Inverse estimates of anthropogenic CO2 uptake, transport, and storage by the ocean
Figure S2a: Column inventory of the time-dependent basis function (mol dye/m3) for regions 1–12 of the 24 model regions shown in Figure 2 of the manuscript in 1995, calculated using the PRINCE-2 OGCM. (3.771Mb)
Figure S2b: Column inventory of the time-dependent basis function (mol dye/m3) for regions 13–24 of the 24 model regions shown in Figure 2 of the manuscript in 1995, calculated using the PRINCE-2 OGCM. (3.761Mb)
Figure S3: Comparison between the atmospheric CO2 perturbation and the global, annual mean air-sea CO2 flux using four different OGCMs: MIT, NCAR, PRINCE, and UL. (1.661Mb)
Figure S4: Covariance between regional flux estimates for the 24 region aggregation (105 Pg C yr−1), scaled to 1995). (3.153Mb)
Figure S5: The weighted mean inverse estimates of anthropogenic carbon (Pg C/yr) from this study (white bars) compared with the inverse anthropogenic carbon estimates of Gloor et al.  (gray bars). (1.116Mb)
Figure S6: Column inventory of the time-dependent basis function (mol dye/m2) for region 9 in 1995, calculated using the nine OGCMs. (8.760Mb)
Figure S7: Zonal mean of the time-dependent basis function (mol dye/m3) for region 9 in 1995, calculated using the nine OGCMs. (3.339Mb)
Figure S8: Comparison between the atmospheric CO2 perturbation and the anthropogenic carbon storage from a forward simulation of the PRINCE-2 model integrated over several regions in the Atlantic Ocean. (1014.Kb)
Figure S9: Zonally, vertically integrated anthropogenic carbon transport by the global, (top), Atlantic (center), and Indo-Pacific (bottom) Oceans from 1765–1995. (1.382Mb)
Figure S10: The zonally averaged hypothetical bias added to the data-based anthropogenic carbon estimates to construct the ‘Matsumoto corrected’ scenario. (1.530Mb)
Figure S11: Zonally, vertically integrated difference between the forward and inverse anthropogenic carbon storage estimates over the global, (top), Atlantic (center),and Indo-Pacific (bottom) Oceans from 1765–1995. (2.180Mb)
Table S1: Summarizes differences between the five different configurations of the PRINCE model. (1.159Kb)
Table S2: Inverse anthropogenic carbon flux estimates based on basis functions from ten different OCGMS and their weighted mean, weighted standard deviation, and range (Pg C yr−1, scaled to 1995). (2.777Kb)
Table S3: Optimal coefficients and standard deviations of a multiple linear regression fit of anthropogenic carbon concentrations estimated using lower and upper limits of the C:O ratio to observed AOU and anthropogenic carbon as discussed in Section 4 of the Text S1 online supplement. (473bytes)
Table S4: Inverse anthropogenic carbon flux estimates from the PRINCE-2 model based on the GLODAP anthropogenic carbon data set and three scenarios designed to test the sensitivity of the inverse estimates to biases associated with estimating the anthropogenic carbon from the observations (Pg C yr−1, scaled to 1995). (1.529Kb)
Table S5: The difference between the anthropogenic carbon uptake in the forward model simulations in 1995 and the inverse flux estimates using the same models scaled to 1995 (Pg C yr−1). (1.958Kb)
Text S3: Discussion of the differences between the UL model and the other participating models in the North Atlantic. (49.83Kb)
Mikaloff Fletcher, Sara E.
Jacobson, Andrew R.
Doney, Scott C.
Follows, Michael J.
Muller, Simon A.
Sarmiento, Jorge L.
MetadataShow full item record
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.
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.
Showing items related by title, author, creator and subject.
Krishnamurthy, Aparna; Moore, J. Keith; Mahowald, Natalie M.; Luo, Chao; Doney, Scott C.; Lindsay, Keith; Zender, Charles S. (American Geophysical Union, 2009-08-28)We present results from transient sensitivity studies with the Biogeochemical Elemental Cycling (BEC) ocean model to increasing anthropogenic atmospheric inorganic nitrogen (N) and soluble iron (Fe) deposition over the ...
Bivalves as indicators of environmental variation and potential anthropogenic impacts in the southern Barents Sea Carroll, Michael L.; Johnson, Beverly J.; Henkes, Gregory A.; McMahon, Kelton W.; Voronkov, Andrey; Ambrose, William G.; Denisenko, Stanislav G. (2009-04)Identifying patterns and drivers of natural variability in populations is necessary to gauge potential effects of climatic change and the expected increases in commercial activities in the Arctic on communities and ...
Using present-day observations to detect when anthropogenic change forces surface ocean carbonate chemistry outside preindustrial bounds Sutton, Adrienne J.; Sabine, Chris L.; Feely, Richard A.; Cai, Wei-Jun; Cronin, Meghan; McPhaden, Michael; Morell, Julio M.; Newton, Jan A.; Noh, Jae Hoon; Ólafsdóttir, Sólveig R.; Salisbury, Joseph E.; Send, Uwe; Vandemark, Douglas; Weller, Robert A. (Copernicus Publications on behalf of the European Geosciences Union, 2016-09-13)One of the major challenges to assessing the impact of ocean acidification on marine life is detecting and interpreting long-term change in the context of natural variability. This study addresses this need through a global ...