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Record W1968621060 · doi:10.1029/2009jc005995

Comparison of composite Bragg theory and quad‐polarization radar backscatter from RADARSAT‐2: With applications to wave breaking and high wind retrieval

2010· article· en· W1968621060 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOcean Waves and Remote Sensing
Canadian institutionsBedford Institute of OceanographyFisheries and Oceans Canada
Fundersnot available
KeywordsRadarBackscatter (email)Wind speedRemote sensingMeteorologySatellitePolarization (electrochemistry)Environmental sciencePhysicsGeologyAerospace engineeringComputer scienceEngineering

Abstract

fetched live from OpenAlex

Depolarized (de‐pol) radar backscatter is now produced by many spaceborne satellites. Analysis of RADARSAT‐2 (R2) quad‐polarization (quad‐pol) data with collocated in situ ocean wind measurements reveals that the de‐pol radar backscatter does not saturate in high winds. This is a significant development for radar wind sensing, because wind retrieval with copolarized (co‐pol) backscatter suffers from problems of incidence‐and‐azimuth‐angle‐dependent signal saturation and dampening in high winds. We present a study comparing satellite quad‐pol measurements with the composite surface Bragg (CB) theory of radar backscattering from the ocean surface. The co‐pol data are in good agreement with the CB theory. De‐pol data are more sensitive to wind speed compared to theoretical prediction, thus retrieval of high winds is more accurate using the de‐pol return. The cubic wind speed dependence of de‐pol returns in high winds reflects the significant breaking wave contributions. The relationship can be used to obtain wave‐breaking properties from space.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.585
Threshold uncertainty score0.351

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.296
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it