Global high-resolution monthly p CO 2 climatology for the coastal ocean derived from neural network interpolation

In spite of the recent strong increase in the number of measurements of the partial pressure of CO 2 in the surface ocean ( p CO 2 ), the air–sea CO 2 balance of the continental shelf seas remains poorly quantified. This is a consequence of these regions remaining strongly under-sampled in both time...

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Published in:Biogeosciences
Main Authors: G. G. Laruelle, P. Landschützer, N. Gruber, J.-L. Tison, B. Delille, P. Regnier
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2017
Subjects:
Online Access:https://doi.org/10.5194/bg-14-4545-2017
https://doaj.org/article/bcea6ade62ba42298ed14f7a1a34f40e
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spelling ftdoajarticles:oai:doaj.org/article:bcea6ade62ba42298ed14f7a1a34f40e 2023-05-15T18:18:56+02:00 Global high-resolution monthly p CO 2 climatology for the coastal ocean derived from neural network interpolation G. G. Laruelle P. Landschützer N. Gruber J.-L. Tison B. Delille P. Regnier 2017-10-01T00:00:00Z https://doi.org/10.5194/bg-14-4545-2017 https://doaj.org/article/bcea6ade62ba42298ed14f7a1a34f40e EN eng Copernicus Publications https://www.biogeosciences.net/14/4545/2017/bg-14-4545-2017.pdf https://doaj.org/toc/1726-4170 https://doaj.org/toc/1726-4189 doi:10.5194/bg-14-4545-2017 1726-4170 1726-4189 https://doaj.org/article/bcea6ade62ba42298ed14f7a1a34f40e Biogeosciences, Vol 14, Pp 4545-4561 (2017) Ecology QH540-549.5 Life QH501-531 Geology QE1-996.5 article 2017 ftdoajarticles https://doi.org/10.5194/bg-14-4545-2017 2022-12-31T09:54:09Z In spite of the recent strong increase in the number of measurements of the partial pressure of CO 2 in the surface ocean ( p CO 2 ), the air–sea CO 2 balance of the continental shelf seas remains poorly quantified. This is a consequence of these regions remaining strongly under-sampled in both time and space and of surface p CO 2 exhibiting much higher temporal and spatial variability in these regions compared to the open ocean. Here, we use a modified version of a two-step artificial neural network method (SOM-FFN; Landschützer et al., 2013) to interpolate the p CO 2 data along the continental margins with a spatial resolution of 0.25° and with monthly resolution from 1998 to 2015. The most important modifications compared to the original SOM-FFN method are (i) the much higher spatial resolution and (ii) the inclusion of sea ice and wind speed as predictors of p CO 2 . The SOM-FFN is first trained with p CO 2 measurements extracted from the SOCATv4 database. Then, the validity of our interpolation, in both space and time, is assessed by comparing the generated p CO 2 field with independent data extracted from the LDVEO2015 database. The new coastal p CO 2 product confirms a previously suggested general meridional trend of the annual mean p CO 2 in all the continental shelves with high values in the tropics and dropping to values beneath those of the atmosphere at higher latitudes. The monthly resolution of our data product permits us to reveal significant differences in the seasonality of p CO 2 across the ocean basins. The shelves of the western and northern Pacific, as well as the shelves in the temperate northern Atlantic, display particularly pronounced seasonal variations in p CO 2, while the shelves in the southeastern Atlantic and in the southern Pacific reveal a much smaller seasonality. The calculation of temperature normalized p CO 2 for several latitudes in different oceanic basins confirms that the seasonality in shelf p CO 2 cannot solely be explained by temperature-induced changes in solubility ... Article in Journal/Newspaper Sea ice Directory of Open Access Journals: DOAJ Articles Pacific Biogeosciences 14 19 4545 4561
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
G. G. Laruelle
P. Landschützer
N. Gruber
J.-L. Tison
B. Delille
P. Regnier
Global high-resolution monthly p CO 2 climatology for the coastal ocean derived from neural network interpolation
topic_facet Ecology
QH540-549.5
Life
QH501-531
Geology
QE1-996.5
description In spite of the recent strong increase in the number of measurements of the partial pressure of CO 2 in the surface ocean ( p CO 2 ), the air–sea CO 2 balance of the continental shelf seas remains poorly quantified. This is a consequence of these regions remaining strongly under-sampled in both time and space and of surface p CO 2 exhibiting much higher temporal and spatial variability in these regions compared to the open ocean. Here, we use a modified version of a two-step artificial neural network method (SOM-FFN; Landschützer et al., 2013) to interpolate the p CO 2 data along the continental margins with a spatial resolution of 0.25° and with monthly resolution from 1998 to 2015. The most important modifications compared to the original SOM-FFN method are (i) the much higher spatial resolution and (ii) the inclusion of sea ice and wind speed as predictors of p CO 2 . The SOM-FFN is first trained with p CO 2 measurements extracted from the SOCATv4 database. Then, the validity of our interpolation, in both space and time, is assessed by comparing the generated p CO 2 field with independent data extracted from the LDVEO2015 database. The new coastal p CO 2 product confirms a previously suggested general meridional trend of the annual mean p CO 2 in all the continental shelves with high values in the tropics and dropping to values beneath those of the atmosphere at higher latitudes. The monthly resolution of our data product permits us to reveal significant differences in the seasonality of p CO 2 across the ocean basins. The shelves of the western and northern Pacific, as well as the shelves in the temperate northern Atlantic, display particularly pronounced seasonal variations in p CO 2, while the shelves in the southeastern Atlantic and in the southern Pacific reveal a much smaller seasonality. The calculation of temperature normalized p CO 2 for several latitudes in different oceanic basins confirms that the seasonality in shelf p CO 2 cannot solely be explained by temperature-induced changes in solubility ...
format Article in Journal/Newspaper
author G. G. Laruelle
P. Landschützer
N. Gruber
J.-L. Tison
B. Delille
P. Regnier
author_facet G. G. Laruelle
P. Landschützer
N. Gruber
J.-L. Tison
B. Delille
P. Regnier
author_sort G. G. Laruelle
title Global high-resolution monthly p CO 2 climatology for the coastal ocean derived from neural network interpolation
title_short Global high-resolution monthly p CO 2 climatology for the coastal ocean derived from neural network interpolation
title_full Global high-resolution monthly p CO 2 climatology for the coastal ocean derived from neural network interpolation
title_fullStr Global high-resolution monthly p CO 2 climatology for the coastal ocean derived from neural network interpolation
title_full_unstemmed Global high-resolution monthly p CO 2 climatology for the coastal ocean derived from neural network interpolation
title_sort global high-resolution monthly p co 2 climatology for the coastal ocean derived from neural network interpolation
publisher Copernicus Publications
publishDate 2017
url https://doi.org/10.5194/bg-14-4545-2017
https://doaj.org/article/bcea6ade62ba42298ed14f7a1a34f40e
geographic Pacific
geographic_facet Pacific
genre Sea ice
genre_facet Sea ice
op_source Biogeosciences, Vol 14, Pp 4545-4561 (2017)
op_relation https://www.biogeosciences.net/14/4545/2017/bg-14-4545-2017.pdf
https://doaj.org/toc/1726-4170
https://doaj.org/toc/1726-4189
doi:10.5194/bg-14-4545-2017
1726-4170
1726-4189
https://doaj.org/article/bcea6ade62ba42298ed14f7a1a34f40e
op_doi https://doi.org/10.5194/bg-14-4545-2017
container_title Biogeosciences
container_volume 14
container_issue 19
container_start_page 4545
op_container_end_page 4561
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