Variability CO2 parameters in the North Atlantic Subtropical Gyre : a neural network approach

Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/91395

Title:	Variability CO2 parameters in the North Atlantic Subtropical Gyre : a neural network approach
Authors:	Galdies, Charles Garcia-Luque, E. Guerra, R.
Keywords:	Waste disposal in the ocean Ships -- Waste disposal Marine pollution Marine debris
Issue Date:	2018
Publisher:	Woods Hole Oceanographic Institution
Citation:	Galdies, C., Garcia-Luque, E., & Guerra, R. (2018). Variability CO2 parameters in the North Atlantic Subtropical Gyre : a neural network approach. Ocean Carbon and Biogeochemistry (OCB) Summer Workshop
Abstract:	Using artificial neural network to derive the variability of the ocean carbonate system during Spring 2016 over the area of study from monthly satellite-derived wind stress (ASCAT), sea surface salinity (SMOS) and sea surface temperature (OISST) fields over the oceans. The predicted variables were dissolved inorganic carbon (DIC), total alkalinity (AT), pHT and partial pressure of ocean surface carbon dioxide (pCO2). Using this approach the components of the seawater carbonate system for springtime 2016 were predicted at high resolution (0.25o x 0.25o) and used to compare against published observations going back since 1988 for the North Atlantic Subtropical Gyre.
URI:	https://www.um.edu.mt/library/oar/handle/123456789/91395
Appears in Collections:	Scholarly Works - InsESEMP

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