Remote Sensing of Sea Surface pCO2 in the Bering Sea in Summer Based on a Mechanistic Semi-Analytical Algorithm (MeSAA)

The Bering Sea, one of the largest and most productive marginal seas, is a crucial carbon sink for the marine carbonate system. However, restricted by the tough observation conditions, few underway datasets of sea surface partial pressure of carbon dioxide (pCO2) have been obtained, with most of the...

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Published in:Remote Sensing
Main Authors: Xuelian Song, Yan Bai, Wei-Jun Cai, Chen-Tung Arthur Chen, Delu Pan, Xianqiang He, Qiankun Zhu
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2016
Subjects:
Q
Online Access:https://doi.org/10.3390/rs8070558
https://doaj.org/article/d0f328e3338443c4ab7697621b4ae52d
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spelling ftdoajarticles:oai:doaj.org/article:d0f328e3338443c4ab7697621b4ae52d 2023-05-15T15:43:03+02:00 Remote Sensing of Sea Surface pCO2 in the Bering Sea in Summer Based on a Mechanistic Semi-Analytical Algorithm (MeSAA) Xuelian Song Yan Bai Wei-Jun Cai Chen-Tung Arthur Chen Delu Pan Xianqiang He Qiankun Zhu 2016-06-01T00:00:00Z https://doi.org/10.3390/rs8070558 https://doaj.org/article/d0f328e3338443c4ab7697621b4ae52d EN eng MDPI AG http://www.mdpi.com/2072-4292/8/7/558 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs8070558 https://doaj.org/article/d0f328e3338443c4ab7697621b4ae52d Remote Sensing, Vol 8, Iss 7, p 558 (2016) sea surface pCO2 satellite remote sensing semi-analytical algorithm the Bering Sea marine carbonate system Science Q article 2016 ftdoajarticles https://doi.org/10.3390/rs8070558 2022-12-31T15:16:11Z The Bering Sea, one of the largest and most productive marginal seas, is a crucial carbon sink for the marine carbonate system. However, restricted by the tough observation conditions, few underway datasets of sea surface partial pressure of carbon dioxide (pCO2) have been obtained, with most of them in the eastern areas. Satellite remote sensing data can provide valuable information covered by a large area synchronously with high temporal resolution for assessments of pCO2 that subsequently allow quantification of air-sea carbon dioxide 2 flux. However, pCO2 in the Bering Sea is controlled by multiple factors and thus it is hard to develop a remote sensing algorithm with empirical regression methods. In this paper pCO2 in the Bering Sea from July to September was derived based on a mechanistic semi-analytical algorithm (MeSAA). It was assumed that the observed pCO2 can be analytically expressed as the sum of individual components controlled by major factors. First, a reference water mass that was minimally influenced by biology and mixing was identified in the central basin, and then thermodynamic and biological effects were parameterized for the entire area. Finally, we estimated pCO2 with satellite temperature and chlorophyll data. Satellite results agreed well with the underway observations. Our study suggested that throughout the Bering Sea the biological effect on pCO2 was more than twice as important as temperature, and contributions of other effects were relatively small. Furthermore, satellite observations demonstrate that the spring phytoplankton bloom had a delayed effect on summer pCO2 but that the influence of this biological event varied regionally; it was more significant on the continental slope, with a later bloom, than that on the shelf with an early bloom. Overall, the MeSAA algorithm was not only able to estimate pCO2 in the Bering Sea for the first time, but also provided a quantitative analysis of the contribution of various processes that influence pCO2. Article in Journal/Newspaper Bering Sea Directory of Open Access Journals: DOAJ Articles Bering Sea Remote Sensing 8 7 558
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic sea surface pCO2
satellite remote sensing
semi-analytical algorithm
the Bering Sea
marine carbonate system
Science
Q
spellingShingle sea surface pCO2
satellite remote sensing
semi-analytical algorithm
the Bering Sea
