Seasonal Variability and Generation Mechanisms of Nonlinear Internal Waves in the Strait of Georgia
Bibliographic record
Abstract
Abstract Seasonal variability and generation mechanisms of large nonlinear internal waves are reported, based on an analysis of 9 years of continuous observational data collected at nodes of the Ocean Networks Canada coastal observatory in the Strait of Georgia, Canada. About one thousand large nonlinear internal wave packets were identified. The timing of these packets suggests a very strong correlation with daily tides and fortnightly cycles. More waves are seen during the stronger tides of the fortnightly cycle but overall waves are seen in less than 40% of all days. Other wave characteristics show seasonal variations. In winter, when the pycnocline is weaker, both the spatial and temporal scales of internal waves are several times larger than summertime waves and wave amplitudes can approach 30 m. These waves are large enough vertically but small enough horizontally that standard acoustic Doppler current profiler (ADCP) processing algorithms present a strongly distorted view of wave shape and features. A specialized reprocessing of the beam velocities is used to correctly measure the wave velocity field and to determine wave propagation speed and direction. In addition to the previously known northward‐propagating waves in the Strait, we also found waves propagating in other directions and a noticeable correlation with winds, which may be a proxy for spatial variations in density and/or velocity shear. By considering wave propagation direction, relationship with tidal phase, and relationship with wind, three generation mechanisms were found. Two particularly interesting generation mechanisms involve waves radiating from the Sand Heads area.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".