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Record W2123341477 · doi:10.5194/acp-7-4107-2007

Satellite measurements of the global mesospheric sodium layer

2007· article· en· W2123341477 on OpenAlexaff
Zhongyu Fan, J. M. C. Plane, J. Gumbel, J. Stegman, E. J. Llewellyn

Bibliographic record

VenueAtmospheric chemistry and physics · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsAtmospheric sciencesThermosphereLatitudeRadianceEnvironmental scienceMesosphereSeasonalityDiurnal temperature variationMorningSatelliteMiddle latitudesIonosphereGeologyStratosphereRemote sensingPhysicsGeodesy

Abstract

fetched live from OpenAlex

Abstract. Optimal estimation theory is used to retrieve the absolute Na density profiles in the mesosphere/lower thermosphere from limb-scanning measurements of the Na radiance at 589 nm in the dayglow. Two years of observations (2003 and 2004), recorded by the OSIRIS spectrometer on the Odin satellite, have been analysed to yield the seasonal and latitudinal variation of the Na layer column abundance, peak height, and peak width. The layer shows little seasonal variation at low latitudes, but the winter/summer ratio increases from a factor of ~3 at mid-latitudes to ~10 in the polar regions. Comparison of the measurements made at about 06:00 and 18:00 LT shows little diurnal variation in the layer, apart from the equatorial region where, during the equinoxes, there is a two-fold increase in Na density below 94 km between morning and evening. This is most likely caused by the strong downward wind produced by the diurnal tide between ~02:00 and 10:00 LT. The dramatic removal of Na below 85 km at latitudes above 50° during summer is explained by the uptake of sodium species on the ice surfaces of polar mesospheric clouds, which were simultaneously observed by the Odin satellite.

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 score0.554
Threshold uncertainty score0.833

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)0.0010.000

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 head0.009
GPT teacher head0.224
Teacher spread0.215 · 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

Citations56
Published2007
Admission routes1
Has abstractyes

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