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Processes Driving Global Interior Ocean pH Distribution ArchiMer
Lauvset, S. K.; Carter, B. R.; Perez, Ff; Jiang, L-q; Feely, R. A.; Velo, A.; Olsen, A..
Ocean acidification evolves on the background of a natural ocean pH gradient that is the result of the interplay between ocean mixing, biological production and remineralization, calcium carbonate cycling, and temperature and pressure changes across the water column. While previous studies have analyzed these processes and their impacts on ocean carbonate chemistry, none have attempted to quantify their impacts on interior ocean pH globally. Here we evaluate how anthropogenic changes and natural processes collectively act on ocean pH, and how these processes set the vulnerability of regions to future changes in ocean acidification. We use the mapped data product from the Global Ocean Data Analysis Project version 2, a novel method to estimate preformed...
Tipo: Text Palavras-chave: PH; Remineralization; CaCO3; Anthropogenic; Global ocean.
Ano: 2020 URL: https://archimer.ifremer.fr/doc/00676/78793/81066.pdf
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State of the Climate in 2018 ArchiMer
Arndt, D. S.; Blunden, J.; Dunn, R. J. H.; Stanitski, D. M.; Gobron, N.; Willett, K. M.; Sanchez-lugo, A.; Berrisford, P.; Morice, C.; Nicolas, Jp; Carrea, L.; Woolway, R. I.; Merchant, C. J.; Dokulil, M. T.; De Eyto, E.; Degasperi, C. L.; Korhonen, J.; Marszelewski, W.; May, L.; Paterson, A. M.; Rusak, J. A.; Schladow, S. G.; Schmid, M.; Verburg, P.; Watanabe, S.; Weyhenmeyer, G. A.; King, A. D.; Donat, M. G.; Christy, J. R.; Po-chedley, S.; Mears, C. R.; Haimberger, L.; Covey, C.; Randel, W.; Noetzli, J.; Biskaborn, B. K.; Christiansen, H. H.; Isaksen, K.; Schoeneich, P.; Smith, S.; Vieira, G.; Zhao, L.; Streletskiy, D. A.; Robinson, D. A.; Pelto, M.; Berry, D. I.; Bosilovich, M. G.; Simmons, A. J.; Mears, C.; Ho, S. P.; Bock, O.; Zhou, X.; Nicolas, J; Vose, R. S.; Adler, R.; Gu, G.; Becker, A.; Yin, X; Tye, M. R.; Blenkinsop, S.; Bosilovich, M. G.; Durre, I.; Ziese, M.; Collow, A. B. Marquardt; Rustemeier, E.; Foster, M. J.; Di Girolamo, L.; Frey, R. A.; Heidinger, A. K.; Sun-mack, S.; Phillips, C.; Menzel, W. P.; Stengel, M.; Zhao, G.; Kim, H.; Rodell, M.; Li, B.; Famiglietti, J. S.; Scanlon, T.; Van Der Schalie, R.; Preimesberger, W.; Reimer, C.; Hahn, S.; Gruber, A.; Kidd, R.; De Jeu, R. A. M.; Dorigo, W. A.; Barichivich, J.; Osborn, T. J.; Harris, I.; Van Der Schrier, G.; Jones, P. D.; Miralles, D. G.; Martens, B.; Beck, H. E.; Dolman, A. J.; Jimenez, C.; Mccabe, M. F.; Wood, E. F.; Allan, R.; Azorin-molina, C.; Mears, C. A.; Mcvicar, T. R.; Mayer, M.; Schenzinger, V.; Hersbach, H.; Stackhouse, P. W., Jr.; Wong, T.; Kratz, D. P.; Sawaengphokhai, P.; Wilber, A. C.; Gupta, S. K.; Loeb, N. G.; Dlugokencky, E. J.; Hall, B. D.; Montzka, S. A.; Dutton, G.; Muhle, J.; Elkins, J. W.; Miller, Br; Remy, S.; Bellouin, N.; Kipling, Z.; Ades, M.; Benedetti, A.; Boucher, O.; Weber, M.; Steinbrecht, W.; Arosio, C.; Van