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  • 1
    Publication Date: 2020-01-20
    Type: Dataset
    Format: text/tab-separated-values, 63 data points
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  • 2
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    PANGAEA
    In:  Supplement to: Doval, María Dolores; Alvarez-Salgado, Xose Anton; Castro, Carmen G; Pérez, Fiz F (2002): Dissolved organic carbon distributions in the Bransfield and Gerlache Straits, Antarctica. Deep Sea Research Part II: Topical Studies in Oceanography, 49(4-5), 663-674, https://doi.org/10.1016/S0967-0645(01)00117-5
    Publication Date: 2020-01-18
    Description: During FRUELA'95 cruise, seawater samples were collected at the Bransfield and Gerlache Straits for the analysis of dissolved organic carbon (DOC) profiles throughout the water column. An excess of DOC probably derived from phytogenic material was observed in the upper mixed layer (UML; average: +22±13 µmol C/l), compared to the constant concentration of refractory DOC below 400 m (44±4 µmol C/l). The average excess DOC concentration was higher than the particulate organic carbon concentration indicating the major contribution of DOC to carbon export in this area. However, large spatial variability of DOC in the upper mixed layer (52-102 µmol C/l) was observed: excess DOC contributed from 15% to 57% to the actual DOC concentration. Maximum average DOC concentrations in the UML were recorded in the Gerlache Strait (71 µmol C/l) and in the Gerlache-Bransfield confluence (80 µmol C/l), whereas minimum values were recorded in the Bransfield Strait (61 µmol C/l). Several shelf and slope stations showed a slight increase of DOC (5-10 µmol C/l) in the deep layer which might be related to organic matter release from the underlying sediments. Considering the net DOC release from phytoplankton, the low bacterial biomass and the reduced vertical DOC export, the DOC excess could build up in about 6 days for most of the sampling stations. The probable fate of the DOC excess is the eastwards horizontal transport by the Bransfield Current out of the study area.
    Type: Dataset
    Format: application/zip, 2 datasets
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  • 3
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    PANGAEA
    In:  Supplement to: Doval, María Dolores; Alvarez-Salgado, Xose Anton; Pérez, Fiz F (2001): Organic matter distributions in the Eastern North Atlantic-Azores Front region. Journal of Marine Systems, 30(1-2), 33-49, https://doi.org/10.1016/S0924-7963(01)00036-7
    Publication Date: 2020-01-18
    Description: Temperate, transitional and subtropical waters of the remote Azores Front region east of Azores (24-40°N, 22-32°W) were sampled during three cruises conducted under increasing stratification conditions (April 1999, May 1997 and August 1998). Despite the temporal increase of surface temperature (by 5 °C) and stratification (by 2.1 1/min**2), as well as the thermocline shoaling (by ~15 m), dissolved organic carbon (DOC) and nitrogen (DON) in the surface layer were not significantly different for the early spring, late spring and summer periods, with average concentrations of 69±2 µM-C and 5.2±0.4 µM-N, respectively. The surface excess of semi-labile DOC, compared with the baseline DOC concentration in the deep ocean (47±2 µM-C), represents 33% of the bulk DOC concentration and as much as 85% of the TOC (=POC+DOC) excess. When compared with the winter baseline (56±2 µM-C), the seasonal surface DOC excess is 20% of the bulk DOC concentration and 87% of the seasonal TOC excess. These results confirm the major role played by DOC in the carbon cycle of surface waters of the Azores Front region. The total amount of bioreactive DOC transported from the temperate to the subtropical North Atlantic by the Ekman flux between March and December represents only ~15% of the average annual primary production, and ~15% and ~30% of the measured sinking POC flux+vertical DOC eddy diffusion during early spring and summer, respectively. Vertical eddy diffusion is 35% and 2% of the spring and summer sinking POC flux, respectively. On the other hand, DOC only contributes 13% to the local oxidation of organic matter in subsurface waters (between the pycnocline and 500 m) of the study region.
