Internal climate variability modulates decadal changes in ocean anthropogenic carbon storage

The ocean removes man-made (anthropogenic) carbon from the atmosphere and thereby mitigates climate change. Observations from global hydrographic surveys reveal the spatial and temporal evolution of the ocean inventory of anthropogenic carbon and suggest substantial decadal variability in historical...

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Bibliographic Details
Main Authors: Holly C Olivarez, Nicole S Lovenduski, Elizabeth Maroon, Jens D Müller, Amanda R Fay, Kristen M Krumhardt, Michael N Levy, Keith Lindsay, Galen A McKinley, Jamin K Rader
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:Environmental Research Letters
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Online Access:https://doi.org/10.1088/1748-9326/ada2ad
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Summary:The ocean removes man-made (anthropogenic) carbon from the atmosphere and thereby mitigates climate change. Observations from global hydrographic surveys reveal the spatial and temporal evolution of the ocean inventory of anthropogenic carbon and suggest substantial decadal variability in historical storage rates. Here, we use a 100-member ensemble of an Earth system model to investigate the influence of external forcing and internal climate variability on historical changes in ocean anthropogenic carbon storage over 1994 to 2014. Our findings reveal that the externally forced, decadal changes in storage are largest in the Atlantic (2–4 mmol m ^−3 decade ^−1 ) and positive nearly everywhere. Internal climate variability modulates regional ocean anthropogenic carbon storage trends by up to 10 mmol m ^−3 decade ^−1 . The influence of internal climate variability on decadal storage changes is most prominent at depths of ∼300 m and at the edges of the subtropical gyres. Internal variability in anthropogenic carbon in the extratropics has high spectral power on decadal to multi-decadal timescales, indicating that the approximately decadal repetitions of hydrographic surveys may produce storage change estimates that are heavily influenced by internal climate variability.
ISSN:1748-9326