Formation and Evolution of Turbulence in Convectively Unstable Internal Solitary Waves of Depression Shoaling over Gentle Slopes in the South China Sea
Bibliographic record
Abstract
Abstract The shoaling of high-amplitude internal solitary waves (ISWs) of depression in the South China Sea (SCS) is examined through large-scale parallel turbulence-resolving high-accuracy/resolution simulations. A select, near-isobath-normal, bathymetric transect of the gentle SCS continental slope is employed together with stratification and current profiles obtained by in situ measurements. Three simulations of separate ISWs with initial deep-water amplitudes in the range [136, 150 m] leverage a novel wave-tracking capability for a propagation distance of 80 km and accurately reproduce key features of in situ–observed phenomena with significantly higher spatiotemporal resolution. The interplay between convective and shear instability and the associated turbulence formation and evolution as a function of deep-water ISW amplitude are further studied in part revealing processes previously not observed in the field. Across all three waves, the convective instability develops in a similar fashion. Heavier water entrained from the wave rear plunges into its interior, giving rise to transient, yet distinct, subsurface vortical structures. Ultimately, a gravity current is triggered which horizontally advances through the wave interior and mixes it down to pycnocline’s base. Although the waveform remains distinctly symmetric, Kelvin–Helmholtz billows emerge near the well-mixed ISW trough, disturb the wave’s trailing edge, and give rise to an active wake. The evolution of the kinetic energy associated with fine-scale perturbations to the ISW-induced velocity field shows two different growth regimes, each dominated by either convective or shear instability. The wake’s perturbation kinetic energy is nonlinearly dependent on deep-water wave amplitude and can become a sizable fraction of the kinetic energy of the deep-water ISW.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".