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Record W2116451052 · doi:10.1109/igarss.2000.857253

Wind field retrieval using satellite based synthetic aperture radars

2002· article· en· W2116451052 on OpenAlexaboutno aff
Jochen Horstmann, Wolfgang Koch, Susanne Lehner

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOcean Waves and Remote Sensing
Canadian institutionsnot available
Fundersnot available
KeywordsRemote sensingSynthetic aperture radarScatterometerSatelliteSpace-based radarMesoscale meteorologyC bandRadarMeteorologyEnvironmental scienceImage resolutionWind speedSide looking airborne radarRadar imagingGeologyComputer scienceRadar engineering detailsGeographyAerospace engineering

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.938
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.000

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 head0.022
GPT teacher head0.199
Teacher spread0.176 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2002
Admission routes1
Has abstractyes

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