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Record W2791989032 · doi:10.1080/01431161.2018.1433889

Sea surface wind speed and sea state retrievals from dual-frequency altimeter and its preliminary application in global view of wind-sea and swell distributions

2018· article· en· W2791989032 on OpenAlexaff
Shuiqing Li, Hui Shen, Yijun Hou, Yijun He, Bi Fan

Bibliographic record

VenueInternational Journal of Remote Sensing · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOcean Waves and Remote Sensing
Canadian institutionsBedford Institute of Oceanography
FundersNational Natural Science Foundation of ChinaNational Science Foundation
KeywordsSwellAltimeterSignificant wave heightBuoySea stateRadar altimeterWind speedWind waveRemote sensingWave heightGeologySea-surface heightWind wave modelMeteorologyEnvironmental scienceGeodesyGeographyOceanography

Abstract

fetched live from OpenAlex

Altimeter radar backscatter intensity, in terms of the normalized radar cross section (NRCS), is known to be modulated by surface wind forcing and the state of wind-sea development. Based on a data set of collocated altimeters (including Topex/Poseidon, Jason-1 and Jason-2) and in situ measurements, different responses to various wind speeds and wave ages (i.e. the state of wind-sea development) were illustrated for altimeter dual-frequency NRCSs (Ku-band at 13.6 Hz and C band at 5.4 Hz), which can facilitate the retrieval of wind speed and wave age parameters. A statistical parametric algorithm was developed to retrieve the two dynamic parameters from the altimeter dual-frequency NRCSs using the neutral network method. The wind-sea significant wave height (SWH) was estimated from wind speed and wave age parameters, which partitions the swell SWH from the altimeter SWH measurement. All newly derived parameters were well validated by comparison against in situ buoy measurements. A preliminary application of the method in examining the swell or wind-sea contributions to global waves was performed; it was found the swell dominance in an open ocean, and the wind-sea dominance in marginal and semi-enclosed seas. The methods would benefit other applications such as studies of air–sea interactions, validation of wave model, determination of swell decay rate and studies of wave climate.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.776
Threshold uncertainty score0.493

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)0.0000.000

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 head0.013
GPT teacher head0.254
Teacher spread0.241 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations9
Published2018
Admission routes1
Has abstractyes

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