Radar imaging of intense nonlinear Ekman divergence
Bibliographic record
Abstract
Abstract In general, given an oceanic thermal front, there is a strong positive correlation between sea surface temperature (SST) gradients and surface winds, and the marine atmospheric boundary layer is unstable over the warm side of the oceanic thermal front. The Gulf Stream is a notable example of an oceanic thermal front, and its warm side is often detected as enhanced backscatter in synthetic aperture radar (SAR) images. However, in some “anomalous” SAR images, low backscatter is sometimes observed on the warm side of the front, which seems inconsistent. Therefore, we propose a mechanism to interpret the generation of the low backscatter, based on interactions between ocean surface wind waves and intense nonlinear Ekman divergence. This mechanism is verified by showing that patterns in an observed anomalous SAR image are in good agreement with those in the simulated radar signature. In addition, this methodology and analysis demonstrate that SAR is potentially important for detecting and diagnosing small scale air‐sea interactions and upper ocean dynamics with strong vertical transports induced by submesoscale processes.
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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 | 0.001 |
| 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 | 0.001 |
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".