Der A, R.; Frith, S. M.; Anderson, J.; Coldewey-egbers, M.; Davis, S.; Degenstein, D.; Fioletov, V. E.; Froidevaux, L.; Hubert, D.; Long, C. S.; Loyola, D.; Rozanov, A.; Roth, C.; Sofieva, V.; Tourpali, K.; Wang, R.; Wild, J. D.; Davis, S. M.; Rosenlof, K. H.; Hurst, D. F.; Selkirk, H. B.; Vomel, H.; Ziemke, J. R.; Cooper, O. R.; Flemming, J.; Inness, A.; Pinty, B.; Kaiser, J. W.; Van Der Werf, G. R.; Hemming, D. L.; Garforth, J.; Park, T.; Richardson, A. D.; Rutishauser, T.; Sparks, T. H.; Thackeray, S. J.; Myneni, R.; Lumpkin, R.; Huang, B.; Kennedy, J.; Xue, Y.; Zhang, H. -m.; Hu, C.; Wang, M.; Johnson, G. C.; Lyman, J. M.; Boyer, T.; Cheng, L.; Domingues, C. M.; Gilson, J.; Ishii, M.; Killick, R. E.; Monselesan, D.; Purkey, S. G.; Wijffels, S. E.; Locarnini, R.; Yu, L.; Jin, X.; Stackhouse, P. W.; Kato, S.; Weller, R. A.; Thompson, P. R.; Widlansky, M. J.; Leuliette, E.; Sweet, W.; Chambers, D. P.; Hamlington, B. D.; Jevrejeva, S.; Marra, J. J.; Merrifield, M. A.; Mitchum, G. T.; Nerem, R. S.; Kelble, C.; Karnauskas, M.; Hubbard, K.; Goni, G.; Streeter, C.; Lumpkin, R.; Dohan, K.; Franz, B. A.; Cetinic, I.; Karakoylu, E. M.; Siegel, D. A.; Westberry, T. K.; Feely, R. A.; Wanninkhof, R.; Carter, B. R.; Landschutzer, P.; Sutton, A. J.; Cosca, C.; Trinanes, J. A.; Baxter, S.; Schreck, C.; Bell, G. D.; Mullan, A. B.; Pezza, A. B.; Coelho, C. A. S.; Wang, B.; He, Q.; Diamond, H. J.; Schreck, C. J.; Bell, G. D.; Blake, E. S.; Landsea, C. W.; Wang, H.; Goldenberg, S. B.; Pasch, R. J.; Klotzbach, P. J.; Kruk, M. C.; Schreck, C. J.; Camargo, S. J.; Trewin, B. C.; Pearce, P. R.; Lorrey, A. M.; Domingues, R.; Goni, G. J.; Knaff, J. A.; Lin, I. -i.; Bringas, F.; Richter-menge, J.; Osborne, E.; Druckenmiller, M.; Jeffries, M. O.; Overland, J. E.; Hanna, E.; Hanssen-bauer, I.; Kim, S. -j.; Walsh, J. E.; Wang, M.; Bhatt, U. S.; Timmermans, M. -l.; Ladd, C.; Perovich, D.; Meier, W.; Tschudi, M.; Farrell, S.; Hendricks, S.; Gerland, S.; Haas, C.; Krumpen, T.; Polashenski, C.; Ricker, R; Webster, M.; Stabeno, P. J.; Tedesco, M.; Box, J. E.; Cappelen, J.; Fausto, R. S.; Fettweis, X.; Andersen, J. K.; Mote, T.; Smeets, C. J. P. P.; Van As, D.; Van De Wal, R. S. W.; Romanovsky, V. E.; Smith, S. L.; Isaksen, K.; Shiklomanov, N. I.; Streletskiy, D. A.; Kholodov, A. L.; Christiansen, H. H.; Drozdov, D. S.; Malkova, G. V.; Marchenko, S. S.; Jella, K. B.; Mudryk, L.; Brown, R.; Derksen, C.; Luojus, K.; Decharme, B.; Holmes, R. M.; Shiklomanov, A. I.; Suslova, A.; Tretiakov, M.; Mcclelland, J. W.; Spencer, R. G. M.; Tank, S. E.; Epstein, H.; Bhatt, U.; Raynolds, M.; Walker, D.; Forbes, B.; Phoenix, G.; Bjerke, J.; Tommervik, H.; Karlsen, S. -r.; Myneni, R.; Park, T.; Goetz, S.; Jia, G.; Bernhard, G. H.; Fioletov, V. E.; Grooss, J. -u.; Ialongo, I.; Johnsen, B.; Lakkala, K.; Manney, G. L.; Mueller, R.; Scambos, T.; Stammerjohn, S.; Clem, K. R.; Barreira, S.; Fogt, R. L.; Colwell, S.; Keller, L. M.; Lazzara, M. A.; Reid, P.; Massom, R. A.; Lieser, J. L.; Meijers, A.; Sallee, J. -b.; Grey, A.; Johnson, K.; Arrigo, K.; Swart, S.; King, B.; Meredith, M.; Mazloff, M.; Scardilli, A.; Claus, F.; Shuman, C. A.; Kramarova, N.; Newman, P. A.; Nash, E. R.; Strahan, S. E.; Long, C. S.; Johnson, B.; Pitts, M.; Santee, M. L.; Petropavlovskikh, I.; Braathen, G. O.; Coy, L.; De Laat, J.; Bissolli, P.; Ganter, C.; Li, T.; Mekonnen, A.; Sanchez-lugo, A.; Gleason, K.; Smith, A.; Fenimore, C.; Heim, R. R., Jr.; Nauslar, N. J.; Brown, T. J.; Mcevoy, D. J.; Lareau, N. P.; Amador, J. A.; Hidalgo, H. G.; Alfaro, E. J.; Calderon, B.; Mora, N.; Stephenson, T. S.; Taylor, M. A.; Trotman, A. R.; Van Meerbeeck, C. J.; Campbell, J. D.; Brown, A.; Spence, J.; Martinez, R.; Diaz, E.; Marin, D.; Hernandez, R.; Caceres, L.; Zambrano, E.; Nieto, J.; Marengo, J. A.; Espinoza, J. C.; Alves, L. M.; Ronchail, J.; Lavado-casimiro, J. W.; Ramos, I.; Davila, C.; Ramos, A. M.; Diniz, F. A.; Aliaga-nestares, V.; Castro, A. Y.; Stella, J. L.; Aldeco, L. S.; Diaz, D. A. Campos; Misevicius, N.; Mekonnen, A.; Kabidi, K.; Sayouri, A.; Elkharrim, M.; Mostafa, A. E.; Hagos, S.; Feng, Z.; Ijampy, J. A.; Sima, F.; Francis, S. D.; Tsidu, G. Mengistu; Kruger, A. C.; Mcbride, C.; Jumaux, G.; Dhurmea, K. R.; Belmont, M.; Rakotoarimalala, C. L.; Labbe, L.; Rosner, B.; Benedict, I.; Van Heerwaarden, C.; Weerts, A.; Hazeleger, W.; Bissolli, P.; Trachte, K.; Zhu, Z.; Zhang, P.; Lee, T. C.; Ripaldi, A.; Mochizuki, Y.; Lim, J. -y; Oyunjargal, L.; Timbal, B.; Srivastava, A. K.; Revadekar, J. V.; Rajeevan, M.; Shimpo, A.; Khoshkam, M.; Kazemi, A. Fazl; Zeyaeyan, S.; Ganter, C.; Lander, M. A.; Mcgree, S.; Tobin, S.; Bettio, L..
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Ano: 2019 URL: https://archimer.ifremer.fr/doc/00677/78862/81179.pdf
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Locally interpolated alkalinity regression for global alkalinity estimation ArchiMer
Carter, B. R.; Williams, N. L.; Gray, A. R.; Feely, R. A..
We introduce methods and software for estimating total seawater alkalinity from salinity and any combination of up to four other parameters (potential temperature, apparent oxygen utilization, total dissolved nitrate, and total silicate). The methods return estimates anywhere in the global ocean with comparable accuracy to other published alkalinity estimation techniques. The software interpolates between a predetermined grid of coefficients for linear regressions onto arbitrary latitude, longitude, and depth coordinates, and thereby avoids the estimate discontinuities many similar methods return when transitioning from one regression constant set to another. The software can also return uncertainty estimates scaled by user-provided input parameter...
