Support to Aviation Control Service (SACS): an online service for near real-time satellite monitoring of volcanic plumes
Bibliographic record
Abstract
Abstract. Volcanic eruptions emit plumes of ash and gases in the atmosphere, potentially at very high altitudes. Ash rich plumes are hazardous for airplanes as ash is very abrasive and easily melts inside their engines. With more than 50 active volcanoes per year and the ever increasing number of commercial flights, the safety of airplanes is a real concern. Satellite measurements are ideal for monitoring global volcanic activity and, in combination with atmospheric dispersion models, to track and forecast volcanic plumes. Here we present the Support to Aviation Control Service (SACS, http://sacs.aeronomie.be), which is a free online service initiated by ESA for the near real-time (NRT) satellite monitoring of volcanic plumes of SO2 and ash. It combines data from two UV-visible (OMI, GOME-2) and two infrared (AIRS, IASI) spectrometers. This new multi-sensor warning system of volcanic plumes, running since April 2012, is based on the detection of SO2 and is optimised to avoid false alerts while at the same time limiting the number of notifications in case of large plumes. The system shows successful results with 95% of our notifications corresponding to true volcanic activity.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.067 | 0.034 |
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".