Internal Waves in the Arctic: Influence of Ice Concentration, Ice Roughness, and Surface Layer Stratification
Bibliographic record
Abstract
Abstract The Arctic ice cover influences the generation, propagation, and dissipation of internal waves, which in turn may affect vertical mixing in the ocean interior. The Arctic internal wavefield and its relationship to the ice cover is investigated using observations from Ice‐Tethered Profilers with Velocity and Seaglider sampling during the 2014 Marginal Ice Zone experiment in the Canada Basin. Ice roughness, ice concentration, and wind forcing all influenced the daily to seasonal changes in the internal wavefield. Three different ice concentration thresholds appeared to determine the evolution of internal wave spectral energy levels: (1) the initial decrease from 100% ice concentration after which dissipation during the surface reflection was inferred to increase, (2) the transition to 70–80% ice concentration when the local generation of internal waves increased, and (3) the transition to open water that was associated with larger‐amplitude internal waves. Ice roughness influenced internal wave properties for ice concentrations greater than approximately 70–80%: smoother ice was associated with reduced local internal wave generation. Richardson numbers were rarely supercritical, consistent with weak vertical mixing under all ice concentrations. On decadal timescales, smoother ice may counteract the effects of lower ice concentration on the internal wavefield complicating future predictions of internal wave activity and vertical mixing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".