Publication Date:
2022-05-25
Description:
Author Posting. © The Author(s), 2015. This is the author's version of the work. It is posted here by permission of Elsevier for personal use, not for redistribution. The definitive version was published in Quaternary Science Reviews 125 (2015): 144-159, doi:10.1016/j.quascirev.2015.08.010.
Description:
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 paleocompilation
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 0:14h±0:20h at the
two standard error level, giving a glacial-to-modern change of 0:32h±0:20h.
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. Observations in the Indian and Pacific Oceans generally have 10 times
the weight of an Atlantic point in the computation of the global mean. 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 0:1h, emphasizing that knowledge of the circulation is vital to accurately map
δ13CDIC in three dimensions.
Description:
GG is supported
by NSF grants OIA-1124880 and OCE-1357121, the WHOI Ocean and Climate
Change Institute, and The Joint Initiative Awards Fund from the Andrew W. Mellon Foundation.
Keywords:
Paleoceanography
;
Physical Oceanography
;
Carbon reservoirs
;
Last Glacial Maximum
;
Inverse methods
Repository Name:
Woods Hole Open Access Server
Type:
Preprint
Format:
application/pdf
Permalink
