Evaluation of the CDOM Absorption Coefficient in the Arctic Seas Based on Sentinel-3 OLCI Data

Our work’s primary goal is to reveal the problematic issues related to estimates of the colored organic matter absorption coefficient in the northern seas from data of the Ocean and Land Color Instrument (OLCI) installed on the Sentinel-3 satellites, e.g., a comparison of the OLCI standard error ass...

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Published in:Remote Sensing
Main Authors: Dmitry Glukhovets, Oleg Kopelevich, Anna Yushmanova, Svetlana Vazyulya, Sergey Sheberstov, Polina Karalli, Inna Sahling
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2020
Subjects:
Online Access:https://doi.org/10.3390/rs12193210
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spelling ftmdpi:oai:mdpi.com:/2072-4292/12/19/3210/ 2023-08-20T04:04:36+02:00 Evaluation of the CDOM Absorption Coefficient in the Arctic Seas Based on Sentinel-3 OLCI Data Dmitry Glukhovets Oleg Kopelevich Anna Yushmanova Svetlana Vazyulya Sergey Sheberstov Polina Karalli Inna Sahling agris 2020-10-01 application/pdf https://doi.org/10.3390/rs12193210 EN eng Multidisciplinary Digital Publishing Institute Ocean Remote Sensing https://dx.doi.org/10.3390/rs12193210 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 12; Issue 19; Pages: 3210 OLCI Sentinel-3 Barents Kara Sea absorption coefficient uncertainties field data Text 2020 ftmdpi https://doi.org/10.3390/rs12193210 2023-08-01T00:12:52Z Our work’s primary goal is to reveal the problematic issues related to estimates of the colored organic matter absorption coefficient in the northern seas from data of the Ocean and Land Color Instrument (OLCI) installed on the Sentinel-3 satellites, e.g., a comparison of the OLCI standard error assessment ADG443_NN_err relating to the measurement and the retrieval of the geophysical products and the uncertainties in the northern seas’ real situation. The natural conditions are incredibly unfavorable there, mainly due to frequent cloudiness and low sun heights. We conducted a comprehensive multi-sensor study of the uncertainties using various approaches. We directly compared the data from satellites (OLCI Sentinel-3 and four other ocean color sensors) and field measurements in five sea expeditions (2016–2019) using the different processing algorithms. Our analysis has shown that the final product’s real uncertainties are significantly (≥100%) higher than the calculated errors of the ADG443_NN_err (~10%). The main reason is the unsatisfactory atmospheric correction. We present the analysis of the various influential factors (satellite sensors, processing algorithms, and other parameters) and formulate future work goals. Text Arctic Kara Sea MDPI Open Access Publishing Arctic Kara Sea The Sentinel ENVELOPE(73.317,73.317,-52.983,-52.983) Remote Sensing 12 19 3210
institution Open Polar
collection MDPI Open Access Publishing
op_collection_id ftmdpi
language English
topic OLCI Sentinel-3
Barents
Kara Sea
absorption coefficient
uncertainties
field data
spellingShingle OLCI Sentinel-3
Barents
Kara Sea
absorption coefficient
uncertainties
field data
Dmitry Glukhovets
Oleg Kopelevich
Anna Yushmanova
Svetlana Vazyulya
Sergey Sheberstov
Polina Karalli
Inna Sahling
Evaluation of the CDOM Absorption Coefficient in the Arctic Seas Based on Sentinel-3 OLCI Data
topic_facet OLCI Sentinel-3
Barents
Kara Sea
absorption coefficient
uncertainties
field data
description Our work’s primary goal is to reveal the problematic issues related to estimates of the colored organic matter absorption coefficient in the northern seas from data of the Ocean and Land Color Instrument (OLCI) installed on the Sentinel-3 satellites, e.g., a comparison of the OLCI standard error assessment ADG443_NN_err relating to the measurement and the retrieval of the geophysical products and the uncertainties in the northern seas’ real situation. The natural conditions are incredibly unfavorable there, mainly due to frequent cloudiness and low sun heights. We conducted a comprehensive multi-sensor study of the uncertainties using various approaches. We directly compared the data from satellites (OLCI Sentinel-3 and four other ocean color sensors) and field measurements in five sea expeditions (2016–2019) using the different processing algorithms. Our analysis has shown that the final product’s real uncertainties are significantly (≥100%) higher than the calculated errors of the ADG443_NN_err (~10%). The main reason is the unsatisfactory atmospheric correction. We present the analysis of the various influential factors (satellite sensors, processing algorithms, and other parameters) and formulate future work goals.
format Text
author Dmitry Glukhovets
Oleg Kopelevich
Anna Yushmanova
Svetlana Vazyulya
Sergey Sheberstov
Polina Karalli
Inna Sahling
author_facet Dmitry Glukhovets
Oleg Kopelevich
Anna Yushmanova
Svetlana Vazyulya
Sergey Sheberstov
Polina Karalli
Inna Sahling
author_sort Dmitry Glukhovets
title Evaluation of the CDOM Absorption Coefficient in the Arctic Seas Based on Sentinel-3 OLCI Data
title_short Evaluation of the CDOM Absorption Coefficient in the Arctic Seas Based on Sentinel-3 OLCI Data
title_full Evaluation of the CDOM Absorption Coefficient in the Arctic Seas Based on Sentinel-3 OLCI Data
title_fullStr Evaluation of the CDOM Absorption Coefficient in the Arctic Seas Based on Sentinel-3 OLCI Data
title_full_unstemmed Evaluation of the CDOM Absorption Coefficient in the Arctic Seas Based on Sentinel-3 OLCI Data
title_sort evaluation of the cdom absorption coefficient in the arctic seas based on sentinel-3 olci data
publisher Multidisciplinary Digital Publishing Institute
publishDate 2020
url https://doi.org/10.3390/rs12193210
op_coverage agris
long_lat ENVELOPE(73.317,73.317,-52.983,-52.983)
geographic Arctic
Kara Sea
The Sentinel
geographic_facet Arctic
Kara Sea
The Sentinel
genre Arctic
Kara Sea
genre_facet Arctic
Kara Sea
op_source Remote Sensing; Volume 12; Issue 19; Pages: 3210
op_relation Ocean Remote Sensing
https://dx.doi.org/10.3390/rs12193210
op_rights https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.3390/rs12193210
container_title Remote Sensing
container_volume 12
container_issue 19
container_start_page 3210
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