    Type: Dataset
    Format: text/tab-separated-values, 864 data points
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  • 4
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    PANGAEA
    In:  Supplement to: Alvarez-Salgado, Xose Anton; Pérez, Fiz F; Ríos, Aida F; Doval, María Dolores (2001): Basin-scale changes of total organic carbon profiles in the eastern South Atlantic. Scientia Marina, 65(1), 1-10, https://doi.org/10.3989/scimar.2001.65n11
    Publication Date: 2020-01-18
    Description: Total organic carbon (TOC) samples were collected at 6 stations spaced ~800 km apart in the eastern South Atlantic, from the Equator to 45°S along 9°W. Analyses were performed by high temperature catalytic oxidation (HTCO) in the base laboratory. Despite the complex advection and mixing patterns of North Atlantic and Antarctic waters with extremely different degrees of ventilation, TOC levels below 500 m are quasi-constant at 55±3 µmol C/l, pointing to the refractory nature of deep-water TOC. On the other hand, a TOC excess from 25 to 38 g C/m**2 is observed in the upper 100 m of the permanently stratified nutrient-depleted Equatorial, Subequatorial and Subtropical upper ocean, where vertical turbulent diffusion is largely prevented. Conversely, TOC levels in the nutrient-rich upper layer of the Subantarctic Front only exceeds 9 g C/m**2 the deep-water baseline. As much as 70% of the TOC variability in the upper 500 m is due to simple mixing of reactive TOC formed in the surface layer and refractory TOC in deep ocean waters, with a minor contribution (13%) to oxygen consumption in the prominent subsurface AOU maximum at 200-400 m depth.
    Type: Dataset
    Format: text/tab-separated-values, 144 data points
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  • 5
    Publication Date: 2020-01-18
    Type: Dataset
    Format: text/tab-separated-values, 632 data points
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  • 6
  • 7
    Publication Date: 2018-10-29
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , NonPeerReviewed
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  • 8
    Publication Date: 2017-01-04
    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
    Type: Article
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  • 9
    Publication Date: 2017-01-04
    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
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 10
    Publication Date: 2018-03-29
    Description: © The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Earth System Science Data 7 (2015): 349–396, doi:10.5194/essd-7-349-2015.
    Description: Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates as well as consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover-change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models forced by observed climate, CO2, and land-cover change (some including nitrogen–carbon interactions). We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2005–2014), EFF was 9.0 ± 0.5 GtC yr−1, ELUC was 0.9 ± 0.5 GtC yr−1, GATM was 4.4 ± 0.1 GtC yr−1, SOCEAN was 2.6 ± 0.5 GtC yr−1, and SLAND was 3.0 ± 0.8 GtC yr−1. For the year 2014 alone, EFF grew to 9.8 ± 0.5 GtC yr−1, 0.6 % above 2013, continuing the growth trend in these emissions, albeit at a slower rate compared to the average growth of 2.2 % yr−1 that took place during 2005–2014. Also, for 2014, ELUC was 1.1 ± 0.5 GtC yr−1, GATM was 3.9 ± 0.2 GtC yr−1, SOCEAN was 2.9 ± 0.5 GtC yr−1, and SLAND was 4.1 ± 0.9 GtC yr−1. GATM was lower in 2014 compared to the past decade (2005–2014), reflecting a larger SLAND for that year. The global atmospheric CO2 concentration reached 397.15 ± 0.10 ppm averaged over 2014. For 2015, preliminary data indicate that the growth in EFF will be near or slightly below zero, with a projection of −0.6 [range of −1.6 to +0.5] %, based on national emissions projections for China and the USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the global economy for the rest of the world. From this projection of EFF and assumed constant ELUC for 2015, cumulative emissions of CO2 will reach about 555 ± 55 GtC (2035 ± 205 GtCO2) for 1870–2015, about 75 % from EFF and 25 % from ELUC. This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set (Le Quéré et al., 2015, 2014, 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_2015).
