Variations in the summer oceanic pCO2 and carbon sink in Prydz Bay using the self-organizing map analysis approach

This study applies a neural network technique to produce maps of oceanic surface pCO2 in Prydz Bay in the Southern Ocean on a weekly 0.1∘ longitude × 0.1∘ latitude grid based on in situ measurements obtained during the 31st CHINARE cruise from February to early March 2015. This study area was divide...

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Published in:Biogeosciences
Main Authors: Xu, Suqing, Park, Keyhong, Wang, Yanmin, Chen, Liqi, Qi, Di, Li, Bingrui
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2019
Subjects:
Online Access:https://doi.org/10.5194/bg-16-797-2019
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spelling ftnonlinearchiv:oai:noa.gwlb.de:cop_mods_00003197 2023-05-15T18:03:39+02:00 Variations in the summer oceanic pCO2 and carbon sink in Prydz Bay using the self-organizing map analysis approach Xu, Suqing Park, Keyhong Wang, Yanmin Chen, Liqi Qi, Di Li, Bingrui 2019-02 electronic https://doi.org/10.5194/bg-16-797-2019 https://noa.gwlb.de/receive/cop_mods_00003197 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00003155/bg-16-797-2019.pdf https://bg.copernicus.org/articles/16/797/2019/bg-16-797-2019.pdf eng eng Copernicus Publications Biogeosciences -- http://www.bibliothek.uni-regensburg.de/ezeit/?2158181 -- http://www.copernicus.org/EGU/bg/bg.html -- 1726-4189 https://doi.org/10.5194/bg-16-797-2019 https://noa.gwlb.de/receive/cop_mods_00003197 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00003155/bg-16-797-2019.pdf https://bg.copernicus.org/articles/16/797/2019/bg-16-797-2019.pdf https://creativecommons.org/licenses/by/4.0/ uneingeschränkt info:eu-repo/semantics/openAccess CC-BY article Verlagsveröffentlichung article Text doc-type:article 2019 ftnonlinearchiv https://doi.org/10.5194/bg-16-797-2019 2022-02-08T23:00:42Z This study applies a neural network technique to produce maps of oceanic surface pCO2 in Prydz Bay in the Southern Ocean on a weekly 0.1∘ longitude × 0.1∘ latitude grid based on in situ measurements obtained during the 31st CHINARE cruise from February to early March 2015. This study area was divided into three regions, namely, the “open-ocean” region, “sea-ice” region and “shelf” region. The distribution of oceanic pCO2 was mainly affected by physical processes in the open-ocean region, where mixing and upwelling were the main controls. In the sea-ice region, oceanic pCO2 changed sharply due to the strong change in seasonal ice. In the shelf region, biological factors were the main control. The weekly oceanic pCO2 was estimated using a self-organizing map (SOM) with four proxy parameters (sea surface temperature, chlorophyll a concentration, mixed Layer Depth and sea surface salinity) to overcome the complex relationship between the biogeochemical and physical conditions in the Prydz Bay region. The reconstructed oceanic pCO2 data coincide well with the in situ pCO2 data from SOCAT, with a root mean square error of 22.14 µatm. Prydz Bay was mainly a strong CO2 sink in February 2015, with a monthly averaged uptake of 23.57±6.36 TgC. The oceanic CO2 sink is pronounced in the shelf region due to its low oceanic pCO2 values and peak biological production. Article in Journal/Newspaper Prydz Bay Sea ice Southern Ocean Niedersächsisches Online-Archiv NOA Prydz Bay Southern Ocean Biogeosciences 16 3 797 810
institution Open Polar
collection Niedersächsisches Online-Archiv NOA
op_collection_id ftnonlinearchiv
language English
topic article
Verlagsveröffentlichung
spellingShingle article
Verlagsveröffentlichung
Xu, Suqing
Park, Keyhong
Wang, Yanmin
Chen, Liqi
Qi, Di
