Sensitivity of Ice Drift to Form Drag and Ice Strength Parameterization in a Coupled Ice–Ocean Model
Bibliographic record
Abstract
A pan-Arctic sea-ice–ocean prediction system is assessed in terms of its ability to predict sea-ice velocity. This system is based on the Regional Ice Ocean Prediction System running operationally at the Canadian Centre for Meteorological and Environmental Prediction. A form drag parameterization is implemented in the system to allow spatially and temporally varying neutral drag coefficients depending on the sea-ice morphological characteristics. Simulated ice velocity is assessed using data from the International Arctic Buoy Programme, as well as ice motion derived from Environment and Climate Change Canada’s synthetic aperture radar automated ice-tracking system. Results indicate that introducing the form drag parameterization systematically increases the sea-ice velocity and exacerbates a positive bias in summer already present in the previous version in which constant neutral drag coefficients were used. The ice strength parameterization used in the model rheology is found to affect the simulated ice drift significantly. Introducing modifications to the ice strength formulation and the empirical parameters helped alleviate the ice velocity bias.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".