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  • 1
    Publication Date: 2024-02-07
    Description: The oceanic uptake and resulting storage of the anthropogenic CO2 (Cant) that humans have emitted into the atmosphere moderates climate change. Yet our knowledge about how this uptake and storage has progressed in time remained limited. Here, we determine decadal trends in the storage of Cant by applying the eMLR(C*) regression method to ocean interior observations collected repeatedly since the 1990s. We find that the global ocean storage of Cant grew from 1994 to 2004 by 29 ± 3 Pg C dec−1 and from 2004 to 2014 by 27 ± 3 Pg C dec−1 (±1σ). The storage change in the second decade is about 15 ± 11% lower than one would expect from the first decade and assuming proportional increase with atmospheric CO2. We attribute this reduction in sensitivity to a decrease of the ocean buffer capacity and changes in ocean circulation. In the Atlantic Ocean, the maximum storage rate shifted from the Northern to the Southern Hemisphere, plausibly caused by a weaker formation rate of North Atlantic Deep Waters and an intensified ventilation of mode and intermediate waters in the Southern Hemisphere. Our estimates of the Cant accumulation differ from cumulative net air-sea flux estimates by several Pg C dec−1, suggesting a substantial and variable, but uncertain net loss of natural carbon from the ocean. Our findings indicate a considerable vulnerability of the ocean carbon sink to climate variability and change. Key Points: - The global ocean storage of anthropogenic carbon grew by 29 ± 3 and 27 ± 3 Pg C dec−1 from 1994 to 2004 and 2004 to 2014, respectively - The change in oceanic storage of anthropogenic carbon relative to the atmospheric CO2 growth decreased by 15 ± 11% from the first to the second decade - This reduction is attributed to a decrease of the ocean buffer capacity and changes in ocean circulation
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: text
    Format: text
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  • 2
    Publication Date: 2016-02-27
    Description: Coastal upwelling regimes are some of the most productive ecosystems in the ocean but are also among the most vulnerable to ocean acidification (OA) due to naturally high background concentrations of CO 2 . Yet our ability to predict how these ecosystems will respond to additional CO 2 resulting from anthropogenic emissions is poor. To help address this uncertainty, researchers perform manipulative experiments where biological responses are evaluated across different CO 2 partial pressure ( p CO 2 ) levels. In upwelling systems, however, contemporary carbonate chemistry variability remains only partly characterized and patterns of co-variation with other biologically important variables such as temperature and oxygen are just beginning to be explored in the context of OA experimental design. If co-variation among variables is prevalent, researchers risk performing OA experiments with control conditions that are not experienced by the focal species, potentially diminishing the ecological relevance of the experiment. Here, we synthesized a large carbonate chemistry dataset that consists of carbonate chemistry, temperature, and oxygen measurements from multiple moorings and ship-based sampling campaigns from the California Current Ecosystem (CCE), and includes fjord and tidal estuaries and open coastal waters. We evaluated patterns of p CO 2 variability and highlight important co-variation between p CO 2 , temperature, and oxygen. We subsequently compared environmental p CO 2 –temperature measurements with conditions maintained in OA experiments that used organisms from the CCE. By drawing such comparisons, researchers can gain insight into the ecological relevance of previously published OA experiments, but also identify species or life history stages that may already be influenced by contemporary carbonate chemistry conditions. We illustrate the implications co-variation among environmental variables can have for the interpretation of OA experimental results and suggest an approach for designing experiments with p CO 2 levels that better reflect OA hypotheses while simultaneously recognizing natural co-variation with other biologically relevant variables.
    Print ISSN: 1054-3139
    Electronic ISSN: 1095-9289
    Topics: Biology , Geosciences , Physics
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