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Ano: 2016 URL: https://archimer.ifremer.fr/doc/00383/49420/49853.pdf
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A uniform, quality controlled Surface Ocean CO2 Atlas (SOCAT) ArchiMer
Pfeil, B.; Olsen, A.; Bakker, D. C. E.; Hankin, S.; Koyuk, H.; Kozyr, A.; Malczyk, J.; Manke, A.; Metzl, N.; Sabine, C. L.; Akl, J.; Alin, S. R.; Bates, N.; Bellerby, R. G. J.; Borges, A.; Boutin, J.; Brown, P. J.; Cai, W. -j.; Chavez, F. P.; Chen, A.; Cosca, C.; Fassbender, A. J.; Feely, R. A.; Gonzalez-davila, M.; Goyet, C.; Hales, B.; Hardman-mountford, N.; Heinze, C.; Hood, M.; Hoppema, M.; Hunt, C. W.; Hydes, D.; Ishii, M.; Johannessen, T.; Jones, S. D.; Key, R. M.; Koertzinger, A.; Landschuetzer, P.; Lauvset, S. K.; Lefevre, N.; Lenton, A.; Lourantou, A.; Merlivat, L.; Midorikawa, T.; Mintrop, L.; Miyazaki, C.; Murata, A.; Nakadate, A.; Nakano, Y.; Nakaoka, S.; Nojiri, Y.; Omar, A. M.; Padin, X. A.; Park, G. -h.; Paterson, K.; Perez, Fiz F; Pierrot, D.; Poisson, A.; Rios, A. F.; Santana-casiano, J. M.; Salisbury, J.; Sarma, V. V. S. S.; Schlitzer, R.; Schneider, B.; Schuster, U.; Sieger, R.; Skjelvan, I.; Steinhoff, T.; Suzuki, T.; Takahashi, T.; Tedesco, K.; Telszewski, M.; Thomas, H.; Tilbrook, B.; Tjiputra, J.; Vandemark, D.; Veness, T.; Wanninkhof, R.; Watson, A. J.; Weiss, R.; Wong, C. S.; Yoshikawa-inoue, H..
A well-documented, publicly available, global data set of surface ocean carbon dioxide (CO2) parameters has been called for by international groups for nearly two decades. The Surface Ocean CO2 Atlas (SOCAT) project was initiated by the international marine carbon science community in 2007 with the aim of providing a comprehensive, publicly available, regularly updated, global data set of marine surface CO2, which had been subject to quality control (QC). Many additional CO2 data, not yet made public via the Carbon Dioxide Information Analysis Center (CDIAC), were retrieved from data originators, public websites and other data centres. All data were put in a uniform format following a strict protocol. Quality control was carried out according to clearly...
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Ano: 2013 URL: https://archimer.ifremer.fr/doc/00383/49450/49923.pdf
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An update to the Surface Ocean CO2 Atlas (SOCAT version 2) ArchiMer
Bakker, D. C. E.; Pfeil, B.; Smith, K.; Hankin, S.; Olsen, A.; Alin, S. R.; Cosca, C.; Harasawa, S.; Kozyr, A.; Nojiri, Y.; O'Brien, K. M.; Schuster, U.; Telszewski, M.; Tilbrook, B.; Wada, C.; Akl, J.; Barbero, L.; Bates, N. R.; Boutin, J.; Bozec, Y.; Cai, W. -j.; Castle, R. D.; Chavez, F. P.; Chen, L.; Chierici, M.; Currie, K.; De Baar, H. J. W.; Evans, W.; Feely, R. A.; Fransson, A.; Gao, Z.; Hales, B.; Hardman-mountford, N. J.; Hoppema, M.; Huang, W. -j.; Hunt, C. W.; Huss, B.; Ichikawa, T.; Johannessen, T.; Jones, E. M.; Jones, S. D.; Jutterstrom, S.; Kitidis, V.; Koertzinger, A.; Landschuetzer, P.; Lauvset, S. K.; Lefevre, N.; Manke, A. B.; Mathis, J. T.; Merlivat, L.; Metzl, N.; Murata, A.; Newberger, T.; Omar, A. M.; Ono, T.; Park, G. -h.; Paterson, K.; Pierrot, D.; Rios, A. F.; Sabine, C. L.; Saito, S.; Salisbury, J.; Sarma, V. V. S. S.; Schlitzer, R.; Sieger, R.; Skjelvan, I.; Steinhoff, T.; Sullivan, K. F.; Sun, H.; Sutton, A. J.; Suzuki, T.; Sweeney, C.; Takahashi, T.; Tjiputra, J.; Tsurushima, N.; Van Heuven, S. M. A. C.; Vandemark, D.; Vlahos, P.; Wallace, D. W. R.; Wanninkhof, R.; Watson, A. J..
