Response of the North Atlantic dynamic sea level and circulation to Greenland meltwater and climate change in an eddy-permitting ocean model
Bibliographic record
Abstract
The response of the North Atlantic dynamic sea surface height (SSH) and ocean circulation to Greenland Ice Sheet (GrIS) meltwater fluxes is investigated using a high-resolution model. The model is forced with either present-day-like or projected warmer climate conditions. In general, the impact of meltwater on the North Atlantic SSH and ocean circulation depends on the surface climate. In the two major regions of deep water formation, the Labrador Sea and the Nordic Seas, the basin-mean SSH increases with the increase of the GrIS meltwater flux. This SSH increase correlates with the decline of the Atlantic meridional overturning circulation (AMOC). However, while in the Labrador Sea the warming forcing and GrIS meltwater input lead to sea level rise, in the Nordic Seas these two forcings have an opposite influence on the convective mixing and basin-mean SSH (relative to the global mean). The warming leads to less sea-ice cover in the Nordic Seas, which favours stronger surface heat loss and deep mixing, lowering the SSH and generally increasing the transport of the East Greenland Current. In the Labrador Sea, the increased SSH and weaker deep convection are reflected in the decreased transport of the Labrador Current (LC), which closes the subpolar gyre in the west. Among the two major components of the LC transport, the thermohaline and bottom transports, the former is less sensitive to the GrIS meltwater fluxes under the warmer climate. The SSH difference across the LC, which is a component of the bottom velocity, correlates with the long-term mean AMOC rate.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".