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Record W2243800325

Carbonyl fluoride (COF2) vertical information above Jungfraujoch by FTIR and multi-spectra fitting: error budget and comparisons with KASIMA 3-D CTM model calculations

2008· article· en· W2243800325 on OpenAlexaboutno aff
Pierre Duchatelet, Emmanuel Mahieu, Roland Ruhnke, Philippe Demoulin, P. F. Bernath, C. D. Boone, Kaley A. Walker, S. Wood

Bibliographic record

VenueORBi (University of Liège) · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsFluorideSpectral lineFourier transform infrared spectroscopyChemistryPhysicsInorganic chemistryOpticsQuantum mechanics
DOInot available

Abstract

fetched live from OpenAlex

The major sources of fluorine in the stratosphere are CFC-11 and CFC-12. During the decomposition process, fluorine is first present in the form of carbonyl compounds (e.g. carbonyl fluoride (COF2)). Given its long life time, COF2 is the second most abundant stratospheric fluorine reservoir. Earliest, COF2 vertical distributions were derived from occultation measurements performed by the ATMOS instrument during the SPACELAB-3 Space Shuttle mission in 1985. The Canadian FTIR spectrometer ACE-FTS, onboard the SCISAT-1 satellite, is the first instrument since the last ATMOS flight in 1994, to record COF2 vertical profiles from space. Four years of ACE-FTS occultation measurements are presently available. Several COF2 IR absorption lines located either in the so-called InSb (1-5 µm) and MCT (2-16 µm) spectral ranges can be used to determine its total column from ground-based high-resolution FTIR observations. In addition, we have proposed, during the EGU General Assembly 2007, an original retrieval procedure that allows us to derive information on the COF2 vertical distribution, between 17 and 30 km, from ground-based FTIR spectra recorded at Jungfraujoch. This “multi-microwindows multi-spectra” approach, using the SFIT-2 v3.91 algorithm, has been completely characterized in terms of fitting strategy and information content. Some examples of COF2 vertical profiles inversions were also presented. This year, we will complete the characterization of the multi-microwindows multi-spectra fitting procedure by exposing the full error budget affecting our COF2 partial and total columns products. Also, comparisons with COF2 model runs generated by the 3D CTM KASIMA (KArlsruhe SImulation model of the Middle Atmosphere) will be presented and critically discussed.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.202

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.010
GPT teacher head0.183
Teacher spread0.173 · 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 designSimulation or modeling
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

Citations0
Published2008
Admission routes1
Has abstractyes

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