Enhanced Mid‐depth Southward Transport in the Northeast Atlantic at the Last Glacial Maximum Despite a Weaker AMOC

Menviel, Laurie; Spence, Paul; Skinner, Luke C; Tachikawa, Kazuyo; Friedrich, Tobias; Missiaen, Lise; Yu, Jimin

doi:10.1029/2019pa003793

Cited by 23 publications

(11 citation statements)

References 61 publications

(116 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A recent estimate, which integrates multiple proxy data sources, derives an increase of the land biosphere over the deglacial of about 850 Gt C (median estimate) (Jeltsch-Thömmes et al, 2019), in good accordance with another recent estimate based on a dynamic global vegetation model (Müller and Joos, 2020). The growth of coral reefs during sea level rise removed an additional 380 Gt C (Vecsei and Berger, 2004) to 1200 Gt C and more (Milliman, 1993;Kleypas, 1997;Ridgwell et al, 2003) from the ocean. Imbalances in the sedimentation-weathering cycle of carbon need to be considered on the multi-millennial timescales.…”

Section: A2 Results From the Bern3d Modelsupporting

confidence: 56%

Evaluating the biological pump efficiency of the Last Glacial Maximum ocean using δ13C

et al. 2021

View full text Add to dashboard Cite

Abstract. Although both physical and biological marine changes are required to explain the 100 ppm lower atmospheric pCO2 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 δ13C) 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 δ13C. We prepared a PI and LGM equilibrium simulation using the ocean model NorESM-OC with full biogeochemistry (including the carbon isotopes δ13C 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 δ13C exists that is 0.07 ‰ larger than the 0.19 ‰ data uncertainty. This error indicates that additional changes in ocean dynamics are needed to simulate an LGM ocean in agreement with proxy data.

show abstract

Section: A2 Results From the Bern3d Modelsupporting

confidence: 56%

Evaluating the biological pump efficiency of the Last Glacial Maximum ocean using δ13C

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Although a complete explanation for D-O variability remains elusive, a tentative scheme can be advanced. As there is strong coupling between sea-ice formation, deep-ocean convection in the Nordic Seas and the AMOC, a small perturbation in the heat or salt flux in the Nordic Seas, such as increased meltwater runoff from circum-Atlantic ice-sheets, a decrease in CO 2 or other climatic instabilities could lead to sea-ice advance 220 , a southward shift of the convection site 221 and AMOC weakening, thus leading to a stadial (Fig. 5b).…”

Section: [H1] Synthesis and Proposed Oscillatory Systemmentioning

confidence: 99%

An ice–climate oscillatory framework for Dansgaard–Oeschger cycles

Menviel

Skinner

Tarasov

et al. 2020

Nat Rev Earth Environ

View full text Add to dashboard Cite

Intermediate glacial states were characterized by large temperature changes in Greenland and the North Atlantic, referred to as Dansgaard-Oeschger (D-O) variability, with some transitions occurring over a few decades. D-O variability included changes in the strength of the Atlantic Meridional Overturning Circulation (AMOC), temperature changes of opposite sign and asynchronous timing in each hemisphere, shifts in the mean position of the Intertropical Convergence Zone and variations in atmospheric CO 2 . Palaeorecords and numerical studies indicate that the AMOC, with a tight coupling to Nordic Seas sea ice, is central to D-O variability, yet a complete theory remains elusive. In this Review, we synthesize the climatic expression and processes proposed to explain D-O cyclicity. What emerges is an oscillatory framework of the AMOC-sea-ice system, arising through feedbacks involving the atmosphere, cryosphere and the Earth's biogeochemical system. Palaeoclimate observations indicate that the AMOC might be more sensitive to perturbations than climate models currently suggest. Tighter constraints on AMOC stability are thus needed to project AMOC changes over the coming century as a response to anthropogenic carbon emissions. Progress can be achieved by additional observational constraints and numerical simulations performed with coupled climate-ice-sheet models. Key points• Abrupt warming events in Greenland and the North Atlantic, referred to as Dansgaard-Oeschger (D-O) events, were associated with changes in the strength of the Atlantic Meridional Overturning Circulation (AMOC), global climate and the carbon cycle.• AMOC changes, with a tight coupling to Nordic Seas sea ice, strongly affect the climate and marine carbon cycle, and, in turn, ice-sheet mass balance. Resultant changes in oceanic wind stress, ocean heat content and salinity feed back on the AMOC.• Owing to the different timescales of the feedbacks, self-sustained AMOC oscillations could emerge during intermediate glacial states. The boundary conditions of intermediate glacial states (size of ice sheets, Bering Strait throughflow and concentration of atmospheric CO 2 appear to be key in enabling these oscillations.• Perturbations other than changes in meltwater input, including changes in atmospheric CO 2 or Northern Hemisphere ice-sheet height and extent, can lead to, and may be required for, D-O variability.• The relatively large and frequent AMOC changes associated with D-O variability suggest a relatively low AMOC stability during intermediate glacial states. This low stability is not evident in all numerical experiments performed with 1 coupled climate models, implying that some might either overestimate the AMOC stability or have a mismatch in the required background state for the low AMOC stability regime.• Additional observations on the location and strength of North Atlantic Deep Water formation and its link with sea ice, as well as its improved representation in climate models, are needed to better constrain future climate projections.Palaeopr...

