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

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 d...

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Main Authors: Galdies, Charles, Garcia-Luque, E., Guerra, R., Ocean Carbon and Biogeochemistry (OCB) Summer Workshop
Format: Conference Object
Language:English
Published: Woods Hole Oceanographic Institution 2018
Subjects:
Waste disposal in the ocean
Ships > Waste disposal
Marine pollution
Marine debris
North Atlantic
Online Access:https://www.um.edu.mt/library/oar/handle/123456789/91395
id ftunivmalta:oai:www.um.edu.mt:123456789/91395
record_format openpolar
spelling ftunivmalta:oai:www.um.edu.mt:123456789/91395 2023-05-15T17:28:28+02:00 Variability CO2 parameters in the North Atlantic Subtropical Gyre : a neural network approach Galdies, Charles Garcia-Luque, E. Guerra, R. Ocean Carbon and Biogeochemistry (OCB) Summer Workshop 2018 https://www.um.edu.mt/library/oar/handle/123456789/91395 en eng Woods Hole Oceanographic Institution 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 https://www.um.edu.mt/library/oar/handle/123456789/91395 info:eu-repo/semantics/openAccess The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder. Waste disposal in the ocean Ships -- Waste disposal Marine pollution Marine debris conferenceObject 2018 ftunivmalta 2022-03-16T18:06:37Z 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. N/A Conference Object North Atlantic University of Malta: OAR@UM
institution Open Polar
collection University of Malta: OAR@UM
op_collection_id ftunivmalta
language English
topic Waste disposal in the ocean
Ships -- Waste disposal
Marine pollution
Marine debris
spellingShingle Waste disposal in the ocean
Ships -- Waste disposal
Marine pollution
Marine debris
Galdies, Charles
Garcia-Luque, E.
Guerra, R.
Ocean Carbon and Biogeochemistry (OCB) Summer Workshop
Variability CO2 parameters in the North Atlantic Subtropical Gyre : a neural network approach
topic_facet Waste disposal in the ocean
Ships -- Waste disposal
Marine pollution
Marine debris
description 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. N/A
format Conference Object
author Galdies, Charles
Garcia-Luque, E.
Guerra, R.
Ocean Carbon and Biogeochemistry (OCB) Summer Workshop
author_facet Galdies, Charles
Garcia-Luque, E.
Guerra, R.
Ocean Carbon and Biogeochemistry (OCB) Summer Workshop
author_sort Galdies, Charles
title Variability CO2 parameters in the North Atlantic Subtropical Gyre : a neural network approach
title_short Variability CO2 parameters in the North Atlantic Subtropical Gyre : a neural network approach
title_full Variability CO2 parameters in the North Atlantic Subtropical Gyre : a neural network approach
title_fullStr Variability CO2 parameters in the North Atlantic Subtropical Gyre : a neural network approach
title_full_unstemmed Variability CO2 parameters in the North Atlantic Subtropical Gyre : a neural network approach
title_sort variability co2 parameters in the north atlantic subtropical gyre : a neural network approach
publisher Woods Hole Oceanographic Institution
publishDate 2018
url https://www.um.edu.mt/library/oar/handle/123456789/91395
genre North Atlantic
genre_facet North Atlantic
op_relation 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
https://www.um.edu.mt/library/oar/handle/123456789/91395
op_rights info:eu-repo/semantics/openAccess
The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder.
_version_ 1766121179759771648

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