Aircraft-based observation of meteoric material in lower-stratospheric aerosol particles between 15 and 68° N
Bibliographic record
Abstract
Abstract. In this paper we analyze aerosol particle composition measurements from five research missions conducted between 2014 and 2018 sampling the upper troposphere and lower stratosphere (UTLS), to assess the meridional extent of particles containing meteoric material. Additional data sets from a ground based study and from a low altitude aircraft mission are used to confirm the existence of meteoric material in lower tropospheric particles. Single particle laser ablation techniques with bipolar ion detection were used to measure the chemical composition of particles in a size range of approximately 150 nm to 3 μm. The five UTLS aircraft missions cover a latitude range from 15 to 68° N, altitudes up to 21 km, and a potential temperature range from 280 to 480 K. In total, 338 363 single particles were analyzed, of which 147 338 particles were measured in the stratosphere. Of these particles, 50 688 were characterized by high abundances of magnesium, iron, and rare iron oxide compounds, together with sulfuric acid. This particle type was found almost exclusively in the stratosphere (48 610 particles) and is interpreted as meteoric material immersed or dissolved within stratospheric sulfuric acid particles. Below the tropopause, the observed fraction of this particle type decreases sharply. However, small fractional abundances were observed below 3000 m a.s.l. in the Canadian Arctic and also at the Jungfraujoch high altitude station (3600 m a.s.l.). Thus, the removal pathway by sedimentation and/or mixing into the troposphere is confirmed. In the tropical lower stratosphere, only a small fraction (
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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 | 0.000 |
| 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) | 0.000 | 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".