Carbon dioxide atmospheric vertical profiles retrieved from space observation using ACE-FTS solar occultation instrument
Bibliographic record
Abstract
Abstract. Major limitations of our present knowledge of the global distribution of CO2 in the atmosphere are the uncertainty in atmospheric transport and the sparseness of in situ concentration measurements. Limb viewing spaceborne sounders such as the Atmospheric Chemistry Experiment Fourier transform spectrometer (ACE-FTS) offer a vertical resolution of a few kilometres for profiles, which is much better than currently flying or planned nadir sounding instruments can achieve. After having demonstrated the feasibility of obtaining CO2 vertical profiles in the 5–25 km altitude range with an accuracy of about 2 ppm in a previous study, we present here the results of five years of ACE-FTS observations in terms of monthly mean profiles of CO2 averaged over 10° latitude bands for northern mid-latitudes. These results are compared with in-situ aircraft measurements and with simulations from two different air transport models. Key features of the measured altitude distribution of CO2 are shown to be accurately reproduced by the ACE-FTS retrievals: variation in altitude of the seasonal cycle amplitude and extrema, seasonal change of the vertical gradient, and mean growth rate. We show that small but significant differences from model simulations could result from an over estimation of the model circulation strength during the northern hemisphere spring. Coupled with column measurements from a nadir viewing instrument, it is expected that occultation measurements will bring useful constraints to the surface carbon flux determination.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".