Global high-resolution monthly pCO2 climatology for the coastal ocean derived from neural network in...
Global high-resolution monthly pCO2 climatology for the coastal ocean derived from neural network interpolation
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Publisher
Katlenburg-Lindau: Copernicus GmbH
Journal title
Language
English
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Publisher
Katlenburg-Lindau: Copernicus GmbH
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Scope and Contents
Contents
In spite of the recent strong increase in the number of measurements of the partial pressure of CO2 in the surface ocean (pCO2), the air–sea CO2 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 pCO2 exhibiting much higher te...
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Full title
Global high-resolution monthly pCO2 climatology for the coastal ocean derived from neural network interpolation
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Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_bcea6ade62ba42298ed14f7a1a34f40e
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_bcea6ade62ba42298ed14f7a1a34f40e
Other Identifiers
ISSN
1726-4170,1726-4189
E-ISSN
1726-4189
DOI
10.5194/bg-14-4545-2017
