Effectiveness of wind-constrained sea-ice momentum on formation of sea-ice distribution and upper halocline of Arctic Ocean in climate model
Bibliographic record
Abstract
Abstract Initialization of sea ice and the upper halocline in the Arctic Ocean is crucial for sea-ice prediction, but their representation in climate models still remains biased. Here, using historical and four different simulations by a single climate model, we find that constraining the sea-ice momentum by surface wind stress contributes to a better representation of the sea-ice velocity, area, and concentration. Moreover, the wind-constrained sea-ice drift modifies the underlying ocean structure via ice-ocean stress, leading to an improved climatological halocline’s vertical structure in the Canada Basin. This is because the excessively represented negative wind and ice-ocean stress curl in the climate model is weakened when constraining the sea-ice momentum and consequently the downward vertical speed, including the Ekman pumping, is also weakened at depths of 0–500 m, alleviating the deepening of isohalines. From these results, the improvement of sea-ice and ocean states by constraining sea-ice momentum is expected to make sea-ice prediction more accurate.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".