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Estimates of Water-Column Nutrient Concentrations and Carbonate System Parameters in the Global Ocean: A Novel Approach Based on Neural Networks ArchiMer
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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