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Despite their importance for Earth’s climate and paleoceanography, the cycles of carbon (C) and its isotope¹³C in the ocean are not well understood. Models typically do not decompose C and¹³C storage caused by different physical, biological, and chemical processes, which makes interpreting results difficult. Consequently, basic observed features, such as the decreased carbon isotopic signature (δ¹³C_DIC) of the glacial ocean remain unexplained. Here, we review recent progress in decomposing Dissolved Inorganic Carbon (DIC) into preformed and regenerated components, extend a precise and complete decomposition to δ¹³C_DIC, and apply it to data-constrained model simulations of the Preindustrial (PI) and Last Glacial Maximum (LGM) oceans. Regenerated components, from respired soft-tissue organic matter and dissolved biogenic calcium carbonate, are reduced in the LGM, indicating a decrease in the active part of the biological pump. Preformed components increase carbon storage and decrease δ¹³C_DICby 0.55 ‰ in the LGM. We separate preformed into saturation and disequilibrium components, each of which have biological and physical contributions. Whereas the physical disequilibrium in the PI is negative for both DIC and δ¹³C_DIC, and changes little between climate states, the biological disequilibrium is positive for DIC but negative for δ¹³C_DIC, a pattern that is magnified in the LGM. The biological disequilibrium is the dominant driver of the increase in glacial ocean C and the decrease in δ¹³C_DIC, indicating a reduced sink of biological carbon. Overall, in the LGM, biological processes increase the ocean’s DIC inventory by 355 Pg more than in the PI, reduce its mean δ¹³C_DICby an additional 0.52 ‰, and contribute 60 ppm to the lowering of atmospheric CO₂. Spatial distributions of the δ¹³C_DICcomponents are presented. Commonly used approximations based on apparent oxygen utilization and phosphate are evaluated and shown to have large errors. 

Input data required for a simulation of the preindustrial control (PIC) simulation with the OSU version of the University of Victoria climate model (version 2.9) with the Model of Ocean Biogeochemistry and Isotopes (MOBI2.2). 

Input data required for a simulation of the Last Glacial Maximum (LGM) simulation with the OSU version of the University of Victoria climate model (version 2.9.10) with the Model of Ocean Biogeochemistry and Isotopes (MOBI2.2). 

OSU-UVic Climate Model of Intermediate Complexity with Model of Ocean Biogeochemistry and Isotopes (MOBI2.2). New features in this release include Nathaniel Fillman's carbon and C13 decomposition code and Samar Khatiwala's Pa/Th code. 

In paleoceanography, carbon and oxygen stable isotope ratios from benthic foraminifera are used as tracers of physical and biogeochemical properties of the deep ocean. We present the first version of the Ocean Carbon Cycling working group database,  of stable isotope ratios of oxygen and carbon from benthic foraminifera from deep ocean sediment cores from the Last Glacial Maximum (LGM, 23-20 ky before present (BP)) to the Holocene (<10 ky BP) with a particular focus on the early last deglaciation (20-15 ky BP). It includes 287 globally distributed coring sites, with metadata, isotopic and chronostratigraphic information, and age models. A quality check was performed for all data and age models. Sites with at least millennial resolution were preferred, because the main goal is to resolve ocean changes associated with the last deglaciation on at least millennial timescales. Software tools were produced to access and analyze the data, and are included with this publication. Deep water mass structure as well as differences between the early deglaciation and LGM are captured by the data in the compilation, even though its coverage is still sparse in many ocean regions. We find high correlations among time series calculated with different age models at sites that allow such analysis. The database provides a useful dynamical approach to map physical and biogeochemical changes of the ocean throughout the last deglaciation.</p> Custom python scripts to read and analyze the data base may be found in https://github.com/juanmuglia/OC3-python-scripts and in OC3-python-scripts.zip in this repository. plots_d13c.pdf and plots_d18o.pdf contain time series for all sites and available age models. 

Abstract Reconstructing the circulation, mixing and carbon content of the Last Glacial Maximum ocean remains challenging. Recent hypotheses suggest that a shoaled Atlantic meridional overturning circulation or increased stratification would have reduced vertical mixing, isolated the abyssal ocean and increased carbon storage, thus contributing to lower atmospheric CO₂concentrations. Here, using an ensemble of ocean simulations, we evaluate impacts of changes in tidal energy dissipation due to lower sea levels on ocean mixing, circulation, and carbon isotope distributions. We find that increased tidal mixing strengthens deep ocean flow rates and decreases vertical gradients of radiocarbon andδ¹³C in the deep Atlantic. Simulations with a shallower overturning circulation and more vigorous mixing fit sediment isotope data best. Our results, which are conservative, provide observational support that vertical mixing in the glacial Atlantic may have been enhanced due to more vigorous tidal dissipation, despite shoaling of the overturning circulation and increases in stratification. 

Abstract We present the first version of the Ocean Circulation and Carbon Cycling (OC3) working group database, of oxygen and carbon stable isotope ratios from benthic foraminifera in deep ocean sediment cores from the Last Glacial Maximum (LGM, 23-19 ky) to the Holocene (<10 ky) with a particular focus on the early last deglaciation (19-15 ky BP). It includes 287 globally distributed coring sites, with metadata, isotopic and chronostratigraphic information, and age models. A quality check was performed for all data and age models, and sites with at least millennial resolution were preferred. Deep water mass structure as well as differences between the early deglaciation and LGM are captured by the data, even though its coverage is still sparse in many regions. We find high correlations among time series calculated with different age models at sites that allow such analysis. The database provides a useful dynamical approach to map physical and biogeochemical changes of the ocean throughout the last deglaciation.