Tide, Wind, and River Forcing of the Surface Currents in the Fraser River Plume
Bibliographic record
Abstract
A long-term record of surface currents from a high-frequency radar system, along with near-surface hydrographic transects, moored current meter records, and satellite imagery, are analyzed to determine the relative importance of river discharge, wind, and tides in driving the surface flow in the Fraser River plume. The observations show a great deal of oceanographic and instrumental variability. However, averaged quantities yielded robust results. The effect of river flow, which determines buoyancy and inertia near the river mouth, was found by taking a long-term average. The resulting flow field was dominated by a jet with two asymmetric gyres; the anticyclonic gyre to the north had flow speeds consistent with geostrophy. The mean flow speed near the river mouth was 14.3 cm s–1, while the flow further afield was 5 cm s–1 or less. Wind stress and surface currents were highly coherent in the subtidal frequency band. Northwesterly winds drive a surface flow to the southeast at speeds of nearly 30 cm s–1. Southeasterly winds drive a surface flow to the northwest at speeds reaching 20 cm s–1; however, there is more spatial variability in speed and direction relative to the northwesterly wind case. A harmonic analysis was used to extract the tidally driven flows. Ellipse parameters for the major tidal constituents varied considerably in both alignment and aspect ratio over the radar domain, in direct contrast to a barotropic model which predicted rectilinear flow along the Strait of Georgia. This is a result of water filling and draining the shallow mud flats north of the Fraser's main channel. The M2 velocities at the surface were also weaker than their barotropic counterparts. However, the shallow water constituent MK3 was enhanced at the surface and nearly as strong as the mean flow, implying that non-linear interactions are important to surface dynamics.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".