Ethane, ethyne and carbon monoxide concentrations in the upper troposphere and lower stratosphere from ACE and GEOS-Chem: a comparison study
Bibliographic record
Abstract
Abstract. Near global upper tropospheric concentrations of carbon monoxide (CO), ethane (C2H6) and ethyne (C2H2) from ACE (Atmospheric Chemistry Experiment) Fourier transform spectrometer on board the Canadian satellite SCISAT-1 are presented and compared with the output from the Chemical Transport Model (CTM) GEOS-Chem. The retrievals of ethane and ethyne from ACE have been improved for this paper by using new sets of microwindows compared with those for previous versions of ACE data. With the improved ethyne retrieval we have been able to produce a near global upper tropospheric distribution of C2H2 from space. Carbon monoxide, ethane and ethyne concentrations retrieved using ACE spectra show the expected seasonality linked to variations in the anthropogenic emissions and destruction rates as well as seasonal biomass burning activity. The GEOS-Chem model was run using the dicarbonyl chemistry suite, an extended chemical mechanism in which ethyne is treated explicitly. Seasonal cycles observed from satellite data are well reproduced by the model output, however the simulated CO concentrations are found to be systematically biased low over the Northern Hemisphere. An average negative global mean bias of 12% and 7% of the model relative to the satellite observations has been found for CO and C2H6 respectively and a positive global mean bias of 1% has been found for C2H2. ACE data are compared for validation purposes with MkIV spectrometer data and Global Tropospheric Experiment (GTE) TRACE-A campaign data showing good agreement with all of them.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".