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  • Inverse modeling  (2)
  • Modeling  (2)
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  • 1
    Publication Date: 2022-05-25
    Description: © The Author(s), 2014. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Geophysical Research Letters 41 (2014): 8438–8444, doi:10.1002/2014GL061574.
    Description: Along the continental margins, rivers and submarine groundwater supply nutrients, trace elements, and radionuclides to the coastal ocean, supporting coastal ecosystems and, increasingly, causing harmful algal blooms and eutrophication. While the global magnitude of gauged riverine water discharge is well known, the magnitude of submarine groundwater discharge (SGD) is poorly constrained. Using an inverse model combined with a global compilation of 228Ra observations, we show that the SGD integrated over the Atlantic and Indo-Pacific Oceans between 60°S and 70°N is (12 ± 3) × 1013 m3 yr−1, which is 3 to 4 times greater than the freshwater fluxes into the oceans by rivers. Unlike the rivers, where more than half of the total flux is discharged into the Atlantic, about 70% of SGD flows into the Indo-Pacific Oceans. We suggest that SGD is the dominant pathway for dissolved terrestrial materials to the global ocean, and this necessitates revisions for the budgets of chemical elements including carbon.
    Description: This work was supported by the Ministry of Oceans and Fisheries, Korea, through the Korea Institute of Marine Science and Technology (KIMST) (20120176) and National Research Foundation (NRF) of Korea (2013R1A2A1A05004343 and 2013R1A1A1058203). Charette and Moore's contributions were supported by the US National Science Foundation through the GEOTRACES project.
    Keywords: Submarine groundwater discharge ; Radium ; Inverse modeling ; Land-ocean interaction ; Brackish groundwater ; Coastal flux
    Repository Name: Woods Hole Open Access Server
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  • 2
    Publication Date: 2022-05-26
    Description: Author Posting. © American Geophysical Union, 2009. 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 114 (2009): C12099, doi:10.1029/2009JC005835.
    Keywords: Modeling ; Climate ; Carbon
    Repository Name: Woods Hole Open Access Server
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  • 3
    Publication Date: 2022-05-26
    Description: Author Posting. © American Geophysical Union, 2009. 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 114 (2009): C09013, doi:10.1029/2008JC005183.
    Description: Here we use observations and ocean models to identify mechanisms driving large seasonal to interannual variations in dissolved inorganic carbon (DIC) and dissolved oxygen (O2) in the upper ocean. We begin with observations linking variations in upper ocean DIC and O2 inventories with changes in the physical state of the ocean. Models are subsequently used to address the extent to which the relationships derived from short-timescale (6 months to 2 years) repeat measurements are representative of variations over larger spatial and temporal scales. The main new result is that convergence and divergence (column stretching) attributed to baroclinic Rossby waves can make a first-order contribution to DIC and O2 variability in the upper ocean. This results in a close correspondence between natural variations in DIC and O2 column inventory variations and sea surface height (SSH) variations over much of the ocean. Oceanic Rossby wave activity is an intrinsic part of the natural variability in the climate system and is elevated even in the absence of significant interannual variability in climate mode indices. The close correspondence between SSH and both DIC and O2 column inventories for many regions suggests that SSH changes (inferred from satellite altimetry) may prove useful in reducing uncertainty in separating natural and anthropogenic DIC signals (using measurements from Climate Variability and Predictability's CO2/Repeat Hydrography program).
    Description: This report was prepared by K.B.R. under awards NA17RJ2612 and NA08OAR4320752, which includes support through the NOAA Office of Climate Observations (OCO). The statements, findings, conclusions, and recommendations are those of the authors and do not necessarily reflect the views of the National Oceanic and Atmospheric Administration or the U.S. Department of Commerce. Support for K.B.R. was also provided by the Carbon Mitigation Initiative (CMI) through the support of BP, Amaco, and Ford. R.M.K. was supported by NOAA grants NA17RJ2612, NA08OAR4320752, and NA08OAR4310820. F.F.P. was supported by the European Union FP6 CARBOOCEAN Integrated project (contract 51176), the French OVIDE project, and the Spanish Salvador de Madariaga program (PR2006– 0523). This work was also supported by the European NOCES project (EVK2-CT201-00134). Y.Y. and A.I. are partly supported by CREST, JST of Japan. The long-term OISO observational program in the South Indian Ocean is supported by the following three French institutes: INSU (Institut National des Sciences de l’Univers), IPSL (Institute Pierre-Simon Laplace), and IPEV (Institut Paul-Emile Victor).
    Keywords: Modeling ; Climate ; Carbon
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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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