Infrared remote sensing of atmospheric composition at the Jungfraujoch station, Swiss Alps, since 1950
Bibliographic record
Abstract
It is in the early 1950s that researchers from the University of Liège have recorded the first atmospheric infrared solar spectra at the Jungfraujoch scientific station, in the Swiss Alps, at a time when climate change was not a matter of worry. These pioneering observations have allowed to confirm that methane and carbon monoxide were ubiquitous constituents of the Earth’s atmosphere. The recording of atmospheric spectra resumed in the mid-1970s, stimulated by rising concerns related to possible stratospheric ozone depletion. Since then, this monitoring activity has been conducted at that site without interruption, allowing to gather high-quality data crucial for the characterization of the Earth’s atmosphere and of the changes affecting it, resulting from anthropogenic activities or natural causes. In this talk, we present some recent results relevant for the verification of international environmental treaties such as the Montreal Protocol on substances that deplete ozone, and the Kyoto Protocol for the limitation of greenhouse gases emissions. We further illustrate contributions of our monitoring program relevant to study air quality and precursors of tropospheric ozone. Finally, we evoke a new DFG project involving University of Leeds, Universität Bremen (lead) and the University of Liège that will digitize and exploit the early spectra for in-depth investigation of atmospheric composition in the early 1950s.
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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 | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".