Internal Solitary Waves with shear: beyond DJL theory
Bibliographic record
Abstract
While background shear is ubiquitous in the natural environment, the vast majority of theoretical and numerical studies of internal solitary waves do not include a background shear. Walter et al 2016, Continental Shelf Research reported on measurements in Monterey Bay in which large amplitude internal solitary wave trains were observed but corresponding waves could not be computed from DJL theory due to the strength of the background shear. In this talk I will revisit this issue using a classical stratified adjustment set up. For the case of an exponential, surface trapped background current I will demonstrate that internal solitary wave trains with and without trapped cores coexist with a substantial region dominated by stratified shear instability and/or Rayleigh Taylor instability. I will then demonstrate the type of internal wave train that results in cases when the the variational formulation of the DJL equation fails to converge. I will speculate on implications for theoretical description of such waves and for more realistic simulations in the coastal ocean.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".