Abstract
A paleo-data compilation with 492 δ13C and δ18O observations provides the opportunity to better sample the Last Glacial Maximum (LGM) and infer its global properties, such as the mean δ13C of dissolved inorganic carbon. Here, the paleo-compilation is used to reconstruct a steady-state water-mass distribution for the LGM, that in turn is used to map the data onto a 3D global grid. A global-mean marine δ13C value and a self-consistent uncertainty estimate are derived using the framework of state estimation (i.e., combining a numerical model and observations). The LGM global-mean δ13C is estimated to be 0.14‰ ± 0.20‰ at the two standard error level, giving a glacial-to-modern change of 0.32‰ ± 0.20‰. The magnitude of the error bar is attributed to the uncertain glacial ocean circulation and the lack of observational constraints in the Pacific, Indian, and Southern Oceans. To halve the error bar, roughly four times more observations are needed, although strategic sampling may reduce this number. If dynamical constraints can be used to better characterize the LGM circulation, the error bar can also be reduced to 0.05 to 0.1‰, emphasizing that knowledge of the circulation is vital to accurately map δ13C in three dimensions.
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