Robust estimates of the Total Alkalinity from Satellite Oceanographic data in the Global Ocean

Total alkalinity (TA) is a key parameter to understand the dynamics of biogeochemical properties in the global ocean and the effects of climate change on ocean acidification, ocean carbon cycle, and carbonate chemistry. To date, global surface ocean distributions of TA were investigated using multip...

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Bibliographic Details
Published in:IEEE Access
Main Authors: Krishna, Kande Vamsi, Shanmugam, Palanisamy
Format: Article in Journal/Newspaper
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE) 2023
Subjects:
Online Access:https://archimer.ifremer.fr/doc/00835/94687/102100.pdf
https://doi.org/10.1109/ACCESS.2023.3271516
https://archimer.ifremer.fr/doc/00835/94687/
id ftarchimer:oai:archimer.ifremer.fr:94687
record_format openpolar
spelling ftarchimer:oai:archimer.ifremer.fr:94687 2023-12-24T10:23:54+01:00 Robust estimates of the Total Alkalinity from Satellite Oceanographic data in the Global Ocean Krishna, Kande Vamsi Shanmugam, Palanisamy 2023 application/pdf https://archimer.ifremer.fr/doc/00835/94687/102100.pdf https://doi.org/10.1109/ACCESS.2023.3271516 https://archimer.ifremer.fr/doc/00835/94687/ eng eng Institute of Electrical and Electronics Engineers (IEEE) https://archimer.ifremer.fr/doc/00835/94687/102100.pdf doi:10.1109/ACCESS.2023.3271516 https://archimer.ifremer.fr/doc/00835/94687/ info:eu-repo/semantics/openAccess restricted use Ieee Access (2169-3536) (Institute of Electrical and Electronics Engineers (IEEE)), 2023 , Vol. 11 , P. 42824-42838 Oceans Sea surface Sea measurements Satellites Spatiotemporal phenomena Spatial resolution Ocean temperature Climate change Total alkalinity sea surface salinity carbon chemistry global ocean satellite data text Article info:eu-repo/semantics/article 2023 ftarchimer https://doi.org/10.1109/ACCESS.2023.3271516 2023-11-28T23:51:10Z Total alkalinity (TA) is a key parameter to understand the dynamics of biogeochemical properties in the global ocean and the effects of climate change on ocean acidification, ocean carbon cycle, and carbonate chemistry. To date, global surface ocean distributions of TA were investigated using multiple regional regression approaches which require smoothening techniques due to severe boundary effects in different oceanic regions/basins across latitudes/longitudes. To reduce the uncertainties and produce spatially and temporally consistent TA products, a novel single linear regression (SLR) approach was developed in this study to estimate TA fields in the global surface ocean waters. The SLR formulation was derived using the continuous in-situ measurements of sea surface salinity (SSS) collected from the different oceans. The performance of the SLR was assessed using independent in-situ/satellite derived TA data and the results from three existing algorithms. In general, the SLR-based global surface ocean TA fields from both in-situ and satellite data agreed well with in-situ measured TA data with a mean relative error less than 1%, which is much lower compared to the error with the existing algorithms. Studies were also conducted to examine the spatiotemporal variability and trends in the global surface ocean climatology of SSS and TA fields in the context of current climate change impacts. Article in Journal/Newspaper Ocean acidification Archimer (Archive Institutionnelle de l'Ifremer - Institut français de recherche pour l'exploitation de la mer) IEEE Access 11 42824 42838
institution Open Polar
collection Archimer (Archive Institutionnelle de l'Ifremer - Institut français de recherche pour l'exploitation de la mer)
op_collection_id ftarchimer
language English
topic Oceans
Sea surface
Sea measurements
Satellites
Spatiotemporal phenomena
Spatial resolution
Ocean temperature
Climate change
Total alkalinity
sea surface salinity
carbon chemistry
global ocean
satellite data
spellingShingle Oceans
Sea surface
Sea measurements
Satellites
Spatiotemporal phenomena
Spatial resolution
Ocean temperature
Climate change
Total alkalinity
sea surface salinity
carbon chemistry
global ocean
satellite data
Krishna, Kande Vamsi
Shanmugam, Palanisamy
Robust estimates of the Total Alkalinity from Satellite Oceanographic data in the Global Ocean
topic_facet Oceans
Sea surface
Sea measurements
Satellites
Spatiotemporal phenomena
Spatial resolution
Ocean temperature
Climate change
Total alkalinity
sea surface salinity
carbon chemistry
global ocean
satellite data
description Total alkalinity (TA) is a key parameter to understand the dynamics of biogeochemical properties in the global ocean and the effects of climate change on ocean acidification, ocean carbon cycle, and carbonate chemistry. To date, global surface ocean distributions of TA were investigated using multiple regional regression approaches which require smoothening techniques due to severe boundary effects in different oceanic regions/basins across latitudes/longitudes. To reduce the uncertainties and produce spatially and temporally consistent TA products, a novel single linear regression (SLR) approach was developed in this study to estimate TA fields in the global surface ocean waters. The SLR formulation was derived using the continuous in-situ measurements of sea surface salinity (SSS) collected from the different oceans. The performance of the SLR was assessed using independent in-situ/satellite derived TA data and the results from three existing algorithms. In general, the SLR-based global surface ocean TA fields from both in-situ and satellite data agreed well with in-situ measured TA data with a mean relative error less than 1%, which is much lower compared to the error with the existing algorithms. Studies were also conducted to examine the spatiotemporal variability and trends in the global surface ocean climatology of SSS and TA fields in the context of current climate change impacts.
format Article in Journal/Newspaper
author Krishna, Kande Vamsi
Shanmugam, Palanisamy
author_facet Krishna, Kande Vamsi
Shanmugam, Palanisamy
author_sort Krishna, Kande Vamsi
title Robust estimates of the Total Alkalinity from Satellite Oceanographic data in the Global Ocean
title_short Robust estimates of the Total Alkalinity from Satellite Oceanographic data in the Global Ocean
title_full Robust estimates of the Total Alkalinity from Satellite Oceanographic data in the Global Ocean
title_fullStr Robust estimates of the Total Alkalinity from Satellite Oceanographic data in the Global Ocean
title_full_unstemmed Robust estimates of the Total Alkalinity from Satellite Oceanographic data in the Global Ocean
title_sort robust estimates of the total alkalinity from satellite oceanographic data in the global ocean
publisher Institute of Electrical and Electronics Engineers (IEEE)
publishDate 2023
url https://archimer.ifremer.fr/doc/00835/94687/102100.pdf
https://doi.org/10.1109/ACCESS.2023.3271516
https://archimer.ifremer.fr/doc/00835/94687/
genre Ocean acidification
genre_facet Ocean acidification
op_source Ieee Access (2169-3536) (Institute of Electrical and Electronics Engineers (IEEE)), 2023 , Vol. 11 , P. 42824-42838
op_relation https://archimer.ifremer.fr/doc/00835/94687/102100.pdf
doi:10.1109/ACCESS.2023.3271516
https://archimer.ifremer.fr/doc/00835/94687/
op_rights info:eu-repo/semantics/openAccess
restricted use
op_doi https://doi.org/10.1109/ACCESS.2023.3271516
container_title IEEE Access
container_volume 11
container_start_page 42824
op_container_end_page 42838
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