and size fraction represented by aerosol models selected during atmospheric correction. |
format |
Text |
author |
Sean McCarthy Richard Gould James Richman Courtney Kearney Adam Lawson |
author_facet |
Sean McCarthy Richard Gould James Richman Courtney Kearney Adam Lawson |
author_sort |
Sean McCarthy |
title |
Impact of Aerosol Model Selection on Water-Leaving Radiance Retrievals from Satellite Ocean Color Imagery |
title_short |
Impact of Aerosol Model Selection on Water-Leaving Radiance Retrievals from Satellite Ocean Color Imagery |
title_full |
Impact of Aerosol Model Selection on Water-Leaving Radiance Retrievals from Satellite Ocean Color Imagery |
title_fullStr |
Impact of Aerosol Model Selection on Water-Leaving Radiance Retrievals from Satellite Ocean Color Imagery |
title_full_unstemmed |
Impact of Aerosol Model Selection on Water-Leaving Radiance Retrievals from Satellite Ocean Color Imagery |
title_sort |
impact of aerosol model selection on water-leaving radiance retrievals from satellite ocean color imagery |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2012 |
url |
https://doi.org/10.3390/rs4123638 |
op_coverage |
agris |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_source |
Remote Sensing; Volume 4; Issue 12; Pages: 3638-3665 |
op_relation |
https://dx.doi.org/10.3390/rs4123638 |
op_rights |
https://creativecommons.org/licenses/by/3.0/ |
op_doi |
https://doi.org/10.3390/rs4123638 |
container_title |
Remote Sensing |
container_volume |
4 |
container_issue |
12 |
container_start_page |
3638 |
op_container_end_page |
3665 |
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