Evaluating the biological pump efficiency of the Last Glacial Maximum ocean using δ 13 C

Although both physical and biological marine changes are required to explain the 100 ppm lower atmospheric p CO 2 of the Last Glacial Maximum (LGM, ∼21 ka) as compared to preindustrial (PI) times, their exact contributions are debated. Proxies of past marine carbon cycling (such as δ 13 C ) document...

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Bibliographic Details
Published in:Climate of the Past
Main Authors: A. L. Morée, J. Schwinger, U. S. Ninnemann, A. Jeltsch-Thömmes, I. Bethke, C. Heinze
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2021
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Online Access:https://doi.org/10.5194/cp-17-753-2021
https://doaj.org/article/5d83bf7b982242edbe049f2ef3fae868
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Summary:Although both physical and biological marine changes are required to explain the 100 ppm lower atmospheric p CO 2 of the Last Glacial Maximum (LGM, ∼21 ka) as compared to preindustrial (PI) times, their exact contributions are debated. Proxies of past marine carbon cycling (such as δ 13 C ) document these changes and thus provide constraints for quantifying the drivers of long-term carbon cycle variability. This modeling study discusses the physical and biological changes in the ocean needed to simulate an LGM ocean in satisfactory agreement with proxy data, here focusing especially on δ 13 C . We prepared a PI and LGM equilibrium simulation using the ocean model NorESM-OC with full biogeochemistry (including the carbon isotopes δ 13 C and radiocarbon) and dynamic sea ice. The modeled LGM–PI differences are evaluated against a wide range of physical and biogeochemical proxy data and show agreement for key aspects of the physical ocean state within the data uncertainties. However, the lack of a simulated increase of regenerated nutrients for the LGM indicates that additional biogeochemical changes are required to simulate an LGM ocean in agreement with proxy data. In order to examine these changes, we explore the potential effects of different global mean biological pump efficiencies on the simulated marine biogeochemical tracer distributions. Through estimating which biological pump efficiency reduces LGM model–proxy biases the most, we estimate that the global mean biological pump efficiency increased from 38 % (PI) to up to 75 % (LGM). The drivers of such an increase in the biological pump efficiency may be both biological and related to circulation changes that are incompletely captured by our model – such as stronger isolation of Southern Source Water. Finally, even after considering a 75 % biological pump efficiency in the LGM ocean, a remaining model–proxy error in δ 13 C exists that is 0.07 ‰ larger than the 0.19 ‰ data uncertainty. This error indicates that additional changes in ocean dynamics are needed ...