marine carbonate system
Science
Q
Xuelian Song
Yan Bai
Wei-Jun Cai
Chen-Tung Arthur Chen
Delu Pan
Xianqiang He
Qiankun Zhu
Remote Sensing of Sea Surface pCO2 in the Bering Sea in Summer Based on a Mechanistic Semi-Analytical Algorithm (MeSAA)
topic_facet sea surface pCO2
satellite remote sensing
semi-analytical algorithm
the Bering Sea
marine carbonate system
Science
Q
description The Bering Sea, one of the largest and most productive marginal seas, is a crucial carbon sink for the marine carbonate system. However, restricted by the tough observation conditions, few underway datasets of sea surface partial pressure of carbon dioxide (pCO2) have been obtained, with most of them in the eastern areas. Satellite remote sensing data can provide valuable information covered by a large area synchronously with high temporal resolution for assessments of pCO2 that subsequently allow quantification of air-sea carbon dioxide 2 flux. However, pCO2 in the Bering Sea is controlled by multiple factors and thus it is hard to develop a remote sensing algorithm with empirical regression methods. In this paper pCO2 in the Bering Sea from July to September was derived based on a mechanistic semi-analytical algorithm (MeSAA). It was assumed that the observed pCO2 can be analytically expressed as the sum of individual components controlled by major factors. First, a reference water mass that was minimally influenced by biology and mixing was identified in the central basin, and then thermodynamic and biological effects were parameterized for the entire area. Finally, we estimated pCO2 with satellite temperature and chlorophyll data. Satellite results agreed well with the underway observations. Our study suggested that throughout the Bering Sea the biological effect on pCO2 was more than twice as important as temperature, and contributions of other effects were relatively small. Furthermore, satellite observations demonstrate that the spring phytoplankton bloom had a delayed effect on summer pCO2 but that the influence of this biological event varied regionally; it was more significant on the continental slope, with a later bloom, than that on the shelf with an early bloom. Overall, the MeSAA algorithm was not only able to estimate pCO2 in the Bering Sea for the first time, but also provided a quantitative analysis of the contribution of various processes that influence pCO2.
format Article in Journal/Newspaper
author Xuelian Song
Yan Bai
Wei-Jun Cai
Chen-Tung Arthur Chen
Delu Pan
Xianqiang He
Qiankun Zhu
author_facet Xuelian Song
Yan Bai
Wei-Jun Cai
Chen-Tung Arthur Chen
Delu Pan
Xianqiang He
Qiankun Zhu
author_sort Xuelian Song
title Remote Sensing of Sea Surface pCO2 in the Bering Sea in Summer Based on a Mechanistic Semi-Analytical Algorithm (MeSAA)
title_short Remote Sensing of Sea Surface pCO2 in the Bering Sea in Summer Based on a Mechanistic Semi-Analytical Algorithm (MeSAA)
title_full Remote Sensing of Sea Surface pCO2 in the Bering Sea in Summer Based on a Mechanistic Semi-Analytical Algorithm (MeSAA)
title_fullStr Remote Sensing of Sea Surface pCO2 in the Bering Sea in Summer Based on a Mechanistic Semi-Analytical Algorithm (MeSAA)
title_full_unstemmed Remote Sensing of Sea Surface pCO2 in the Bering Sea in Summer Based on a Mechanistic Semi-Analytical Algorithm (MeSAA)
title_sort remote sensing of sea surface pco2 in the bering sea in summer based on a mechanistic semi-analytical algorithm (mesaa)
publisher MDPI AG
publishDate 2016
url https://doi.org/10.3390/rs8070558
https://doaj.org/article/d0f328e3338443c4ab7697621b4ae52d
geographic Bering Sea
geographic_facet Bering Sea
genre Bering Sea
genre_facet Bering Sea
op_source Remote Sensing, Vol 8, Iss 7, p 558 (2016)
op_relation http://www.mdpi.com/2072-4292/8/7/558
https://doaj.org/toc/2072-4292
2072-4292
doi:10.3390/rs8070558
https://doaj.org/article/d0f328e3338443c4ab7697621b4ae52d
op_doi https://doi.org/10.3390/rs8070558
container_title Remote Sensing
container_volume 8
container_issue 7
container_start_page 558
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