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| Bittig, Henry C.; Steinhoff, Tobias; Claustre, Harve; Fiedler, Bjoern; Williams, Nancy L.; Sauzede, Raphaelle; Koertzinger, Arne; Gattuso, Jean-pierre. |
| This work presents two new methods to estimate oceanic alkalinity (A(T)), dissolved inorganic carbon (C-T), pH, and pCO(2) from temperature, salinity, oxygen, and geolocation data. "CANYON-B" is a Bayesian neural network mapping that accurately reproduces GLODAPv2 bottle data and the biogeochemical relations contained therein. "CONTENT" combines and refines the four carbonate system variables to be consistent with carbonate chemistry. Both methods come with a robust uncertainty estimate that incorporates information from the local conditions. They are validated against independent GO-SHIP bottle and sensor data, and compare favorably to other state-of-the-art mapping methods. As "dynamic climatologies" they show comparable performance to classical... |
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Palavras-chave: Carbon cycle; GLODAP; Marine carbonate system; Surface pCO(2) climatology; Revelle buffer factor increase; Machine learning; Nutrient estimation. |
| Ano: 2018 |
URL: https://archimer.ifremer.fr/doc/00675/78681/80879.pdf |
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| Sauzede, Raphaelle; Claustre, Hervé; Bittig, Henry; Pasqueron De Fommervault, Orens; Gattuso, Jean-pierre; Legendre, Louis; Johnson, Kenneth S. |
| A neural network-based method (CANYON: CArbonate system and Nutrients concentration from hYdrological properties and Oxygen using a Neural-network) was developed to estimate water-column biogeochemically relevant variables in the Global Ocean. These are the concentrations of 3 nutrients [nitrate (NO3−), phosphate (PO43−) and silicate (Si(OH)4)] and 4 carbonate system parameters [total alkalinity (AT), dissolved inorganic carbon (CT), pH (pHT) and partial pressure of CO2 (pCO2)], which are estimated from concurrent in situ measurements of temperature, salinity, hydrostatic pressure and oxygen (O2) together with sampling latitude, longitude and date. Seven neural-networks were developed using the GLODAPv2 database, which is largely representative of the... |
| Tipo: Text |
Palavras-chave: Neural network; Nutrients; Carbonate system; Global ocean; GLODAPv2 database; Profiling floats. |
| Ano: 2017 |
URL: https://archimer.ifremer.fr/doc/00383/49467/49952.pdf |
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| Sarthou, Geraldine; Lherminier, Pascale; Achterberg, Eric P.; Alonso-perez, Fernando; Bucciarelli, Eva; Boutorh, Julia; Bouvier, Vincent; Boyle, Edward A.; Branellec, Pierre; Carracedo, Lidia I.; Casacuberta, Nuria; Castrillejo, Maxi; Cheize, Marie; Pereira, Leonardo Contreira; Cossa, Daniel; Daniault, Nathalie; De Saint-leger, Emmanuel; Dehairs, Frank; Deng, Feifei; De Gesincourt, Floriane Desprez; Devesa, Jeremy; Foliot, Lorna; Fonseca-batista, Debany; Gallinari, Morgane; Garcia-ibanez, Maribel I.; Gourain, Arthur; Grossteffan, Emilie; Hamon, Michel; Heimburger, Lars Eric; Henderson, Gideon M.; Jeandel, Catherine; Kermabon, Catherine; Lacan, Francois; Le Bot, Philippe; Le Goff, Manon; Le Roy, Emilie; Lefebvre, Alison; Leizour, Stephane; Lemaitre, Nolwenn; Masque, Pere; Menage, Olivier; Barraqueta, Jan-lukas Menzel; Mercier, Herle; Perault, Fabien; Perez, Fiz F; Planquette, Helene; Planchon, Frederic; Roukaerts, Arnout; Sanial, Virginie; Sauzede, Raphaelle; Schmechtig, Catherine; Shelley, Rachel U.; Stewart, Gillian; Sutton, Jill; Tang, Yi; Tisnerat-laborde, Nadine; Tonnard, Manon; Treguer, Paul; Van Beek, Pieter; Zurbrick, Cheryl M.; Zunino Rodriguez, Patricia. |
| The GEOVIDE cruise, a collaborative project within the framework of the international GEOTRACES programme, was conducted along the French-led section in the North Atlantic Ocean (Section GA01), between 15 May and 30 June 2014. In this special issue (https://www.biogeosciences.net/special_ issue900.html), results from GEOVIDE, including physical oceanography and trace element and isotope cyclings, are presented among 18 articles. Here, the scientific context, project objectives, and scientific strategy of GEOVIDE are provided, along with an overview of the main results from the articles published in the special issue. |
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| Ano: 2018 |
URL: https://archimer.ifremer.fr/doc/00470/58178/60685.pdf |
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