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Record W2138504084 · doi:10.5194/amt-3-1351-2010

Calibration of the Total Carbon Column Observing Network using aircraft profile data

2010· article· en· W2138504084 on OpenAlexafffund
Debra Wunch, G. C. Toon, P. O. Wennberg, S. C. Wofsy, Britton B. Stephens, M. L. Fischer, Osamu Uchino, James B. Abshire, P. F. Bernath, Sébastien Biraud, Jean-François Blavier, C. D. Boone, Kenneth P. Bowman, E. V. Browell, T. Campos, B. J. Connor, Bruce C. Daube, Nicholas M. Deutscher, Minghui Diao, James W. Elkins, Christoph Gerbig, E. W. Gottlieb, David Griffith, D. F. Hurst, Rodrigo Jiménez, G. Keppel‐Aleks, E. A. Kort, Ronald Macatangay, Toshinobu Machida, Hidekazu Matsueda, F. L. Moore, Isamu Morino, S. Park, John Robinson, Coleen M. Roehl, Y. Sawa, V. Sherlock, Colm Sweeney, T. Tanaka, Mark A. Zondlo

Bibliographic record

VenueAtmospheric measurement techniques · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsUniversity of Waterloo
FundersLawrence Berkeley National LaboratoryBiological and Environmental ResearchCanadian Space AgencyJet Propulsion LaboratoryAustralian Research CouncilNational Oceanic and Atmospheric AdministrationNational Aeronautics and Space AdministrationLangley Research CenterOffice of ScienceCalifornia Institute of TechnologyU.S. Department of EnergyNational Center for Atmospheric ResearchNational Science Foundation
KeywordsCalibrationEnvironmental scienceColumn (typography)Instrumentation (computer programming)Range (aeronautics)Remote sensingMeteorologyAtmospheric sciencesStatisticsComputer scienceGeologyMathematics

Abstract

fetched live from OpenAlex

Abstract. The Total Carbon Column Observing Network (TCCON) produces precise measurements of the column average dry-air mole fractions of CO2, CO, CH4, N2O and H2O at a variety of sites worldwide. These observations rely on spectroscopic parameters that are not known with sufficient accuracy to compute total columns that can be used in combination with in situ measurements. The TCCON must therefore be calibrated to World Meteorological Organization (WMO) in situ trace gas measurement scales. We present a calibration of TCCON data using WMO-scale instrumentation aboard aircraft that measured profiles over four TCCON stations during 2008 and 2009. These calibrations are compared with similar observations made in 2004 and 2006. The results indicate that a single, global calibration factor for each gas accurately captures the TCCON total column data within error.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.059
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.029
GPT teacher head0.225
Teacher spread0.197 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations536
Published2010
Admission routes2
Has abstractyes

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