Variations in the summer oceanic p CO 2 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 p CO 2 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 di...
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ftdoajarticles:oai:doaj.org/article:46a47d85784f4d128536f7c17ea180e8 2023-05-15T18:03:40+02:00 Variations in the summer oceanic p CO 2 and carbon sink in Prydz Bay using the self-organizing map analysis approach S. Xu K. Park Y. Wang L. Chen D. Qi B. Li 2019-02-01T00:00:00Z https://doi.org/10.5194/bg-16-797-2019 https://doaj.org/article/46a47d85784f4d128536f7c17ea180e8 EN eng Copernicus Publications https://www.biogeosciences.net/16/797/2019/bg-16-797-2019.pdf https://doaj.org/toc/1726-4170 https://doaj.org/toc/1726-4189 doi:10.5194/bg-16-797-2019 1726-4170 1726-4189 https://doaj.org/article/46a47d85784f4d128536f7c17ea180e8 Biogeosciences, Vol 16, Pp 797-810 (2019) Ecology QH540-549.5 Life QH501-531 Geology QE1-996.5 article 2019 ftdoajarticles https://doi.org/10.5194/bg-16-797-2019 2022-12-31T07:00:57Z This study applies a neural network technique to produce maps of oceanic surface p CO 2 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 p CO 2 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 p CO 2 changed sharply due to the strong change in seasonal ice. In the shelf region, biological factors were the main control. The weekly oceanic p CO 2 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 p CO 2 data coincide well with the in situ p CO 2 data from SOCAT, with a root mean square error of 22.14 µ atm. Prydz Bay was mainly a strong CO 2 sink in February 2015, with a monthly averaged uptake of 23.57±6.36 TgC. The oceanic CO 2 sink is pronounced in the shelf region due to its low oceanic p CO 2 values and peak biological production. Article in Journal/Newspaper Prydz Bay Sea ice Southern Ocean Directory of Open Access Journals: DOAJ Articles Prydz Bay Southern Ocean Biogeosciences 16 3 797 810 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Ecology QH540-549.5 Life QH501-531 Geology QE1-996.5 |
spellingShingle |
Ecology QH540-549.5 Life QH501-531 Geology QE1-996.5 S. Xu K. Park Y. Wang L. Chen D. Qi B. Li Variations in the summer oceanic p CO 2 and carbon sink in Prydz Bay using the self-organizing map analysis approach |
topic_facet |
Ecology QH540-549.5 Life QH501-531 Geology QE1-996.5 |
description |
This study applies a neural network technique to produce maps of oceanic surface p CO 2 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 p CO 2 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 p CO 2 changed sharply due to the strong change in seasonal ice. In the shelf region, biological factors were the main control. The weekly oceanic p CO 2 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 p CO 2 data coincide well with the in situ p CO 2 data from SOCAT, with a root mean square error of 22.14 µ atm. Prydz Bay was mainly a strong CO 2 sink in February 2015, with a monthly averaged uptake of 23.57±6.36 TgC. The oceanic CO 2 sink is pronounced in the shelf region due to its low oceanic p CO 2 values and peak biological production. |
format |
Article in Journal/Newspaper |
author |
S. Xu K. Park Y. Wang L. Chen D. Qi B. Li |
author_facet |
S. Xu K. Park Y. Wang L. Chen D. Qi B. Li |
author_sort |
S. Xu |
title |
Variations in the summer oceanic p CO 2 and carbon sink in Prydz Bay using the self-organizing map analysis approach |
title_short |
Variations in the summer oceanic p CO 2 and carbon sink in Prydz Bay using the self-organizing map analysis approach |
title_full |
Variations in the summer oceanic p CO 2 and carbon sink in Prydz Bay using the self-organizing map analysis approach |
title_fullStr |
Variations in the summer oceanic p CO 2 and carbon sink in Prydz Bay using the self-organizing map analysis approach |
title_full_unstemmed |
Variations in the summer oceanic p CO 2 and carbon sink in Prydz Bay using the self-organizing map analysis approach |
title_sort |
variations in the summer oceanic p co 2 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://doaj.org/article/46a47d85784f4d128536f7c17ea180e8 |
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_source |
Biogeosciences, Vol 16, Pp 797-810 (2019) |
op_relation |
https://www.biogeosciences.net/16/797/2019/bg-16-797-2019.pdf https://doaj.org/toc/1726-4170 https://doaj.org/toc/1726-4189 doi:10.5194/bg-16-797-2019 1726-4170 1726-4189 https://doaj.org/article/46a47d85784f4d128536f7c17ea180e8 |
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 |
_version_ |
1766174591952093184 |