Improved Internal Wave Spectral Continuum in a Regional Ocean Model
Bibliographic record
Abstract
Abstract Recent work demonstrates that high‐resolution global models forced simultaneously by atmospheric fields and the astronomical tidal potential contain a partial internal (gravity) wave (IW) spectral continuum. Regional simulations of the MITgcm forced at the horizontal boundaries by a global run that carries a partial IW continuum spectrum are performed at the same grid spacing as the global run and at finer grid spacings in an attempt to fill out more of the IW spectral continuum. Decreasing only the horizontal grid spacing from 2 to 0.25 km greatly improves the frequency spectra and slightly improves the vertical wavenumber spectra of the horizontal velocity. Decreasing only the vertical grid spacing by a factor of 3 does not yield any significant improvements. Decreasing both horizontal and vertical grid spacings yields the greatest degree of improvement, filling the frequency spectrum out to 72 cpd. Our results suggest that improved IW spectra in regional models are possible if they are run at finer grid spacings and are forced at their lateral boundaries by remotely generated IWs. Additionally, consistency relations demonstrate that improvements in the spectra are indeed due to the existence of IWs at higher frequencies and vertical wavenumbers when remote IW forcing is included and model grid spacings decrease. By being able to simulate an IW spectral continuum to 0.25 km scales, these simulations demonstrate that one may be able to track the energy pathways of IWs from generation to dissipation and improve the understanding of processes such as IW‐driven mixing.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".