First multi-year occultation observations of CO<sub>2</sub> in the MLT by ACE satellite: observations and analysis using the extended CMAM
Bibliographic record
Abstract
This paper presents the first global set of observations of CO2 in the mesosphere and lower thermosphere (MLT) obtained by the ACE-FTS instrument on SCISAT-I, a small Canadian satellite launched in 2003. The observations use the solar occultation technique and document the fall-off in the mixing ratio of CO2 in the MLT region. The beginning of the fall-off of the CO2, or "knee" occurs at about 78 km and lies higher than in the CRISTA-1 measurements (~70 km) but lower than in the SABER 1.06 (~80 km) and much lower than in rocket measurements. We also present the measurements of CO obtained concurrently which provide important constraints for analysis. We have compared the ACE measurements with simulations of the CO2 and CO distributions in the vertically extended version of the Canadian Middle Atmosphere Model (CMAM). Applying standard chemistry we find that we cannot get agreement between the model and ACE CO2 observations although the CO observations are adequately reproduced. There appears to be about a 10 km offset compared to the observed ACE CO2, with the model "knee" occurring too high. In analyzing the disagreement, we have investigated the variation of several parameters of interest (photolysis rates, formation rate for CO2, and the impact of uncertainty in turbulent eddy diffusion) in order to explore parameter space for this problem. Our conclusions are that there must be a loss process for CO2, about 2–4~times faster than photolysis that will sequester the carbon in some form other than CO and we have speculated on the role of meteoritic dust as a possible candidate. In addition, from this study we have highlighted a possible important role for unresolved vertical eddy diffusion in 3-D models in determining the distribution of candidate species in the mesosphere which requires further study.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".