Age of air from ACE-FTS measurements of sulfur hexafluoride
Bibliographic record
Abstract
Climate models predict that the Brewer–Dobson circulation (BDC) will accelerate due to tropospheric warming, leading to a redistribution of trace gases and, consequently, to a change of the radiative properties of the atmosphere. Changes in the BDC are diagnosed by the so-called “age of air”, that is, the time since air in the stratosphere exited the troposphere. These changes can be derived from a long-term observation-based record of long-lived trace gases with increasing concentration in the troposphere, such as sulfur hexafluoride (SF 6 ). The Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) provides the longest available continuous time series of vertically resolved SF 6 measurements, spanning 2004 to the present. In this study, a new age-of-air product is derived from the ACE-FTS SF 6 dataset. The ACE-FTS product is in good agreement with other observation-based age-of-air datasets and shows the expected global distribution of age-of-air values. Age of air from a chemistry–climate model is evaluated, and the linear trend of the observation-based age of air is calculated in 12 regions within the lower stratospheric midlatitudes (14–20 km, 40–70°) in each hemisphere. In 8 of 12 regions, there was not a statistically significant trend. The trends in the other regions, specifically 50–60 and 60–70° S at 17–20 km and 40–50° N at 14–17 and 17–20 km, are negative and significant to 2 standard deviations. This is therefore the first observation-based age-of-air trend study to suggest an acceleration of the shallow branch of the BDC, which transports air poleward in the lower stratosphere, in regions within both hemispheres.
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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 | 0.001 | 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".