Long-term evolution and seasonal modulation of methanol above Jungfraujoch (46.5° N, 8.0° E): optimisation of the retrieval strategy, comparison with model simulations and independent observations
Bibliographic record
Abstract
Abstract. Methanol (CH3OH) is the second most abundant organic compound in the Earth's atmosphere after methane. In this work, we present the first long-term time series of methanol total, lower tropospheric and upper tropospheric-lower stratospheric partial columns derived from the analysis of high resolution Fourier transform infrared solar spectra recorded at the Jungfraujoch station (46.5° N, 3580 m a.s.l.). The retrieval of methanol is very challenging due to strong absorptions of ozone in the region of the selected υ8 band of CH3OH. Two wide spectral intervals have been defined and adjusted in order to maximize the information content. Methanol does not exhibit a significant trend over the 1995–2012 time period, but a strong seasonal modulation characterized by maximum values and variability in June–July, minimum columns in winter and a peak-to-peak amplitude of 130%. In situ measurements performed at the Jungfraujoch and ACE-FTS occultations give similar results for the methanol seasonal variation. The total and lower tropospheric columns are also compared with IMAGESv2 model simulations. There is no systematic bias between the observations and IMAGESv2 but the model underestimates the peak-to-peak amplitude of the seasonal modulations.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".