Experimental Confirmation of Stokes Drift Measurement by High-Frequency Radars
Bibliographic record
Abstract
Abstract High-frequency radars (HFR) remotely measure ocean surface currents based on the Doppler shift of electromagnetic waves backscattered by surface gravity waves with one-half of the electromagnetic wavelength, called Bragg waves. Their phase velocity is affected by their interactions with the mean Eulerian currents and with all of the other waves present at the sea surface. Therefore, HFRs should measure a quantity related to the Stokes drift in addition to mean Eulerian currents. However, different expressions have been proposed for this quantity: the filtered surface Stokes drift, one-half of the surface Stokes drift, and the weighted depth-averaged Stokes drift. We evaluate these quantities using directional wave spectra measured by bottom-mounted acoustic wave and current (AWAC) profilers in the lower Saint Lawrence Estuary, Quebec, Canada, deployed in an area covered by four HFRs: two Wellen radars (WERA) and two coastal ocean dynamics applications radars (CODAR). Since HFRs measure the weighted depth-averaged Eulerian currents, we extrapolate the Eulerian currents measured by the AWACs to the sea surface assuming linear Ekman dynamics to perform the weighted depth averaging. During summer 2013, when winds are weak, correlations between the AWAC and HFR currents are stronger (0.93) than during winter 2016/17 (0.42–0.62), when winds are high. After adding the different wave-induced quantities to the Eulerian currents measured by the AWACs, however, correlations during winter 2016/17 significantly increase. Among the different expressions tested, the highest correlations (0.80–0.96) are obtained using one-half of the surface Stokes drift, suggesting that HFRs measure the latter in addition to mean Eulerian currents.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| 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 teacher head, 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".