Determination and analysis of time series of CFC-11 from Lauder and Jungfraujoch
Bibliographic record
Abstract
The monitoring of the chlorofluorocarbons (CFCs) and their successive substitutes - the hydrochlorofluorocarbons (HCFCs) and the hydrofluorocarbons (HFCs) - is essential to track the evolution of their atmospheric concentrations and emissions in accordance with the Montreal Protocol on Substances that Deplete the Ozone Layer. In this study, we used the retrievals of ground-based high-resolution Fourier transform infrared (FTIR) solar spectra and model data (TOMCAT/SLIMCAT developed by Martyn Chipperfield) in order to analyse the CFC-11 total columns above the Jungfraujoch (46.5°N, 3580 m a.s.l.) and Lauder (45°S, 370 m a.s.l) stations. The Jungfraujoch time series has been scaled allowing the creation of a significant time series from June 1986 to December 2020. We analysed and compared ground-based FTIR and model data for both stations to obtain the trends for the last 20 years. A deceleration in the CFC-11 total column decrease has been observed from 2013 in both stations as reported by Montzka et al., 2018 and Rigby et al., 2019. Lauder time series however shows an acceleration in the decrease over the period between 2008 and 2012. Currently, we are (in collaboration with Dan Smale) therefore studying the possible causes of this behaviour since the drop is mainly observed on the tropospheric column.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".