On the Robustness of Air-Sea Flux Estimates of Anthropogenic Carbon from Ocean Inversions Sara Mikaloff Fletcher, Nicolas Gruber, Andrew Jacobson, Scott Doney, Stephanie Dutkiewicz, Mick Follows, Keith Lindsay, Dimitris Menemenlis, Anne Mouchet GLODAP Dataset

Anthropogenic Carbon (μmol/Kg) C ant is the component of DIC due to elevated atmospheric CO 2 C ant is the component of DIC due to elevated atmospheric CO 2 Estimated from observations of DIC and other ocean tracers using the ∆C* method (Gruber et al., 1996). Estimated from observations of DIC and other ocean tracers using the ∆C* method (Gruber et al., 1996). Latitude Depth (m)

The Ocean Inversion The inverse model finds the combination of carbon fluxes from a discrete number of ocean regions that optimally fit the observations The inverse model finds the combination of carbon fluxes from a discrete number of ocean regions that optimally fit the observations C j ant =Anthropogenic carbon calculated from observations at site i C j ant =Anthropogenic carbon calculated from observations at site i x i = Magnitude of the flux from region i x i = Magnitude of the flux from region i H i,j = The modelled response of a unit flux from region i at station j, called the basis function H i,j = The modelled response of a unit flux from region i at station j, called the basis function ε=Error associated with the method ε=Error associated with the method The model regions and observations used in the ocean inversion

Key Questions Are the inverse estimates robust with respect to ocean transport? Are the inverse estimates robust with respect to ocean transport? Are the inverse estimates robust with respect to uncertainty in C ant ? Are the inverse estimates robust with respect to uncertainty in C ant ? What have we learned? What have we learned?

Anthropogenic Carbon Flux Scaled to 1995 S. Ocean S. Mid. Lat. 18S-44S Tropics 18S-18N N. Mid. Lat. 18N-49N N. Ocean North

Flux Storage Transport (Positive = North) ECCO MIT PRINCE-LL PRINCE-HH PRINCE-LHS PRINCE-RDS PRINCE-PSS UL

Uncertainty in Anthropogenic Carbon Estimates Matsumoto and Gruber (submitted, 2004) Matsumoto and Gruber (submitted, 2004) Stoichiometric ratios used to remove the signal due to biological activity (Anderson and Sarmiento, 1994) Stoichiometric ratios used to remove the signal due to biological activity (Anderson and Sarmiento, 1994) –Low R c:o –High R c:o 0 Anthropogenic Carbon Bias Potential Density 27.4 Bias=10% Bias=7%

Anthropogenic Carbon Bias (PRINCE-RDS model) North S. Ocean S. Mid. Lat. 18S-44S Tropics 18S-18N N. Mid. Lat. 18N-49N N. Ocean

Global Total Anthropogenic Carbon Uptake Scaled to 1995 (Pg C/yr) Model OCMIP-2 forward model Inverse Model ECCONA2.10 MITNA2.20 MOM-LL MOM-HH MOM-LHS MOM-RDS MOM-RDS UL Mean (Range) 2.26 (1.84 – 2.94) 2.23 (1.93 – 2.77)

Inverse Model – Forward Model S. Ocean S. Mid. Lat. 18S-44S Tropics 18S-18N N. Mid. Lat. 18N-49N N. Ocean North

Conclusions The broad features of the ocean inversion are robust The broad features of the ocean inversion are robust –The greatest source of uncertainty is model transport –The largest spread between models occurs in the Southern Ocean The anthropogenic carbon inventories call for: The anthropogenic carbon inventories call for: –Global anthropogenic carbon uptake of 1.95 to 2.77 Pg C/yr –Equator-ward transport from high-latitudes, with storage at mid- latitudes –Some cross-equatorial transport Compared to the forward simulations, the inverse estimates find: Compared to the forward simulations, the inverse estimates find: –Greater uptake in the Southern Ocean between 44S and 58S and the Indian Ocean –Less uptake throughout most of the pacific ocean

Sources of Uncertainty in the Inverse Estimates Modeled transport Anthropogenic Carbon Estimates Implicit assumptions –O–O–O–Ocean transport is in steady state –A–A–A–Anthropogenic carbon uptake is proportional to the atmospheric carbon perturbation Inverse methodology –A–A–A–Aggregation error