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Record W2163532696 · doi:10.1029/2009jd012488

Odin/OSIRIS observations of stratospheric BrO: Retrieval methodology, climatology, and inferred Br<sub><i>y</i></sub>

2010· article· en· W2163532696 on OpenAlexaff
C. A. McLinden, C. S. Haley, N. D. Lloyd, F. Hendrick, Alexei Rozanov, Björn‐Martin Sinnhuber, F. Goutail, D. A. Degenstein, E. J. Llewellyn, Christopher E. Sioris, Michel Van Roozendaël, Jean‐Pierre Pommereau, W. Lotz, John P. Burrows

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsUniversity of SaskatchewanYork UniversityEnvironment and Climate Change Canada
FundersTekesCentre National d’Etudes SpatialesEuropean Space Agency
KeywordsStratosphereRadianceOsirisSatelliteSpectrographOccultationEnvironmental scienceAtmospheric sciencesRemote sensingMeteorologyPhysicsSpectral lineGeologyAstronomy

Abstract

fetched live from OpenAlex

A 7+ year (2001–2008) data set of stratospheric BrO profiles measured by the Optical Spectrograph and Infra‐Red Imager System (OSIRIS) instrument, a UV‐visible spectrometer measuring limb‐scattered sunlight from the Odin satellite, is presented. Zonal mean radiance spectra are computed for each day and inverted to yield effective daily zonal mean BrO profiles from 16 to 36 km. A detailed description of the retrieval methodology and error analysis is presented. Single‐profile precision and effective resolution are found to be about 30% and 3–5 km, respectively, throughout much of the retrieval range. Individual profile and monthly mean comparisons with ground‐based, balloon, and satellite instruments are found to agree to about 30%. A BrO climatology is presented, and its morphology and correlation with NO 2 is consistent with our current understanding of bromine chemistry. Monthly mean Br y maps are derived. Two methods of calculating total Br y in the stratosphere are used and suggest (21.0 ± 5.0) pptv with a contribution from very short lived substances of (5.0 ± 5.0) pptv, consistent with other recent estimates.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.371
Threshold uncertainty score0.730

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
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 head0.090
GPT teacher head0.339
Teacher spread0.249 · 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

Citations59
Published2010
Admission routes1
Has abstractyes

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