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Record W2793356036 · doi:10.1007/s00382-018-4157-8

Response of a comprehensive climate model to a broad range of external forcings: relevance for deep ocean ventilation and the development of late Cenozoic ice ages

2018· article· en· W2793356036 on OpenAlexafffund
Eric D. Galbraith, Casimir de Lavergne

Bibliographic record

VenueClimate Dynamics · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversité de MontréalMcGill University
FundersUniversity of TorontoCanada Foundation for InnovationMinisterio de Economía y CompetitividadCompute Canada
KeywordsGeologyNorth Atlantic Deep WaterAntarctic Bottom WaterIce sheetAntarctic ice sheetClimatologyOceanographyIce-sheet modelCryosphereSea iceThermohaline circulationAntarctic sea ice

Abstract

fetched live from OpenAlex

Over the past few million years, the Earth descended from the relatively warm and stable climate of the Pliocene into the increasingly dramatic ice age cycles of the Pleistocene. The influences of orbital forcing and atmospheric CO 2 on land-based ice sheets have long been considered as the key drivers of the ice ages, but less attention has been paid to their direct influences on the circulation of the deep ocean. Here we provide a broad view on the influences of CO 2 , orbital forcing and ice sheet size according to a comprehensive Earth system model, by integrating the model to equilibrium under 40 different combinations of the three external forcings. We find that the volume contribution of Antarctic (AABW) vs. North Atlantic (NADW) waters to the deep ocean varies widely among the simulations, and can be predicted from the difference between the surface densities at AABW and NADW deep water formation sites. Minima of both the AABW-NADW density difference and the AABW volume occur near interglacial CO 2 (270–400 ppm). At low CO 2 , abundant formation and northward export of sea ice in the Southern Ocean contributes to very salty and dense Antarctic waters that dominate the global deep ocean. Furthermore, when the Earth is cold, low obliquity (i.e. a reduced tilt of Earth’s rotational axis) enhances the Antarctic water volume by expanding sea ice further. At high CO 2 , AABW dominance is favoured due to relatively warm subpolar North Atlantic waters, with more dependence on precession. Meanwhile, a large Laurentide ice sheet steers atmospheric circulation as to strengthen the Atlantic Meridional Overturning Circulation, but cools the Southern Ocean remotely, enhancing Antarctic sea ice export and leading to very salty and expanded AABW. Together, these results suggest that a ‘sweet spot’ of low CO 2 , low obliquity and relatively small ice sheets would have poised the AMOC for interruption, promoting Dansgaard–Oeschger-type abrupt change. The deep ocean temperature and salinity simulated under the most representative ‘glacial’ state agree very well with reconstructions from the Last Glacial Maximum (LGM), which lends confidence in the ability of the model to estimate large-scale changes in water-mass geometry. The model also simulates a circulation-driven increase of preformed radiocarbon reservoir age, which could explain most of the reconstructed LGM-preindustrial ocean radiocarbon change. However, the radiocarbon content of the simulated glacial ocean is still higher than reconstructed for the LGM, and the model does not reproduce reconstructed LGM deep ocean oxygen depletions. These ventilation-related disagreements probably reflect unresolved physical aspects of ventilation and ecosystem processes, but also raise the possibility that the LGM ocean circulation was not in equilibrium. Finally, the simulations display an increased sensitivity of both surface air temperature and AABW volume to orbital forcing under low CO 2 . We suggest that this enhanced orbital sensitivity contributed to the development of the ice age cycles by amplifying the responses of climate and the carbon cycle to orbital forcing, following a gradual downward trend of CO 2 .

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.278
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations149
Published2018
Admission routes2
Has abstractyes

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