The fate of freshwater around Greenland: insights from an eddying coupled general circulation model
Bibliographic record
Abstract
In the sub-polar North Atlantic, the accumulation of fresh meltwaters from Greenland and the Arctic can impact the strength of the climatically important Atlantic Meridional Overturning Circulation. In this study I pin down the role of eddies in transporting these freshwaters away from their sources and identify connections between the accumulation, destruction and import of low-salinity waters around the coast of Greenland. I use ten years of daily outputs from the coupled ICON general circulation model, run with a 10~km atmosphere and a 5~km (eddy resolving) ocean. Comparing transports of low-salinity waters with traditionally defined freshwater transports, I find freshwater transports around Greenland do not describe pathways of low-salinity waters. Offshore transports of freshwater are often found to result from onshore transports of saline water, with low-salinity waters remaining confined to the Greenland shelf. Across shelf exchanges are relatively weak around the East Coast and become appreciable only on the Western coast. Eddy transports of low-salinity waters are weak apart from on the West Coast of Greenland and near Denmark Strait during wintertime. Balances between the import of low-salinity waters, their storage and their destruction via mixing vary depending upon both the season and region in question, implying that where and when freshwater is input around Greenland will affect both its salinity and the time elapsed upon its eventual arrival in the Labrador Sea.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".