Detecting regional modes of variability in observation-based surface ocean pCO2

We use a neural network-based estimate of the sea surface partial pressure of CO 2 (pCO 2 ) derived from measurements assembled within the Surface Ocean CO 2 Atlas to investigate the dominant modes of pCO 2 variability from 1982 through 2015. Our analysis shows that detrended and deseasonalized sea...

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Published in:Geophysical Research Letters
Main Authors: Landschützer, P., Ilyina, T., Lovenduski, N.
Format: Article in Journal/Newspaper
Language:English
Published: 2019
Subjects:
Online Access:http://hdl.handle.net/21.11116/0000-0003-3900-D
http://hdl.handle.net/21.11116/0000-0003-5FC2-8
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spelling ftpubman:oai:pure.mpg.de:item_3034947 2023-08-27T04:10:53+02:00 Detecting regional modes of variability in observation-based surface ocean pCO2 Landschützer, P. Ilyina, T. Lovenduski, N. 2019-03-16 application/pdf http://hdl.handle.net/21.11116/0000-0003-3900-D http://hdl.handle.net/21.11116/0000-0003-5FC2-8 eng eng info:eu-repo/grantAgreement/EC/H2020/641816 info:eu-repo/semantics/altIdentifier/doi/10.1029/2018GL081756 http://hdl.handle.net/21.11116/0000-0003-3900-D http://hdl.handle.net/21.11116/0000-0003-5FC2-8 info:eu-repo/semantics/openAccess Geophysical Research Letters info:eu-repo/semantics/article 2019 ftpubman https://doi.org/10.1029/2018GL081756 2023-08-02T01:23:14Z We use a neural network-based estimate of the sea surface partial pressure of CO 2 (pCO 2 ) derived from measurements assembled within the Surface Ocean CO 2 Atlas to investigate the dominant modes of pCO 2 variability from 1982 through 2015. Our analysis shows that detrended and deseasonalized sea surface pCO 2 varies substantially by region and the respective frequencies match those from the major modes of climate variability (Atlantic Multidecadal Oscillation, Pacific Decadal Oscillation, multivariate ENSO index, Southern Annular Mode), suggesting a climate modulated air-sea exchange of CO 2 . We find that most of the regional pCO 2 variability is driven by changes in the ocean circulation and/or changes in biology, whereas the North Atlantic variability is tightly linked to temperature variations in the surface ocean and the resulting changes in solubility. Despite the 34-year time series, our analysis reveals that we can currently only detect one to two periods of slow frequency oscillations, challenging our ability to robustly link pCO 2 variations to climate variability. ©2019. American Geophysical Union. All Rights Reserved. Article in Journal/Newspaper North Atlantic Max Planck Society: MPG.PuRe Pacific Geophysical Research Letters 46 5 2670 2679
institution Open Polar
collection Max Planck Society: MPG.PuRe
op_collection_id ftpubman
language English
description We use a neural network-based estimate of the sea surface partial pressure of CO 2 (pCO 2 ) derived from measurements assembled within the Surface Ocean CO 2 Atlas to investigate the dominant modes of pCO 2 variability from 1982 through 2015. Our analysis shows that detrended and deseasonalized sea surface pCO 2 varies substantially by region and the respective frequencies match those from the major modes of climate variability (Atlantic Multidecadal Oscillation, Pacific Decadal Oscillation, multivariate ENSO index, Southern Annular Mode), suggesting a climate modulated air-sea exchange of CO 2 . We find that most of the regional pCO 2 variability is driven by changes in the ocean circulation and/or changes in biology, whereas the North Atlantic variability is tightly linked to temperature variations in the surface ocean and the resulting changes in solubility. Despite the 34-year time series, our analysis reveals that we can currently only detect one to two periods of slow frequency oscillations, challenging our ability to robustly link pCO 2 variations to climate variability. ©2019. American Geophysical Union. All Rights Reserved.
format Article in Journal/Newspaper
author Landschützer, P.
Ilyina, T.
Lovenduski, N.
spellingShingle Landschützer, P.
Ilyina, T.
Lovenduski, N.
Detecting regional modes of variability in observation-based surface ocean pCO2
author_facet Landschützer, P.
Ilyina, T.
Lovenduski, N.
author_sort Landschützer, P.
title Detecting regional modes of variability in observation-based surface ocean pCO2
title_short Detecting regional modes of variability in observation-based surface ocean pCO2
title_full Detecting regional modes of variability in observation-based surface ocean pCO2
title_fullStr Detecting regional modes of variability in observation-based surface ocean pCO2
title_full_unstemmed Detecting regional modes of variability in observation-based surface ocean pCO2
title_sort detecting regional modes of variability in observation-based surface ocean pco2
publishDate 2019
url http://hdl.handle.net/21.11116/0000-0003-3900-D
http://hdl.handle.net/21.11116/0000-0003-5FC2-8
geographic Pacific
geographic_facet Pacific
genre North Atlantic
genre_facet North Atlantic
op_source Geophysical Research Letters
op_relation info:eu-repo/grantAgreement/EC/H2020/641816
info:eu-repo/semantics/altIdentifier/doi/10.1029/2018GL081756
http://hdl.handle.net/21.11116/0000-0003-3900-D
http://hdl.handle.net/21.11116/0000-0003-5FC2-8
op_rights info:eu-repo/semantics/openAccess
op_doi https://doi.org/10.1029/2018GL081756
container_title Geophysical Research Letters
container_volume 46
container_issue 5
container_start_page 2670
op_container_end_page 2679
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