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Record W2176028944 · doi:10.1175/jtech1880.1

Satellite Measurement of Stratospheric Winds and Ozone Using Doppler Michelson Interferometry. Part I: Instrument Model and Measurement Simulation

2006· article· en· W2176028944 on OpenAlexaffabout
Peyman Rahnama, Yves Rochon, I. C. McDade, G. G. Shepherd, William A. Gault, Alan Scott

Bibliographic record

VenueJournal of Atmospheric and Oceanic Technology · 2006
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsCOM DEV InternationalEnvironment and Climate Change CanadaYork University
FundersNational Aeronautics and Space Administration
KeywordsMichelson interferometerRemote sensingRadianceDoppler effectEnvironmental scienceSatelliteInterferometryAtmospheric soundingMeteorologyPhysicsOpticsGeology

Abstract

fetched live from OpenAlex

Abstract This paper presents an instrument model and observation simulations for the measurement of stratospheric winds and ozone concentration using a satellite instrument employing imaging and the Doppler Michelson interferometery technique. The measurement technique and instrument concept are described. The instrument model and simulations are based on initial design characteristics of the Canadian Stratospheric Wind Interferometer for Transport Studies (SWIFT) satellite instrument. SWIFT employs an imaging array and a field-widened Michelson interferometer. It will measure stratospheric winds and ozone densities using the wind-induced phase shifts of interferograms from atmospheric limb radiance spectra in the vicinity of the vibration–rotation ozone line at 1133.4335 cm−1. The measurement simulation and analysis tools have been developed to assess the SWIFT instrument performance and to evaluate the impact of instrument and measurement characteristics on expected wind and ozone errors. Sample results of the measurement simulation and the related line-of-sight wind error noise levels are presented.

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)0.001
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 score0.508
Threshold uncertainty score0.716

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 integrity0.0000.000
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 head0.027
GPT teacher head0.219
Teacher spread0.192 · 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

Citations28
Published2006
Admission routes2
Has abstractyes

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