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  • AGU (American Geophysical Union)  (2)
  • 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
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  • 2
    Publication Date: 2024-02-07
    Description: Accurately predicting future ocean acidification (OA) conditions is crucial for advancing OA research at regional and global scales, and guiding society's mitigation and adaptation efforts. This study presents a new model-data fusion product covering 10 global surface OA indicators based on 14 Earth System Models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6), along with three recent observational ocean carbon data products. The indicators include fugacity of carbon dioxide, pH on total scale, total hydrogen ion content, free hydrogen ion content, carbonate ion content, aragonite saturation state, calcite saturation state, Revelle Factor, total dissolved inorganic carbon content, and total alkalinity content. The evolution of these OA indicators is presented on a global surface ocean 1° × 1° grid as decadal averages every 10 years from preindustrial conditions (1750), through historical conditions (1850–2010), and to five future Shared Socioeconomic Pathways (2020–2100): SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. These OA trajectories represent an improvement over previous OA data products with respect to data quantity, spatial and temporal coverage, diversity of the underlying data and model simulations, and the provided SSPs. The generated data product offers a state-of-the-art research and management tool for the 21st century under the combined stressors of global climate change and ocean acidification. The gridded data product is available in NetCDF at the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Information: https://www.ncei.noaa.gov/data/oceans/ncei/ocads/metadata/0259391.html, and global maps of these indicators are available in jpeg at: https://www.ncei.noaa.gov/access/ocean-carbon-acidification-data-system/synthesis/surface-oa-indicators.html. Key Points: - This study presents the evolution of 10 ocean acidification (OA) indicators in the global surface ocean from 1750 to 2100 - By leveraging 14 Earth System Models (ESMs) and the latest observational data, it represents a significant advancement in OA projections - This inter-model comparison effort showcases the overall agreements among different ESMs in projecting surface ocean carbon variables
    Type: Article , PeerReviewed
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