The Surface Ocean CO2 Atlas (SOCAT), an activity of the international marine carbon research community, provides access to synthesis and gridded fCO(2) (fugacity of carbon dioxide) products for the surface oceans. Version 2 of SOCAT is an update of the previous release (version 1) with more data (increased from 6.3 million to 10.1 million surface water fCO(2) values) and extended data coverage (from 1968-2007 to 1968-2011). The quality control criteria, while identical in both versions, have been applied more strictly in version 2 than in version 1. The SOCAT website (http://www.socat.info/) has links to quality control comments, metadata, individual data set files, and synthesis and gridded data products. Interactive online tools allow visitors to explore...
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Ano: 2014 URL: https://archimer.ifremer.fr/doc/00291/40260/39418.pdf
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Surface Ocean CO2 Atlas (SOCAT) Gridded Data Products ArchiMer
Sabine, C. L.; Hankin, S.; Koyuk, H.; Bakker, D. C. E.; Pfeil, B.; Olsen, A.; Metzl, N.; Kozyr, A.; Fassbender, A.; Manke, A.; Malczyk, J.; Akl, J.; Alin, S. R.; Bellerby, R. G. J.; Borges, A.; Boutin, J.; Brown, P. J.; Cai, W. -j.; Chavez, F. P.; Chen, A.; Cosca, C.; Feely, R. A.; Gonzalez-davila, M.; Goyet, C.; Hardman-mountford, N.; Heinze, C.; Hoppema, M.; Hunt, C. W.; Hydes, D.; Ishii, M.; Johannessen, T.; Key, R. M.; Koertzinger, A.; Landschuetzer, P.; Lauvset, S. K.; Lefevre, N.; Lenton, A.; Lourantou, A.; Merlivat, L.; Midorikawa, T.; Mintrop, L.; Miyazaki, C.; Murata, A.; Nakadate, A.; Nakano, Y.; Nakaoka, S.; Nojiri, Y.; Omar, A. M.; Padin, X. A.; Park, G. -h.; Paterson, K.; Perez, F.f.; Pierrot, D.; Poisson, A.; Rios, A. F.; Salisbury, J.; Santana-casiano, J. M.; Sarma, V. V. S. S.; Schlitzer, R.; Schneider, B.; Schuster, U.; Sieger, R.; Skjelvan, I.; Steinhoff, T.; Suzuki, T.; Takahashi, T.; Tedesco, K.; Telszewski, M.; Thomas, H.; Tilbrook, B.; Vandemark, D.; Veness, T.; Watson, A. J.; Weiss, R.; Wong, C. S.; Yoshikawa-inoue, H..
A well documented, publicly available, global data set for surface ocean carbon dioxide (CO2) parameters has been called for by international groups for nearly two decades. The Surface Ocean CO2 Atlas (SOCAT) project was initiated by the international marine carbon science community in 2007 with the aim of providing a comprehensive, publicly available, regularly updated, global data set of marine surface CO2, which had been subject to quality control (QC). SOCAT version 1.5 was made public in September 2011 and holds 6.3 million quality controlled surface CO2 data from the global oceans and coastal seas, spanning four decades (1968–2007). The SOCAT gridded data is the second data product to come from the SOCAT project. Recognizing that some groups may have...
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Ano: 2013 URL: https://archimer.ifremer.fr/doc/00141/25178/23284.pdf
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Updated methods for global locally interpolated estimation of alkalinity, pH, and nitrate ArchiMer
Carter, B. R.; Feely, R. A.; Williams, N. L.; Dickson, A. G.; Fong, M. B.; Takeshita, Y..
We have taken advantage of the release of version 2 of the Global Data Analysis Project data product (Olsen et al. ) to refine the locally interpolated alkalinity regression (LIAR) code for global estimation of total titration alkalinity of seawater (A(T)), and to extend the method to also produce estimates of nitrate (N) and in situ pH (total scale). The updated MATLAB software and methods are distributed as Supporting Information for this article and referred to as LIAR version 2 (LIARv2), locally interpolated nitrate regression (LINR), and locally interpolated pH regression (LIPHR). Collectively they are referred to as locally interpolated regressions (LIRs). Relative to LIARv1, LIARv2 has an 18% lower average A(T) estimate root mean squared error...
