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: Laruelle, G.G., Landschützer, P., Gruber, N., Tison, J.-L., Delille, B., Regnier, P.
Format: Article in Journal/Newspaper
Language:English
Published: 2017
Subjects:
Online Access:https://www.vliz.be/imisdocs/publications/313391.pdf
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spelling ftvliz:oai:oma.vliz.be:295561 2023-05-15T18:19:01+02:00 Global high-resolution monthly p CO 2 climatology for the coastal ocean derived from neural network interpolation Laruelle, G.G. Landschützer, P. Gruber, N. Tison, J.-L. Delille, B. Regnier, P. 2017 application/pdf https://www.vliz.be/imisdocs/publications/313391.pdf en eng info:eu-repo/semantics/altIdentifier/wos/000412902300002 info:eu-repo/semantics/altIdentifier/doi/doi.org/10.5194/bg-14-4545-2017 https://www.vliz.be/imisdocs/publications/313391.pdf info:eu-repo/semantics/openAccess %3Ci%3EBiogeosciences+14%2819%29%3C%2Fi%3E%3A+4545-4561.+%3Ca+href%3D%22https%3A%2F%2Fdx.doi.org%2F10.5194%2Fbg-14-4545-2017%22+target%3D%22_blank%22%3Ehttps%3A%2F%2Fdx.doi.org%2F10.5194%2Fbg-14-4545-2017%3C%2Fa%3E info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion 2017 ftvliz https://doi.org/10.5194/bg-14-4545-2017 2022-05-01T10:59:44Z 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 but are also the result of seasonal changes in circulation, mixing and biological productivity. Our results also reveal that the amplitudes of both thermal and nonthermal seasonal variations in p CO 2 are significantly larger at high latitudes. Finally, because this product's spatial extent includes parts of the open ocean as well, it can be readily merged with existing global open-ocean products to produce a true global perspective of the spatial and temporal variability of surface ocean p CO 2 . Article in Journal/Newspaper Sea ice Flanders Marine Institute (VLIZ): Open Marine Archive (OMA) Pacific Biogeosciences 14 19 4545 4561
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collection Flanders Marine Institute (VLIZ): Open Marine Archive (OMA)
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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 but are also the result of seasonal changes in circulation, mixing and biological productivity. Our results also reveal that the amplitudes of both thermal and nonthermal seasonal variations in p CO 2 are significantly larger at high latitudes. Finally, because this product's spatial extent includes parts of the open ocean as well, it can be readily merged with existing global open-ocean products to produce a true global perspective of the spatial and temporal variability of surface ocean p CO 2 .
format Article in Journal/Newspaper
author Laruelle, G.G.
Landschützer, P.
Gruber, N.
Tison, J.-L.
Delille, B.
Regnier, P.
spellingShingle Laruelle, G.G.
Landschützer, P.
Gruber, N.
Tison, J.-L.
Delille, B.
Regnier, P.
Global high-resolution monthly p CO 2 climatology for the coastal ocean derived from neural network interpolation
author_facet Laruelle, G.G.
Landschützer, P.
Gruber, N.
Tison, J.-L.
Delille, B.
Regnier, P.
author_sort Laruelle, G.G.
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
publishDate 2017
url https://www.vliz.be/imisdocs/publications/313391.pdf
geographic Pacific
geographic_facet Pacific
genre Sea ice
genre_facet Sea ice
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container_title Biogeosciences
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