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 0 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">o</sup> ) and cross-wind (wind direction is 90 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">o</sup> ) 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 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 | 0.000 |
| 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 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".