Lidar observations of volcanic aerosol over the UK since June 2019
Bibliographic record
Abstract
On 22 June 2019, the Raikoke volcano in the Kuril Islands erupted, sending a plume of ask and sulphur dioxide into the stratosphere. A Raman lidar system at Capel Dewi, 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 lidar was modified to give it much enhanced sensitivity in the elastic channel, allowing measurements up to 25 km, but the Raman channel is 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. Small amounts of stratospheric aerosol were measured prior to the arrival of the volcanic cloud, probably from pyroconvection over Canada. Volcanic ash began to arrive as a thin layer at 14 km late on 3 July, extending over the following month to fill the stratosphere below around 19 km. Aerosol optical depths reached around 0.03 by mid-August and continued at this level for the remainder of the year. The location of peak backscatter varied considerably but was generally around 15 km. However, on one notable occasion on August 25, 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".