Water properties and circulation in Arctic Ocean models
Bibliographic record
Abstract
As a part of the Arctic Ocean Model Intercomparison Project, results from 10 Arctic ocean/ice models are intercompared over the period 1970 through 1999. Models' monthly mean outputs are laterally integrated over two subdomains (Amerasian and Eurasian basins), then examined as functions of depth and time. Differences in such fields as averaged temperature and salinity arise from models' differences in parameterizations and numerical methods and from different domain sizes, with anomalies that develop at lower latitudes carried into the Arctic. A systematic deficiency is seen as AOMIP models tend to produce thermally stratified upper layers rather than the “cold halocline”, suggesting missing physics perhaps related to vertical mixing or to shelf‐basin exchanges. Flow fields pose a challenge for intercomparison. We introduce topostrophy, the vertical component of V × ∇ D where V is monthly mean velocity and ∇ D is the gradient of total depth, characterizing the tendency to follow topographic slopes. Positive topostrophy expresses a tendency for cyclonic “rim currents”. Systematic differences of models' circulations are found to depend strongly upon assumed roles of unresolved eddies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".