The Water-Following Performance of Various Lagrangian Surface Drifters Measured in a Dye Release Experiment
Bibliographic record
Abstract
Abstract Many different surface drifter designs have been developed recently to track near-surface ocean currents, but the degree to which these drifters slip through the water because of mechanisms associated with the wind is poorly known. In the 2020 Tracer Release Experiment (TReX), 19 drifters of eight different designs, both commercially available and home-built, were simultaneously released with a patch of rhodamine dye. The dye rapidly spread vertically through the mixed layer but also more slowly dispersed horizontally. Although winds were light, drifters moved downwind from the dye patch at speeds of 3–17 cm s −1 (0.6%–4% of wind speed) depending on the design type. Measurements were made of wind and ocean conditions, and these were incorporated into a boundary layer model at the air–sea interface to estimate complete velocity profiles above and below the surface. Then, a steady-state drag model is used with these profiles to successfully predict drifter slip. Drogued drifters (those with a subsurface drag element) can be affected by Eulerian shear in the upper 0.5 m of the water column, as well as the Stokes drift, but undrogued drifters are in addition greatly affected by direct wind drag, and possibly by resonant interactions with waves. The dye, cycling vertically in the mixed layer, is largely unaffected by all of these factors; therefore, even “perfect” surface drifters do not move with a mixed layer tracer. Significance Statement Surface drifters are used by oceanographers to measure ocean surface currents. However, different designs also slip downwind through the water at rates that are poorly known but are typically around a few percent of the wind speed. In 2020 we simultaneously deployed drifters of eight different designs along with rhodamine dye in a field experiment to see how well the different designs track the water. Here we independently and successfully model drifter slippage for the different designs. Slip factors are then estimated for a range of wind and ocean conditions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 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".