School of Environmental Sciences, University of East Anglia, Norwich,
UK
Laboratoire des Sciences du Climat et de l'Environnement (LSCE),
Institut Pierre Simon Laplace (IPSL), CNRS/CEA/UVSQ/Univ. Paris-Saclay, Orme
des Merisiers, Gif-sur-Yvette, 91191, France
Laboratoire des Sciences du Climat et de l'Environnement (LSCE),
Institut Pierre Simon Laplace (IPSL), CNRS/CEA/UVSQ/Univ. Paris-Saclay, Orme
des Merisiers, Gif-sur-Yvette, 91191, France
Laboratoire des Sciences du Climat et de l'Environnement (LSCE),
Institut Pierre Simon Laplace (IPSL), CNRS/CEA/UVSQ/Univ. Paris-Saclay, Orme
des Merisiers, Gif-sur-Yvette, 91191, France
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2,903
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Cumulative views and downloads
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Total article views: 3,087 (including HTML, PDF, and XML)
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2,288
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3,087
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Total article views: 1,056 (including HTML, PDF, and XML)
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615
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Viewed (geographical distribution)
Total article views: 4,143 (including HTML, PDF, and XML)
Thereof 4,000 with geography defined
and 143 with unknown origin.
Total article views: 3,087 (including HTML, PDF, and XML)
Thereof 2,951 with geography defined
and 136 with unknown origin.
Total article views: 1,056 (including HTML, PDF, and XML)
Thereof 1,049 with geography defined
and 7 with unknown origin.
In this work we explored design options for a future Atlantic-scale observational network enabling the release of carbon system estimates by combining data streams from various platforms. We used outputs of a physical–biogeochemical global ocean model at sites of real-world observations to reconstruct surface ocean pCO2 by applying a non-linear feed-forward neural network. The results provide important information for future BGC-Argo deployment, i.e. important regions and the number of floats.
In this work we explored design options for a future Atlantic-scale observational network...