Li, Bingrui
Variations in the summer oceanic pCO2 and carbon sink in Prydz Bay using the self-organizing map analysis approach
topic_facet article
Verlagsveröffentlichung
description This study applies a neural network technique to produce maps of oceanic surface pCO2 in Prydz Bay in the Southern Ocean on a weekly 0.1∘ longitude × 0.1∘ latitude grid based on in situ measurements obtained during the 31st CHINARE cruise from February to early March 2015. This study area was divided into three regions, namely, the “open-ocean” region, “sea-ice” region and “shelf” region. The distribution of oceanic pCO2 was mainly affected by physical processes in the open-ocean region, where mixing and upwelling were the main controls. In the sea-ice region, oceanic pCO2 changed sharply due to the strong change in seasonal ice. In the shelf region, biological factors were the main control. The weekly oceanic pCO2 was estimated using a self-organizing map (SOM) with four proxy parameters (sea surface temperature, chlorophyll a concentration, mixed Layer Depth and sea surface salinity) to overcome the complex relationship between the biogeochemical and physical conditions in the Prydz Bay region. The reconstructed oceanic pCO2 data coincide well with the in situ pCO2 data from SOCAT, with a root mean square error of 22.14 µatm. Prydz Bay was mainly a strong CO2 sink in February 2015, with a monthly averaged uptake of 23.57±6.36 TgC. The oceanic CO2 sink is pronounced in the shelf region due to its low oceanic pCO2 values and peak biological production.
format Article in Journal/Newspaper
author Xu, Suqing
Park, Keyhong
Wang, Yanmin
Chen, Liqi
Qi, Di
Li, Bingrui
author_facet Xu, Suqing
Park, Keyhong
Wang, Yanmin
Chen, Liqi
Qi, Di
Li, Bingrui
author_sort Xu, Suqing
title Variations in the summer oceanic pCO2 and carbon sink in Prydz Bay using the self-organizing map analysis approach
title_short Variations in the summer oceanic pCO2 and carbon sink in Prydz Bay using the self-organizing map analysis approach
title_full Variations in the summer oceanic pCO2 and carbon sink in Prydz Bay using the self-organizing map analysis approach
title_fullStr Variations in the summer oceanic pCO2 and carbon sink in Prydz Bay using the self-organizing map analysis approach
title_full_unstemmed Variations in the summer oceanic pCO2 and carbon sink in Prydz Bay using the self-organizing map analysis approach
title_sort variations in the summer oceanic pco2 and carbon sink in prydz bay using the self-organizing map analysis approach
publisher Copernicus Publications
publishDate 2019
url https://doi.org/10.5194/bg-16-797-2019
https://noa.gwlb.de/receive/cop_mods_00003197
https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00003155/bg-16-797-2019.pdf
https://bg.copernicus.org/articles/16/797/2019/bg-16-797-2019.pdf
geographic Prydz Bay
Southern Ocean
geographic_facet Prydz Bay
Southern Ocean
genre Prydz Bay
Sea ice
Southern Ocean
genre_facet Prydz Bay
Sea ice
Southern Ocean
op_relation Biogeosciences -- http://www.bibliothek.uni-regensburg.de/ezeit/?2158181 -- http://www.copernicus.org/EGU/bg/bg.html -- 1726-4189
https://doi.org/10.5194/bg-16-797-2019
https://noa.gwlb.de/receive/cop_mods_00003197
https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00003155/bg-16-797-2019.pdf
https://bg.copernicus.org/articles/16/797/2019/bg-16-797-2019.pdf
op_rights https://creativecommons.org/licenses/by/4.0/
uneingeschränkt
info:eu-repo/semantics/openAccess
op_rightsnorm CC-BY
op_doi https://doi.org/10.5194/bg-16-797-2019
container_title Biogeosciences
container_volume 16
container_issue 3
container_start_page 797
op_container_end_page 810
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