The sensitivity of p CO 2 reconstructions to sampling scales across a Southern Ocean sub-domain: a semi-idealized ocean sampling simulation approach
The Southern Ocean is a complex system yet is sparsely sampled in both space and time. These factors raise questions about the confidence in present sampling strategies and associated machine learning (ML) reconstructions. Previous studies have not yielded a clear understanding of the origin of unce...
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Copernicus Publications
2022
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ftdoajarticles:oai:doaj.org/article:2c99341eaafe4e46b0bac103b125b0a3 2023-05-15T13:54:48+02:00 The sensitivity of p CO 2 reconstructions to sampling scales across a Southern Ocean sub-domain: a semi-idealized ocean sampling simulation approach L. M. Djeutchouang N. Chang L. Gregor M. Vichi P. M. S. Monteiro 2022-09-01T00:00:00Z https://doi.org/10.5194/bg-19-4171-2022 https://doaj.org/article/2c99341eaafe4e46b0bac103b125b0a3 EN eng Copernicus Publications https://bg.copernicus.org/articles/19/4171/2022/bg-19-4171-2022.pdf https://doaj.org/toc/1726-4170 https://doaj.org/toc/1726-4189 doi:10.5194/bg-19-4171-2022 1726-4170 1726-4189 https://doaj.org/article/2c99341eaafe4e46b0bac103b125b0a3 Biogeosciences, Vol 19, Pp 4171-4195 (2022) Ecology QH540-549.5 Life QH501-531 Geology QE1-996.5 article 2022 ftdoajarticles https://doi.org/10.5194/bg-19-4171-2022 2022-12-31T00:28:49Z The Southern Ocean is a complex system yet is sparsely sampled in both space and time. These factors raise questions about the confidence in present sampling strategies and associated machine learning (ML) reconstructions. Previous studies have not yielded a clear understanding of the origin of uncertainties and biases for the reconstructions of the partial pressure of carbon dioxide ( p CO 2 ) at the surface ocean ( <math xmlns="http://www.w3.org/1998/Math/MathML" id="M7" display="inline" overflow="scroll" dspmath="mathml"><mrow><mi>p</mi><msubsup><mi mathvariant="normal">CO</mi><mn mathvariant="normal">2</mn><mi mathvariant="normal">ocean</mi></msubsup></mrow></math> <svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="47pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="384f359723e12c1d22fe40db07699d29"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="bg-19-4171-2022-ie00001.svg" width="47pt" height="15pt" src="bg-19-4171-2022-ie00001.png"/></svg:svg> ). We examine these questions through a series of semi-idealized observing system simulation experiments (OSSEs) using a high-resolution ( ± 10 km) coupled physical and biogeochemical model (NEMO-PISCES, Nucleus for European Modelling of the Ocean, Pelagic Interactions Scheme for Carbon and Ecosystem Studies). Here we choose 1 year of the model sub-domain of 10 ∘ of latitude (40–50 ∘ S) by 20 ∘ of longitude (10 ∘ W–10 ∘ E). This domain is crossed by the sub-Antarctic front and thus includes both the sub-Antarctic zone and the polar frontal zone in the south-east Atlantic Ocean, which are the two most sampled sub-regions of the Southern Ocean. We show that while this sub-domain is small relative to the Southern Ocean scales, it is representative of the scales of variability we aim to examine. The OSSEs simulated the observational scales of <math xmlns="http://www.w3.org/1998/Math/MathML" id="M14" display="inline" ... Article in Journal/Newspaper Antarc* Antarctic Southern Ocean Directory of Open Access Journals: DOAJ Articles Antarctic Southern Ocean Biogeosciences 19 17 4171 4195 |
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 |
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Ecology QH540-549.5 Life QH501-531 Geology QE1-996.5 L. M. Djeutchouang N. Chang L. Gregor M. Vichi P. M. S. Monteiro The sensitivity of p CO 2 reconstructions to sampling scales across a Southern Ocean sub-domain: a semi-idealized ocean sampling simulation approach |
topic_facet |
Ecology QH540-549.5 Life QH501-531 Geology QE1-996.5 |
description |
