Wind field retrieval using satellite based synthetic aperture radars
Bibliographic record
Abstract
The high spatial resolution and large coverage of satellite-based synthetic aperture radars (SAR) offer an unique opportunity to derive mesoscale wind fields over the ocean surface especially in coastal areas. For this purpose an algorithm was developed and tested using the C-band SAR images from the European remote sensing satellite ERS-2 and from the Canadian satellite RADARSAT-1. Wind speeds are derived from the normalized radar cross sections (NRCS) using a semi empirical model. The model was originally developed for a C-band scatterometer with vertical polarization and therefore has to be modified for horizontal polarization of the RADARSAT-1 SAR. Several C-band polarization ratios were considered including theoretical and empirical forms. To improve and verify the algorithm, wind speeds were computed from several RADARSAT-1 ScanSAR images and compared to results of the Danish high resolution limited area model (HIRLAM). Furthermore the main error sources in SAR wind field extraction are studied with respect to both polarizations.
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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) | 0.008 | 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".