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Ano: 2018 URL: https://archimer.ifremer.fr/doc/00662/77386/79020.pdf
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Calculating surface ocean pCO 2 from biogeochemical Argo floats equipped with pH: An uncertainty analysis ArchiMer
Williams, N. L.; Juranek, L. W.; Feely, R. A.; Johnson, K. S.; Sarmiento, J. L.; Talley, L. D.; Dickson, A. G.; Gray, A. R.; Wanninkhof, R.; Russell, J. L.; Riser, S. C.; Takeshita, Y..
More than 74 biogeochemical profiling floats that measure water column pH, oxygen, nitrate, fluorescence, and backscattering at 10 day intervals have been deployed throughout the Southern Ocean. Calculating the surface ocean partial pressure of carbon dioxide (pCO2sw) from float pH has uncertainty contributions from the pH sensor, the alkalinity estimate, and carbonate system equilibrium constants, resulting in a relative standard uncertainty in pCO2sw of 2.7% (or 11 µatm at pCO2sw of 400 µatm). The calculated pCO2sw from several floats spanning a range of oceanographic regimes are compared to existing climatologies. In some locations, such as the subantarctic zone, the float data closely match the climatologies, but in the polar Antarctic zone...
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Ano: 2017 URL: https://archimer.ifremer.fr/doc/00383/49462/49946.pdf
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Air-sea CO2 flux in the Pacific Ocean for the period 1990-2009 ArchiMer
Ishii, M.; Feely, R. A.; Rodgers, K. B.; Park, G. -h.; Wanninkhof, R.; Sasano, D.; Sugimoto, H.; Cosca, C. E.; Nakaoka, S.; Telszewski, M.; Nojiri, Y.; Fletcher, S. E. Mikaloff; Niwa, Y.; Patra, P. K.; Valsala, V.; Nakano, H.; Lima, I.; Doney, S. C.; Buitenhuis, E. T.; Aumont, Olivier; Dunne, J. P.; Lenton, A.; Takahashi, T..
Air-sea CO2 fluxes over the Pacific Ocean are known to be characterized by coherent large-scale structures that reflect not only ocean subduction and upwelling patterns, but also the combined effects of wind-driven gas exchange and biology. On the largest scales, a large net CO2 influx into the extratropics is associated with a robust seasonal cycle, and a large net CO2 efflux from the tropics is associated with substantial interannual variability. In this work, we have synthesized estimates of the net air-sea CO2 flux from a variety of products, drawing upon a variety of approaches in three sub-basins of the Pacific Ocean, i. e., the North Pacific extratropics (18-66 degrees N), the tropical Pacific (18 degrees S-18 degrees N), and the South Pacific...
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Ano: 2014 URL: http://archimer.ifremer.fr/doc/00192/30320/28789.pdf
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Global Carbon Budget 2015 ArchiMer
Le Quere, C.; Moriarty, R.; Andrew, R. M.; Canadell, J. G.; Sitch, S.; Korsbakken, J. I.; Friedlingstein, P.; Peters, G. P.; Andres, R. J.; Boden, T. A.; Houghton, R. A.; House, J. I.; Keeling, R. F.; Tans, P.; Arneth, A.; Bakker, D. C. E.; Barbero, L.; Bopp, L.; Chang, J.; Chevallier, F.; Chini, L. P.; Ciais, P.; Fader, M.; Feely, R. A.; Gkritzalis, T.; Harris, I.; Hauck, J.; Ilyina, T.; Jain, A. K.; Kato, E.; Kitidis, V.; Goldewijk, K. Klein; Koven, C.; Landschuetzer, P.; Lauvset, S. K.; Lefevre, N.; Lenton, A.; Lima, I. D.; Metzl, N.; Millero, F.; Munro, D. R.; Murata, A.; Nabel, J. E. M. S.; Nakaoka, S.; Nojiri, Y.; O'Brien, K.; Olsen, A.; Ono, T.; Perez, Florian; Pfeil, B.; Pierrot, D.; Poulter, B.; Rehder, G.; Roedenbeck, C.; Saito, S.; Schuster, U.; Schwinger, J.; Seferian, R.; Steinhoff, T.; Stocker, B. D.; Sutton, A. J.; Takahashi, T.; Tilbrook, B.; Van Der Laan-luijkx, I. T.; Van Der Werf, G. R.; Van Heuven, S.; Vandemark, D.; Viovy, N.; Wiltshire, A.; Zaehle, S.; Zeng, N..
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...
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Ano: 2015 URL: https://archimer.ifremer.fr/doc/00383/49442/49934.pdf
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