Measurement Report: Lidar measurements of stratospheric aerosol following the Raikoke and Ulawun volcanic eruptions
Bibliographic record
Abstract
Abstract. On 22 June 2019 the Raikoke volcano in the Kuril islands erupted, sending a plume of ash and sulphur dioxide into the stratosphere. A Raman lidar system at Capel Dewi Atmospheric Observatory, UK (52.4° N, 4.1° W) has been used to measure the extent and optical depth of the stratospheric aerosol layer following the eruption. The elastic channel allowed measurements up to 25 km, but the Raman channel was only sensitive to the troposphere. Therefore, backscatter ratio profiles were derived by comparison with aerosol-free profiles derived from nearby radiosondes, corrected for aerosol extinction with a lidar ratio of 40–50 sr. Small amounts of aerosol were measured prior to the arrival of the volcanic cloud, probably from pyroconvection over Canada. Volcanic ash may have first arrived as a thin layer at 14 km late on 3 July, and was certainly detected from 13 July onwards, eventually extending up to 20.5 km. Aerosol optical depths reached around 0.05 by early August, decaying thereafter to around 0.01 by the end of 2019 and remaining around that level until May 2020. The location of peak backscatter varied considerably but was generally around 15 km. However, on one notable occasion on 25 August, a layer around 300 m thick with peak lidar backscatter ratio around 1.5 was observed as high as 21 km.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".