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Record W2170531874 · doi:10.5194/acp-5-563-2005

Increased Northern Hemispheric carbon monoxide burden in the troposphere in 2002 and 2003 detected from the ground and from space

2005· article· en· W2170531874 on OpenAlexaff
L. N. Yurganov, P. Duchatelet, A. V. Dzhola, D. P. Edwards, F. Hase, I. Krämer, Emmanuel Mahieu, J. Mellqvist, Justus Notholt, P. C. Novelli, A. Rockmann, H. E. Scheel, M. Schneider, Astrid Schulz, A. Strandberg, Ralf Sussmann, Hiroshi Tanimoto, Voltaire A. Velazco, J. R. Drummond, J. C. Gille

Bibliographic record

VenueAtmospheric chemistry and physics · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsUniversity of Toronto
FundersRussian Foundation for Basic ResearchBundesministerium für Bildung und ForschungEuropean Space Agency
KeywordsTroposphereNorthern HemisphereAtmospheric sciencesBorealCarbon monoxideAtmosphere (unit)Environmental scienceMixing ratioRadiometerClimatologyTaigaSatelliteSouthern HemisphereMeteorologyRemote sensingChemistryPhysicsGeologyGeographyAstronomy

Abstract

fetched live from OpenAlex

Abstract. Carbon monoxide total column amounts in the atmosphere have been measured in the High Northern Hemisphere (30°-90° N, HNH) between January 2002 and December 2003 using infrared spectrometers of high and moderate resolution and the Sun as a light source. They were compared to ground-level CO mixing ratios and to total column amounts measured from space by the Terra/MOPITT instrument. All these data reveal increased CO abundances in 2002-2003 in comparison to the unperturbed 2000-2001 period. Maximum anomalies were observed in September 2002 and August 2003. Using a simple two-box model, the corresponding annual CO emission anomalies (referenced to 2000-2001 period) have been found equal to 95Tg in 2002 and 130Tg in 2003, thus close to those for 1996 and 1998. A good correlation with hot spots detected by a satellite radiometer allows one to assume strong boreal forest fires, occurred mainly in Russia, as a source of the increased CO burdens.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.221
Threshold uncertainty score0.967

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 head0.003
GPT teacher head0.165
Teacher spread0.162 · 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

Citations160
Published2005
Admission routes1
Has abstractyes

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