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  • Carbon cycle  (2)
  • Convection  (1)
  • Ocean circulation
  • American Geophysical Union  (4)
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  • American Geophysical Union  (4)
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  • 1
    Publication Date: 2022-05-25
    Description: Author Posting. © American Geophysical Union, 2007. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Global Biogeochemical Cycles 21 (2007): GB3007, doi:10.1029/2006GB002857.
    Description: Results are presented of export production, dissolved organic matter (DOM) and dissolved oxygen simulated by 12 global ocean models participating in the second phase of the Ocean Carbon-cycle Model Intercomparison Project. A common, simple biogeochemical model is utilized in different coarse-resolution ocean circulation models. The model mean (±1σ) downward flux of organic matter across 75 m depth is 17 ± 6 Pg C yr−1. Model means of globally averaged particle export, the fraction of total export in dissolved form, surface semilabile dissolved organic carbon (DOC), and seasonal net outgassing (SNO) of oxygen are in good agreement with observation-based estimates, but particle export and surface DOC are too high in the tropics. There is a high sensitivity of the results to circulation, as evidenced by (1) the correlation of surface DOC and export with circulation metrics, including chlorofluorocarbon inventory and deep-ocean radiocarbon, (2) very large intermodel differences in Southern Ocean export, and (3) greater export production, fraction of export as DOM, and SNO in models with explicit mixed layer physics. However, deep-ocean oxygen, which varies widely among the models, is poorly correlated with other model indices. Cross-model means of several biogeochemical metrics show better agreement with observation-based estimates when restricted to those models that best simulate deep-ocean radiocarbon. Overall, the results emphasize the importance of physical processes in marine biogeochemical modeling and suggest that the development of circulation models can be accelerated by evaluating them with marine biogeochemical metrics.
    Description: R. G. N. and J. L. S. acknowledge the support of NASA grants NAG5-6451 and NAG5-6591, respectively, as part of the JGOFS Synthesis and Modeling Program. G. K. P. and F. J. acknowledge support by the Swiss National Science Foundation. European contributions were supported by the EU GOSAC Project (ENV4-CT97- 0495).
    Keywords: Export production ; Numerical modeling ; Ocean circulation
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 2
    Publication Date: 2022-10-21
    Description: © The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Haumann, F. A., Moorman, R., Riser, S. C., Smedsrud, L. H., Maksym, T., Wong, A. P. S., Wilson, E. A., Drucker, R., Talley, L. D., Johnson, K. S., Key, R. M., & Sarmiento, J. L. Supercooled Southern Ocean waters. Geophysical Research Letters, 47(20), (2020): e2020GL090242, doi:10.1029/2020GL090242.
    Description: In cold polar waters, temperatures sometimes drop below the freezing point, a process referred to as supercooling. However, observational challenges in polar regions limit our understanding of the spatial and temporal extent of this phenomenon. We here provide observational evidence that supercooled waters are much more widespread in the seasonally ice‐covered Southern Ocean than previously reported. In 5.8% of all analyzed hydrographic profiles south of 55°S, we find temperatures below the surface freezing point (“potential” supercooling), and half of these have temperatures below the local freezing point (“in situ” supercooling). Their occurrence doubles when neglecting measurement uncertainties. We attribute deep coastal‐ocean supercooling to melting of Antarctic ice shelves and surface‐induced supercooling in the seasonal sea‐ice region to wintertime sea‐ice formation. The latter supercooling type can extend down to the permanent pycnocline due to convective sinking plumes—an important mechanism for vertical tracer transport and water‐mass structure in the polar ocean.
    Description: F. A. H. was supported by the Swiss National Science Foundation (SNSF; Schweizerischer Nationalfonds zur Förderung der wissenschaftlichen Forschung) grant numbers P2EZP2_175162 and P400P2_186681. This work was supported by the National Science Foundation (NSF) Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) Project under the NSF Award PLR‐1425989. R. M. would like to thank the National Oceanic and Atmospheric Administration (NOAA) GFDL for mentorship and computational support. S. R. was also supported by the U.S. Argo grant and NOAA grant NA15OAR4320063 to the University of Washington. L. H. S. thanks the Fulbright Foundation for the U.S.‐Norway Arctic Chair grant. We are deeply thankful to the large number of scientists, technicians, and funding agencies contributing to these databases, being responsible for the collection and quality control of the high‐quality data that form the basis of this work. We thank Josh Plant for his initial notification on very low temperatures observed in some of the float profiles. We would also like to thank the students, teachers, and schools who are participating in the SOCCOM Adopt‐a‐Float program. Four of the floats used in this study were adopted and have a clear signal of supercooling. These participants are listed in Table S1.
