The DOI matches its Crossref record; 61 of the 61 references it cites were found in a registry or an index.
Data-based estimates of the ocean carbon sink variability – first results of the Surface Ocean p CO 2 Mapping intercomparison (SOCOM)
Open accessAbstract
Abstract. Using measurements of the surface-ocean CO2 partial pressure (pCO2) and 14 different pCO2 mapping methods recently collated by the Surface Ocean pCO2 Mapping intercomparison (SOCOM) initiative, variations in regional and global sea–air CO2 fluxes are investigated. Though the available mapping methods use widely different approaches, we find relatively consistent estimates of regional pCO2 seasonality, in line with previous estimates. In terms of interannual variability (IAV), all mapping methods estimate the largest variations to occur in the eastern equatorial Pacific. Despite considerable spread in the detailed variations, mapping methods that fit the data more closely also tend to agree more closely with each other in regional averages. Encouragingly, this includes mapping methods belonging to complementary types – taking variability either directly from the pCO2 data or indirectly from driver data via regression. From a weighted ensemble average, we find an IAV amplitude of the global sea–air CO2 flux of 0.31 PgC yr−1 (standard deviation over 1992–2009), which is larger than simulated by biogeochemical process models. From a decadal perspective, the global ocean CO2 uptake is estimated to have gradually increased since about 2000, with little decadal change prior to that. The weighted mean net global ocean CO2 sink estimated by the SOCOM ensemble is −1.75 PgC yr−1 (1992–2009), consistent within uncertainties with estimates from ocean-interior carbon data or atmospheric oxygen trends.
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Cites
The NCEP/NCAR 40-Year Reanalysis Project
Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, J., et al. (1996) · Bulletin of the American Meteorological Society · doi:10.1175/1520-0477(1996)077<0437:tnyrp>2.0.co;2 · Cited by 28,360
Uppala, S. M., KÅllberg, P. W., Simmons, A. J., Andrae, U., Bechtold, V. D. C., Fiorino, M., Gibson, J. K., Haseler, J., Hernandez, A., Kelly, G. A., et al. (2005) · Quarterly Journal of the Royal Meteorological Society · doi:10.1256/qj.04.176 · Cited by 6,804
(2013) · Cited by 6,752
Relationship between wind speed and gas exchange over the ocean
Wanninkhof, R. (1992) · Journal of Geophysical Research: Oceans · doi:10.1029/92jc00188 · Cited by 4,737
Self-citationThe Oceanic Sink for Anthropogenic CO 2
Sabine, C. L., Feely, R. A., Gruber, N., Key, R. M., Lee, K., Bullister, J. L., Wanninkhof, R., Wong, C. S., Wallace, D. W. R., Tilbrook, B., et al. (2004) · Science · doi:10.1126/science.1097403 · Cited by 4,035
Self-citationClimatological Atlas of the World Ocean
Levitus, S. (1983) · Eos, Transactions American Geophysical Union · doi:10.1029/eo064i049p00962-02 · Cited by 3,078
Takahashi, T., Sutherland, S. C., Wanninkhof, R., Sweeney, C., Feely, R. A., Chipman, D. W., Hales, B., Friederich, G., Chavez, F., Sabine, C., et al. (2009) · Deep Sea Research Part II: Topical Studies in Oceanography · doi:10.1016/j.dsr2.2008.12.009 · Cited by 2,346
Self-citationAN OPERATIONAL OBJECTIVE ANALYSIS SYSTEM
CRESSMAN, G. P. (1959) · Monthly Weather Review · doi:10.1175/1520-0493(1959)087<0367:aooas>2.0.co;2 · Cited by 1,798
GFDL's CM2 Global Coupled Climate Models. Part I: Formulation and Simulation Characteristics
Delworth, T. L., Broccoli, A. J., Rosati, A., Stouffer, R. J., Balaji, V., Beesley, J. A., Cooke, W. F., Dixon, K. W., Dunne, J., Dunne, K. A., et al. (2006) · Journal of Climate · doi:10.1175/jcli3629.1 · Cited by 1,690
The global climatology of an interannually varying air-sea flux data set.
Large, W. G., & Yeager, S. G. (2009) · Climate Dynamics · doi:10.1007/s00382-008-0441-3 · Cited by 1,636
Cited by
Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Hauck, J., Olsen, A., Peters, G. P., Peters, W., Pongratz, J., Sitch, S., et al. (2020) · Earth System Science Data · doi:10.5194/essd-12-3269-2020 · Cited by 2,544
Self-citationLe Quéré, C., Andrew, R. M., Friedlingstein, P., Sitch, S., Hauck, J., Pongratz, J., Pickers, P. A., Korsbakken, J. I., Peters, G. P., Canadell, J. G., et al. (2018) · Earth System Science Data · doi:10.5194/essd-10-2141-2018 · Cited by 1,645
Self-citationFriedlingstein, P., Jones, M. W., O'Sullivan, M., Andrew, R. M., Bakker, D. C. E., Hauck, J., Le Quéré, C., Peters, G. P., Peters, W., Pongratz, J., et al. (2022) · Earth System Science Data · doi:10.5194/essd-14-1917-2022 · Cited by 1,285
Self-citationBakker, D. C. E., Pfeil, B., Landa, C. S., Metzl, N., O'Brien, K. M., Olsen, A., Smith, K., Cosca, C., Harasawa, S., Jones, S. D., et al. (2016) · Earth System Science Data · doi:10.5194/essd-8-383-2016 · Cited by 681
Self-citationInterannual variation of terrestrial carbon cycle: Issues and perspectives
Piao, S., Wang, X., Wang, K., Li, X., Bastos, A., Canadell, J. G., Ciais, P., Friedlingstein, P., & Sitch, S. (2020) · Global Change Biology · doi:10.1111/gcb.14884 · Cited by 486
Metadata
- Authors
- Rödenbeck, C., Bakker, D. C. E., Gruber, N., Iida, Y., Jacobson, A. R., Jones, S., Landschützer, P., Metzl, N., Nakaoka, S., Olsen, A., Park, G.-H., Peylin, P., Rodgers, K. B., Sasse, T. P., Schuster, U., Shutler, J. D., Valsala, V., Wanninkhof, R., & Zeng, J.
- Venue
- Biogeosciences
- Publisher
- Copernicus GmbH
- Published
- 2015-12-11
- Volume
- 12
- Issue
- 23
- Pages
- 7251-7278
- ISSN
- 1726-4170 (ISSN-L)
- 1726-4189
- OpenAlex
- W1905022141
- Cited by
- 296
- References
- 61
- FWCI
- 12.29
- Type
- journal article
- Language
- en
- Open access
- gold
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- Rödenbeck, C., Bakker, D. C. E., Gruber, N., Iida, Y., Jacobson, A. R., Jones, S., Landschützer, P., Metzl, N., Nakaoka, S., Olsen, A., Park, G.-H., Peylin, P., Rodgers, K. B., Sasse, T. P., Schuster, U., Shutler, J. D., Valsala, V., Wanninkhof, R., & Zeng, J. (2015). Data-based estimates of the ocean carbon sink variability – first results of the Surface Ocean p CO 2 Mapping intercomparison (SOCOM). Biogeosciences. https://doi.org/10.5194/bg-12-7251-2015
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