Measured changes in ocean surface roughness due to atmospheric boundary layer rolls
Bibliographic record
Abstract
A research aircraft was recently flown over the Mid‐Atlantic Bight during a mild cold air outbreak to sample the planetary boundary layer at low levels of 15–20 m above the sea surface. Aircraft sensors measured near‐surface atmospheric turbulence and, at the same time, variations in sea surface roughness using laser and radar. The aircraft turbulence observations indicate a coherent secondary flow consistent with boundary layer roll vortices of crosswind scale 1.5–2.0 km. Modulation in measured laser and radar‐inferred sea surface slope variance occurs at similar scales. Remarkable correlation is found between the radar backscatter and near‐surface wind speed data, showing that the short wave slope variance is responsive to these large eddies. Associated small but periodic changes in wind direction do not appear to impact the short wave slope signature. Differentiation between short‐ and intermediate‐scale wave roughness using aircraft laser and radar data leads us to conclude that observed fluctuations in intermediate‐scale wave slope were not directly linked to the local wind. A synthetic aperture radar (SAR) image was acquired by the Canadian Space Agency's RADARSAT coincident with the aircraft measurements. Widespread streaking in the SAR image suggests the surface impacts of atmospheric longitudinal rolls. Our aircraft results indicate that the dominant term dictating SAR backscatter modulations at the eddy scale of 1–2 km is the fluctuation of the along‐wind velocity, nominally associated with regions of near‐surface convergence or divergence. Wind speed fluctuations of 7–10% estimated from the SAR and aircraft radar are consistent with the aircraft's measured variations in near‐surface wind speed.
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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) | 0.000 | 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) | 0.001 | 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".