    Description: NERC provided funding to C. Le Quéré, R. Moriarty, and the GCP through their International Opportunities Fund specifically to support this publication (NE/103002X/1). G. P. Peters and R. M. Andrew were supported by the Norwegian Research Council (236296). J. G. Canadell was supported by the Australian Climate Change Science Programme. S. Sitch was supported by EU FP7 for funding through projects LUC4C (GA603542). R. J. Andres was supported by US Department of Energy, Office of Science, Biological and Environmental Research (BER) programmes under US Department of Energy contract DE-AC05- 00OR22725. T. A. Boden was supported by US Department of Energy, Office of Science, Biological and Environmental Research (BER) programmes under US Department of Energy contract DE-AC05-00OR22725. J. I. House was supported by the Leverhulme foundation and the EU FP7 through project LUC4C (GA603542). P. Friedlingstein was supported by the EU FP7 for funding through projects LUC4C (GA603542) and EMBRACE (GA282672). A. Arneth was supported by the EU FP7 for funding through LUC4C (603542), and the Helmholtz foundation and its ATMO programme. D. C. E. Bakker was supported by the EU FP7 for funding through project CARBOCHANGE (284879), the UK Ocean Acidification Research Programme (NE/H017046/1; funded by the Natural Environment Research Council, the Department for Energy and Climate Change and the Department for Environment, Food and Rural Affairs). L. Barbero was supported by NOAA’s Ocean Acidification Program and acknowledges support for this work from the National Aeronautics and Space Administration (NASA) ROSES Carbon Cycle Science under NASA grant 13-CARBON13_2-0080. P. Ciais acknowledges support from the European Research Council through Synergy grant ERC-2013-SyG-610028 “IMBALANCE-P”. M. Fader was supported by the EU FP7 for funding through project LUC4C (GA603542). J. Hauck was supported by the Helmholtz Postdoc Programme (Initiative and Networking Fund of the Helmholtz Association). R. A. Feely and A. J. Sutton were supported by the Climate Observation Division, Climate Program Office, NOAA, US Department of Commerce. A. K. Jain was supported by the US National Science Foundation (NSF AGS 12-43071) the US Department of Energy, Office of Science and BER programmes (DOE DE-SC0006706) and NASA LCLUC programme (NASA NNX14AD94G). E. Kato was supported by the ERTDF (S-10) from the Ministry of Environment, Japan. K. Klein Goldewijk was supported by the Dutch NWO VENI grant no. 863.14.022. S. K. Lauvset was supported by the project “Monitoring ocean acidification in Norwegian waters” from the Norwegian Ministry of Climate and Environment. V. Kitidis was supported by the EU FP7 for funding through project CARBOCHANGE (264879). C. Koven was supported by the Director, Office of Science, Office of Biological and Environmental Research of the US Department of Energy under contract no. DE-AC02-05CH11231 as part of their Regional and Global Climate Modeling Program. P. Landschützer was supported by GEOCarbon. I. T. van der Lann-Luijkx received financial support from OCW/NWO for ICOS-NL and computing time from NWO (SH-060-13). I. D. Lima was supported by the US National Science Foundation (NSF AGS-1048827). N. Metzl was supported by Institut National des Sciences de l’Univers (INSU) and Institut Paul Emile Victor (IPEV) for OISO cruises. D. R. Munro was supported by the US National Science Foundation (NSF PLR-1341647 and NSF AOAS-0944761). J. E. M. S. Nabel was supported by the German Research Foundation’s Emmy Noether Programme (PO1751/1-1) and acknowledges Julia Pongratz and Kim Naudts for their contributions. Y. Nojiri and S. Nakaoka were supported by the Global Environment Research Account for National Institutes (1432) by the Ministry of Environment of Japan. A. Olsen appreciates support from the Norwegian Research Council (SNACS, 229752). F. F. Pérez were supported by BOCATS (CTM2013-41048-P) project co-founded by the Spanish government and the Fondo Europeo de Desarrollo Regional (FEDER). B. Pfeil was supported through the European Union’s Horizon 2020 research and innovation programme AtlantOS under grant agreement no. 633211. D. Pierrot was supported by NOAA through the Climate Observation Division of the Climate Program Office. B. Poulter was supported by the EU FP7 for funding through GEOCarbon. G. Rehder was supported by BMBF (Bundesministerium für Bildung und Forschung) through project ICOS, grant no. 01LK1224D. U. Schuster was supported by NERC UKOARP (NE/H017046/1), NERC RAGANRoCC (NE/K002473/1), the European Space Agency (ESA) OceanFlux Evolution project, and EU FP7 CARBOCHANGE (264879). T. Steinhoff was supported by ICOS-D (BMBF FK 01LK1101C) and EU FP7 for funding through project CARBOCHANGE (264879). J. Schwinger was supported by the Research Council of Norway through project EVA (229771), and acknowledges the Norwegian Metacenter for Computational Science (NOTUR, project nn2980k), and the Norwegian Storage Infrastructure (NorStore, project ns2980k) for supercomputer time and storage resources. T. Takahashi was supported by grants from NOAA and the Comer Education and Science Foundation. B. Tilbrook was supported by the Australian Department of Environment and the Integrated Marine Observing System. B. D. Stocker was supported by the Swiss National Science Foundation and FP7 funding through project EMBRACE (282672). S. van Heuven was supported by the EU FP7 for funding through project CARBOCHANGE (264879). G. R. van der Werf was supported by the European Research Council (280061). A. Wiltshire was supported by the Joint UK DECC/Defra Met Office Hadley Centre Climate Programme (GA01101) and EU FP7 Funding through project LUC4C (603542). S. Zaehle was supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (QUINCY; grant agreement no. 647204). ISAM (PI: Atul K. Jain) simulations were carried out at the National Energy Research Scientific Computing Center (NERSC), which is supported by the US DOE under contract DE-AC02-05CH11231.
    Repository Name: Woods Hole Open Access Server
    Type: Article
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