Modelling of the Arctic Ocean and Labrador Sea at 1/60th Degree
Bibliographic record
Abstract
Our group has carried out simulations of the Labrador Sea at 1/60th and shown that very-high resolution significantly improves the model solution. That resolution, by representing the mesoscale and part of the sub-mesoscale significantly improves the simulation of boundary current system, eddies and shelf-basin exchange, with the small-scale processes combining to also improve the large-scale circulation and overturning. Given such improvements for the Labrador Sea, we now examine modelling the entire Arctic Ocean and the subpolar North Atlantic Ocean north of 53N latitude. The configuration is named ARC60. The experiment also includes an iceberg module and tidal forcing. Here we present some of our ongoing analysis using the two very high resolution configurations and how it changes the solution compared to lower resolution simulations. We explore questions related to water formation in the Labrador Sea and Greenland melt, behavior of the Labrador Current and the Deep Western Boundary Current. We also explore the impact of Greenland runoff on driving coastal seasonal features in Melville Bay. Finally we look at eddies and small scale processes in the Arctic Ocean and Beaufort Gyre.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".