Variations in Arctic Ocean Dynamics and Hydrography under Early Last Interglacial and Future Warmings
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".