The Arctic Ocean Circulation as simulated in a very high-resolution global ocean model (OCCAM)
Bibliographic record
Abstract
Abstract To investigate the Arctic Ocean Circulation, results from a high-resolution fully global ocean model have been analyzed. The results come from two runs of the Ocean Circulation and Climate Advanced Modelling project (OCCAM) model, developed and run by the Southampton Oceanography Centre, at 1/4° × 1/4° and 1/8° × 1/8° resolution. The model is based on the Bryan-Semtner-Cox model and has 36 vertical levels. Enhancements include a free surface, an improved advection scheme and an improved treatment of the surface fresh-water flux. The model is forced with a monthly European Centre for Medium-range Weather Forecasts wind-stress climatology. It reproduces many of the fine-scale features found in the Arctic Ocean. The analysis concentrates on several of the key features, including the highly energetic eddy system in the western part of the Beaufort Sea, East Greenland West and Spitsbergen Currents and the detailed structure of the marginal currents along the Siberian and Canadian coasts. Much of the paper is focused on the water transport through the Bering and Fram Straits and through the Canadian Archipelago. Comparisons of the model net fluxes through the straits against observations are presented. The analyses of the results demonstrate the ability of the fine-resolution model to simulate features such as small-scale eddies and jets, which have some agreement with the limited observations available.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".