    Keywords: Southern Ocean ; Supercooling ; Sea ice ; Ice shelf ; Observations ; Convection
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  • 3
    Publication Date: 2022-05-26
    Description: Author Posting. © American Geophysical Union, 2008. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 113 (2008): C07032, doi:10.1029/2007JC004598.
    Description: This paper examines the sensitivity of atmospheric pCO2 to changes in ocean biology that result in drawdown of nutrients at the ocean surface. We show that the global inventory of preformed nutrients is the key determinant of atmospheric pCO2 and the oceanic carbon storage due to the soft-tissue pump (OCS soft ). We develop a new theory showing that under conditions of perfect equilibrium between atmosphere and ocean, atmospheric pCO2 can be written as a sum of exponential functions of OCS soft . The theory also demonstrates how the sensitivity of atmospheric pCO2 to changes in the soft-tissue pump depends on the preformed nutrient inventory and on surface buffer chemistry. We validate our theory against simulations of nutrient depletion in a suite of realistic general circulation models (GCMs). The decrease in atmospheric pCO2 following surface nutrient depletion depends on the oceanic circulation in the models. Increasing deep ocean ventilation by increasing vertical mixing or Southern Ocean winds increases the atmospheric pCO2 sensitivity to surface nutrient forcing. Conversely, stratifying the Southern Ocean decreases the atmospheric CO2 sensitivity to surface nutrient depletion. Surface CO2 disequilibrium due to the slow gas exchange with the atmosphere acts to make atmospheric pCO2 more sensitive to nutrient depletion in high-ventilation models and less sensitive to nutrient depletion in low-ventilation models. Our findings have potentially important implications for both past and future climates.
    Description: While at MIT, I.M. was supported by the NOAA Postdoctoral Program in Climate and Global Change, administered by the University Corporation for Atmospheric Research.
    Keywords: Carbon cycle ; Preformed nutrient ; Nutrient depletion
    Repository Name: Woods Hole Open Access Server
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  • 4
    Publication Date: 2022-05-26
    Description: Author Posting. © American Geophysical Union, 2006. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Global Biogeochemical Cycles 20 (2006): GB2002, doi:10.1029/2005GB002530.
    Description: Regional air-sea fluxes of anthropogenic CO2 are estimated using a Green's function inversion method that combines data-based estimates of anthropogenic CO2 in the ocean with information about ocean transport and mixing from a suite of Ocean General Circulation Models (OGCMs). In order to quantify the uncertainty associated with the estimated fluxes owing to modeled transport and errors in the data, we employ 10 OGCMs and three scenarios representing biases in the data-based anthropogenic CO2 estimates. On the basis of the prescribed anthropogenic CO2 storage, we find a global uptake of 2.2 ± 0.25 Pg C yr−1, scaled to 1995. This error estimate represents the standard deviation of the models weighted by a CFC-based model skill score, which reduces the error range and emphasizes those models that have been shown to reproduce observed tracer concentrations most accurately. The greatest anthropogenic CO2 uptake occurs in the Southern Ocean and in the tropics. The flux estimates imply vigorous northward transport in the Southern Hemisphere, northward cross-equatorial transport, and equatorward transport at high northern latitudes. Compared with forward simulations, we find substantially more uptake in the Southern Ocean, less uptake in the Pacific Ocean, and less global uptake. The large-scale spatial pattern of the estimated flux is generally insensitive to possible biases in the data and the models employed. However, the global uptake scales approximately linearly with changes in the global anthropogenic CO2 inventory. Considerable uncertainties remain in some regions, particularly the Southern Ocean.
    Description: This research was financially supported by the National Aeronautics and Space Administration under grant NAG5- 12528. N. G. also acknowledges support by the National Science Foundation (OCE-0137274). Climate and Environmental Physics, Bern acknowledges support by the European Union through the Integrated Project CarboOcean and the Swiss National Science Foundation.
    Keywords: Anthropogenic CO2 ; Carbon cycle ; Inverse modeling
    Repository Name: Woods Hole Open Access Server
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