C-band Compact-Polarimetric SAR Monitoring of Ocean Winds
Bibliographic record
Abstract
To investigate the capability of ocean wind monitoring by the C-band compact-polarimetry (CP) Synthetic Aperture Radar (SAR), we develop a theoretical model based on the fundamental mechanisms of interactions between sea surface wind-waves and radar microwave. We simulate the dependencies of the NRCSs (normalized radar cross-sections) on wind speeds and incidence angles, for up-wind (wind direction is 0o) and cross-wind (wind direction is 90o) conditions. Analysis of the model results lead to two ocean wind retrieval methods for RV-polarization and RH-polarization (pol) SAR (Synthetic Aperture Radar) data, respectively. The RV-polarized method is proposed based on the CMOD framework and a sensitivity analysis, while the RH-polarized method and model are based on application of a quadratic function. Both the theoretical model and wind retrieval methods suggest that the RV-pol should be more suitable for ocean wind especially hurricane monitoring than the RH-pol method. The database used in this study includes wind vectors observed by in situ buoys of the National Data Buoy Center (NDBC) and simulated C-band CP radar signals, created by a simulator based on imputing C-band RADARSAT-2 SAR images.
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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".