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Variations in Arctic Ocean Dynamics and Hydrography under Early Last Interglacial and Future Warmings

2025· preprint· en· W4411639977 on OpenAlexaboutno aff
Marie Sicard, Agatha M. de Boer, Helen K. Coxall, Torben Koenigk, Mehdi Pasha Karami, René Gabriel Navarro Labastida, Martin Jakobsson, Matt O’Regan, Flor Vermassen

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsnot available
Fundersnot available
KeywordsHydrographyOceanographyInterglacialArcticClimatologyThe arcticGeographyEnvironmental scienceGeologyGlacial periodPaleontology

Abstract

fetched live from OpenAlex

Using outputs from eight CMIP6/PMIP4 models, we analyze the hydrographic and surface ocean circulation differences across three climate states: the pre-industrial (PI; 1850 CE), the Last Interglacial (LIG; 127 ka BP), characterized by strong summer insolation, and a future warming scenario driven by gradually increasing atmospheric CO2 and with similar annual Arctic sea-ice volume to the LIG. In the LIG experiments, an anomalous cyclonic circulation over Greenland and surrounding seas enhances the Baffin and Labrador currents, while slightly weakening the East Greenland Current relative to PI. These changes affect sea-ice and water export on both sides of Greenland. Most models also show a strengthened North Atlantic Subpolar Gyre (SPG) and increased volume transports through the Fram Strait and Barents Sea Opening. However, this does not always correlate with a larger heat transport into the Arctic. In contrast, the CO2-forced simulations show a weakened SPG, but more amount of water and heat are carried towards the Arctic compared with the PI period. Consequently, temperatures of the surface and subsurface waters are higher in the Eurasian Basin and sea-ice decline in the Barents Sea is more pronounced compared with the PI and LIG periods. These changes in the CO2-forced experiments closely resemble the ongoing Arctic Atlantification, whereas evidence for a similar process during the LIG is less clear.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.004
GPT teacher head0.208
Teacher spread0.203 · 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 designObservational
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

Citations0
Published2025
Admission routes1
Has abstractyes

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