An Algorithm for Wind Direction Retrieval From X-Band Marine Radar Images
Bibliographic record
Abstract
A new method for retrieving wind direction from X-band marine radar images is presented in this letter. The new algorithm investigates radar backscatter in the wavenumber domain and obtains wind direction from the wavenumber spectrum. Different from previous algorithms that detect rain-contaminated images and discard them, the new algorithm could be applied to both rain-contaminated and rain-free images. For rain-contaminated images collected under low wind speeds (i.e., less than 8 m/s), wind directions were retrieved based on spectral components with wavenumbers of [0.01, 0.2]. For rain-contaminated images obtained under high wind speeds and rain-free images, wind directions were retrieved from the spectrum with values at zero wavenumber. The algorithm has been tested using X-band radar images and shipborne anemometer data collected on the east coast of Canada. Comparison with the anemometer data shows that the root-mean-square error of wind directions retrieved from rain-contaminated images collected under low wind speeds is reduced by 25.1°.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".