Effects of Kuroshio intrusions on nonlinear internal waves in the South China Sea during winter
Bibliographic record
Abstract
During winter the Kuroshio tends to cross Luzon Strait, penetrating the northeastern South China Sea where it forms energetic mesoscale structures. Luzon Strait is also a site where westward‐propagating large‐amplitude internal waves are generated. We describe observations of these waves acquired in the deep basin of the South China Sea during the winter of 2010−2011, with the goal of assessing the influence of mesoscale variability on their properties. Combining tidal current simulations with an internal wave generation and evolution model, we obtain time series of deviations between our observations and the model simulations. These deviations are analyzed in terms of mesoscale variability based on the data‐assimilated HYbrid Coordinate Ocean Model (HYCOM) simulations. We find that simplified models of nonlinear internal wave response to changes in horizontal stratification gradients and vertical shear provide at best weak simulations of amplitude modulation. In contrast to these results, deviations of internal wave arrival time, occurring up to 2 h early during Kuroshio inflows, are quite well simulated when derived from integration of the first internal mode phase speed along two‐dimensional ray‐traced paths using HYCOM simulations of velocity and density fields together with bathymetry. Refraction of the internal waves by Kuroshio intrusions can lead to substantial distortion of the paths, sufficient to provide a potential explanation for the apparent suppression of waves during previous winter measurements. Our results suggest that the internal wave field can be a sensitive indicator of mesoscale variability in Luzon Strait and the northeastern South China Sea.
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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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 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".