Internal wave transmission through a density staircase: Interfacial waves excitation
Bibliographic record
Abstract
<!--!introduction!--> Thermohaline staircases (TS) are a prominent feature in the Arctic Ocean basins at mid-depths, where they overlie the warm Atlantic water mass. Internal waves (IW) able to propagate through TS might be more likely to break, enhancing vertical heat fluxes that could bring warm water to the surface. However, only large horizontal waves are likely to propagate since TS act as a filter for IWs. As wind-driven IW activity is expected to increase with the decrease of sea ice cover, it is essential to understand how TS affect IW propagation. We carried out numerical simulations to study IW transmission through a density staircase. The code used solves the two-dimensional nonlinear incompressible Boussinesq Navier-Stokes equation, evolving in time vorticity and buoyancy. The model initiates with a small amplitude vertical wave packet. We performed several simulations with varied relative wavenumbers and varying the step thickness and the step number of the ST. We discovered a novel transmission mechanism in which an incoming IW excites interfacial waves (ITW) within the TS that slowly leak energy above and below the TS. ITWs have a vertical baroclinic structure and travel along the TS. IW transmission theory predicts perfect wave transmission peaks only for IWs and ITWs in resonance. Instead, we found a smooth transition between perfect reflection to perfect transmission. Although we used IWs with short wavelengths in our simulations, long horizontal IWs might also generate ITWs within the TS after the transmission process.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".