show abstract

“…Archer and Maier-Reimer, 1994;Ridgwell, 2003). Carbonate dissolution is calculated based on the ocean box or marine surface sediment calcium carbonate concentration relative to a depth-dependant saturation concentration (Morse and Berner, 1972;Millero, 1983). The isotopes of carbon are calculated applying various fractionation factors associated with the biological, physical and chemical fluxes of carbon (see Table S1 and O 'Neill et al, 2019).…”

Section: Model Descriptionmentioning

confidence: 99%

Sequential changes in ocean circulation and biological export productivity during the last glacial–interglacial cycle: a model–data study

et al. 2021

View full text Add to dashboard Cite

Abstract. We conduct a model–data analysis of the marine carbon cycle to understand and quantify the drivers of atmospheric CO2 concentration during the last glacial–interglacial cycle. We use a carbon cycle box model, “SCP-M”, combined with multiple proxy data for the atmosphere and ocean, to test for variations in ocean circulation and Southern Ocean biological export productivity across marine isotope stages spanning 130 000 years ago to the present. The model is constrained by proxy data associated with a range of environmental conditions including sea surface temperature, salinity, ocean volume, sea-ice cover and shallow-water carbonate production. Model parameters for global ocean circulation, Atlantic meridional overturning circulation and Southern Ocean biological export productivity are optimized in each marine isotope stage against proxy data for atmospheric CO2, δ13C and Δ14C and deep-ocean δ13C, Δ14C and CO32-. Our model–data results suggest that global overturning circulation weakened during Marine Isotope Stage 5d, coincident with a ∼ 25 ppm fall in atmospheric CO2 from the last interglacial period. There was a transient slowdown in Atlantic meridional overturning circulation during Marine Isotope Stage 5b, followed by a more pronounced slowdown and enhanced Southern Ocean biological export productivity during Marine Isotope Stage 4 (∼ −30 ppm). In this model, the Last Glacial Maximum was characterized by relatively weak global ocean and Atlantic meridional overturning circulation and increased Southern Ocean biological export productivity (∼ −20 ppm during MIS 3 and MIS 2). Ocean circulation and Southern Ocean biological export productivity returned to modern values by the Holocene period. The terrestrial biosphere decreased by 385 Pg C in the lead-up to the Last Glacial Maximum, followed by a period of intense regrowth during the last glacial termination and the Holocene (∼ 600 Pg C). Slowing ocean circulation, a colder ocean and to a lesser extent shallow carbonate dissolution contributed ∼ −70 ppm to atmospheric CO2 in the ∼ 100 000-year lead-up to the Last Glacial Maximum, with a further ∼ −15 ppm contributed during the glacial maximum. Our model results also suggest that an increase in Southern Ocean biological export productivity was one of the ingredients required to achieve the Last Glacial Maximum atmospheric CO2 level. We find that the incorporation of glacial–interglacial proxy data into a simple quantitative ocean transport model provides useful insights into the timing of past changes in ocean processes, enhancing our understanding of the carbon cycle during the last glacial–interglacial period.

show abstract

Enhanced Mid‐depth Southward Transport in the Northeast Atlantic at the Last Glacial Maximum Despite a Weaker AMOC

Cited by 23 publications

References 61 publications

Evaluating the biological pump efficiency of the Last Glacial Maximum ocean using <i>δ</i><sup>13</sup>C

Evaluating the biological pump efficiency of the Last Glacial Maximum ocean using <i>δ</i><sup>13</sup>C

An ice–climate oscillatory framework for Dansgaard–Oeschger cycles

Sequential changes in ocean circulation and biological export productivity during the last glacial–interglacial cycle: a model–data study

Contact Info

Product

Resources

About

Enhanced Mid‐depth Southward Transport in the Northeast Atlantic at the Last Glacial Maximum Despite a Weaker AMOC

Cited by 23 publications

References 61 publications

Evaluating the biological pump efficiency of the Last Glacial Maximum ocean using &lt;i&gt;δ&lt;/i&gt;&lt;sup&gt;13&lt;/sup&gt;C

Evaluating the biological pump efficiency of the Last Glacial Maximum ocean using &lt;i&gt;δ&lt;/i&gt;&lt;sup&gt;13&lt;/sup&gt;C

An ice–climate oscillatory framework for Dansgaard–Oeschger cycles

Sequential changes in ocean circulation and biological export productivity during the last glacial–interglacial cycle: a model–data study

Contact Info

Product

Resources

About

Evaluating the biological pump efficiency of the Last Glacial Maximum ocean using <i>δ</i><sup>13</sup>C

Evaluating the biological pump efficiency of the Last Glacial Maximum ocean using <i>δ</i><sup>13</sup>C