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Record W2131980837 · doi:10.5194/amt-5-2993-2012

Assessment of the quality of OSIRIS mesospheric temperatures using satellite and ground-based measurements

2012· article· en· W2131980837 on OpenAlexafffundabout
Patrick E. Sheese, Kimberly Strong, E. J. Llewellyn, R. L. Gattinger, J. M. Russell, C. D. Boone, Mark E. Hervig, R. J. Sica, Justin Bandoro

Bibliographic record

VenueAtmospheric measurement techniques · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsWestern UniversityUniversity of SaskatchewanUniversity of WaterlooUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Space AgencyTekesEuropean Space Agency
KeywordsOsirisSatelliteMesosphereStratopauseMesopauseEnvironmental scienceRayleigh scatteringAltitude (triangle)Atmospheric sciencesSpectrographStratosphereRemote sensingPhysicsGeologyOpticsAstronomy

Abstract

fetched live from OpenAlex

Abstract. The Optical Spectrograph and InfraRed Imaging System (OSIRIS) on the Odin satellite is currently in its 12th year of observing the Earth's limb. For the first time, continuous temperature profiles extending from the stratopause to the upper mesosphere have been derived from OSIRIS measurements of Rayleigh-scattered sunlight. Through most of the mesosphere, OSIRIS temperatures are in good agreement with coincident temperature profiles derived from other satellite and ground-based measurements. In the altitude region of 55–80 km, OSIRIS temperatures are typically within 4–5 K of those from the SABER, ACE-FTS, and SOFIE instruments on the TIMED, SciSat-I, and AIM satellites, respectively. The mean differences between individual OSIRIS profiles and those of the other satellite instruments are typically within the combined uncertainties and previously reported biases. OSIRIS temperatures are typically within 2 K of those from the University of Western Ontario's Purple Crow Lidar in the altitude region of 52–79 km, where the mean differences are within combined uncertainties. Near 84 km, OSIRIS temperatures exhibit a cold bias of 10–15 K, which is due to a cold bias in OSIRIS O2 A-band temperatures at 85 km, the upper boundary of the Rayleigh-scatter derived temperatures; and near 48 km OSIRIS temperatures exhibit a cold bias of 5–15 K, which is likely due to multiple-scatter effects that are not taken into account in the retrieval.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.050
GPT teacher head0.310
Teacher spread0.260 · 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 source (direct Gemma or distilled Codex), 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

Citations21
Published2012
Admission routes3
Has abstractyes

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