Radar Scattering Features Under High Wind Conditions From Spaceborne Quad-Polarization SAR Observations
Bibliographic record
Abstract
This study examines the impact of wave breaking (WB) and Bragg scattering on the normalized radar cross section (NRCS) to reveal radar scattering features during high wind conditions. This is conducted by decomposing C-band quasi-synchronous wide-swath quad-polarization synthetic aperture radar (SAR) observations acquired from the RADARSAT Constellation Mission (RCM) and RADARSAT-2 (RS-2). The analysis results clearly demonstrate that the polarization difference (PD) associated with Bragg scattering saturates at high wind speeds, while still maintaining azimuthal modulation. Notably, the radar returns from breaking waves at cross-polarization (HV or VH) exhibit higher sensitivity to wind speeds but lower sensitivity to wind direction, compared to co-polarization (HH or VV). Moreover, our analyses show that WB contributes 40%, 80%, and 90% of VV-, HH-, and HV-polarized NRCS, respectively. This study highlights the unique capabilities provided by collocated RCM and RS-2 observations for investigating radar scattering features under high wind conditions. Results of this study can be further used to develop empirical models for estimating co- and cross-polarization radar backscatters induced by WB under high wind speeds.
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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) | 0.000 | 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".