On Modeling of Quad‐Polarization Radar Scattering From the Ocean Surface With Breaking Waves
Bibliographic record
Abstract
Abstract Accurate estimates of microwave radar returns based on theoretical electromagnetic scattering models are of great benefit to obtain insight into the microwave scattering mechanism at the ocean surface. In this study, quad‐polarized radar backscatters from the regular ocean surface (no breaking waves) are first simulated using a composite surface Bragg model and a second‐order small slope approximation model, using three different surface roughness spectral models. The copolarized and cross‐polarized radar backscatters, induced by breaking waves, are then quantitatively estimated using two recent empirical models, which are dependent on incidence angles, wind speeds, and wind directions. Model‐simulated total radar backscatters, from regular surface waves and breaking waves, are statistically compared with measurements from spaceborne C‐band quad‐polarization RADARSAT‐2 synthetic aperture radar and also calculations from copolarized and cross‐polarized geophysical model functions. Results show that simulations of quad‐polarization radar backscatter are significantly improved when the effects of breaking waves are incorporated, especially for HH and VH polarizations.
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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 | 0.001 | 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".