The Southern Ocean is a complex system yet is sparsely sampled in both space and time. These factors raise questions about the confidence in present sampling strategies and associated machine learning (ML) reconstructions. Previous studies have not yielded a clear understanding of the origin of uncertainties and biases for the reconstructions of the partial pressure of carbon dioxide ( p CO 2 ) at the surface ocean ( <math xmlns="http://www.w3.org/1998/Math/MathML" id="M7" display="inline" overflow="scroll" dspmath="mathml"><mrow><mi>p</mi><msubsup><mi mathvariant="normal">CO</mi><mn mathvariant="normal">2</mn><mi mathvariant="normal">ocean</mi></msubsup></mrow></math> <svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="47pt" height="15pt" class="svg-formula" dspmath="mathimg" md5hash="384f359723e12c1d22fe40db07699d29"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="bg-19-4171-2022-ie00001.svg" width="47pt" height="15pt" src="bg-19-4171-2022-ie00001.png"/></svg:svg> ). We examine these questions through a series of semi-idealized observing system simulation experiments (OSSEs) using a high-resolution ( ± 10 km) coupled physical and biogeochemical model (NEMO-PISCES, Nucleus for European Modelling of the Ocean, Pelagic Interactions Scheme for Carbon and Ecosystem Studies). Here we choose 1 year of the model sub-domain of 10 ∘ of latitude (40–50 ∘ S) by 20 ∘ of longitude (10 ∘ W–10 ∘ E). This domain is crossed by the sub-Antarctic front and thus includes both the sub-Antarctic zone and the polar frontal zone in the south-east Atlantic Ocean, which are the two most sampled sub-regions of the Southern Ocean. We show that while this sub-domain is small relative to the Southern Ocean scales, it is representative of the scales of variability we aim to examine. The OSSEs simulated the observational scales of <math xmlns="http://www.w3.org/1998/Math/MathML" id="M14" display="inline" ... |
format |
Article in Journal/Newspaper |
author |
L. M. Djeutchouang N. Chang L. Gregor M. Vichi P. M. S. Monteiro |
author_facet |
L. M. Djeutchouang N. Chang L. Gregor M. Vichi P. M. S. Monteiro |
author_sort |
L. M. Djeutchouang |
title |
The sensitivity of p CO 2 reconstructions to sampling scales across a Southern Ocean sub-domain: a semi-idealized ocean sampling simulation approach |
title_short |
The sensitivity of p CO 2 reconstructions to sampling scales across a Southern Ocean sub-domain: a semi-idealized ocean sampling simulation approach |
title_full |
The sensitivity of p CO 2 reconstructions to sampling scales across a Southern Ocean sub-domain: a semi-idealized ocean sampling simulation approach |
title_fullStr |
The sensitivity of p CO 2 reconstructions to sampling scales across a Southern Ocean sub-domain: a semi-idealized ocean sampling simulation approach |
title_full_unstemmed |
The sensitivity of p CO 2 reconstructions to sampling scales across a Southern Ocean sub-domain: a semi-idealized ocean sampling simulation approach |
title_sort |
sensitivity of p co 2 reconstructions to sampling scales across a southern ocean sub-domain: a semi-idealized ocean sampling simulation approach |
publisher |
Copernicus Publications |
publishDate |
2022 |
url |
https://doi.org/10.5194/bg-19-4171-2022 https://doaj.org/article/2c99341eaafe4e46b0bac103b125b0a3 |
geographic |
Antarctic Southern Ocean |
geographic_facet |
Antarctic Southern Ocean |
genre |
Antarc* Antarctic Southern Ocean |
genre_facet |
Antarc* Antarctic Southern Ocean |
op_source |
Biogeosciences, Vol 19, Pp 4171-4195 (2022) |
op_relation |
https://bg.copernicus.org/articles/19/4171/2022/bg-19-4171-2022.pdf https://doaj.org/toc/1726-4170 https://doaj.org/toc/1726-4189 doi:10.5194/bg-19-4171-2022 1726-4170 1726-4189 https://doaj.org/article/2c99341eaafe4e46b0bac103b125b0a3 |
op_doi |
https://doi.org/10.5194/bg-19-4171-2022 |
container_title |
Biogeosciences |
container_volume |
19 |
container_issue |
17 |
container_start_page |
4171 |
op_container_end_page |
4195 |
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1766260915025477632 |