Satellite observations of stratospheric hydrogen fluoride andcomparisons with SLIMCAT calculations
Bibliographic record
Abstract
Abstract. The vast majority of emissions of fluorine-containing molecules are anthropogenic in nature, e.g. chlorofluorocarbons (CFCs), hydrochlorofluorocarbons (HCFCs), and hydrofluorocarbons (HFCs). Many of these fluorine-containing species deplete stratospheric ozone and are regulated by the Montreal Protocol. Once in the atmosphere they slowly degrade, ultimately leading to the formation of hydrogen fluoride (HF), the dominant reservoir of stratospheric fluorine due to its extreme stability. Monitoring the growth of stratospheric HF is therefore an important marker for the success of the Montreal Protocol. We report the comparison of global distributions and trends of HF measured in the Earth's atmosphere by the satellite remote-sensing instruments ACE-FTS (Atmospheric Chemistry Experiment Fourier transform spectrometer), which has been recording atmospheric spectra since 2004, and HALOE (HALogen Occultation Experiment), which recorded atmospheric spectra between 1991 and 2005, with the output of SLIMCAT, a state-of-the-art three-dimensional chemical transport model. In general the agreement between observation and model is good, although the ACE-FTS measurements are biased high by ∼ 10 % relative to HALOE. The observed global HF trends reveal a substantial slowing down in the rate of increase of HF since the 1990s: 4.97 ± 0.12 % year−1 (1991–1997; HALOE), 1.12 ± 0.08 % year−1 (1998–2005; HALOE), and 0.52 ± 0.03 % year−1 (2004–2012; ACE-FTS). In comparison, SLIMCAT calculates trends of 4.01, 1.10, and 0.48 % year−1, respectively, for the same periods; the agreement is very good for all but the earlier of the two HALOE periods. Furthermore, the observations reveal variations in the HF trends with latitude and altitude; for example, between 2004 and 2012 HF actually decreased in the Southern Hemisphere below ∼ 35 km. An additional SLIMCAT simulation with repeating meteorology for the year 2000 produces much cleaner trends in HF with minimal variations with latitude and altitude. Therefore, the variations with latitude and altitude in the observed HF trends are due to variability in stratospheric dynamics on the timescale of a few years. Overall, the agreement between observation and model points towards the ongoing success of the Montreal Protocol and the usefulness of HF as a metric for stratospheric fluorine.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".