Trends in volcanic degassing through eruption cycles: insights from satellite measurements
Bibliographic record
Abstract
Effective use of volcanic gas measurements for eruption forecasting and hazard mitigation at active volcanoes requires an understanding of long-term degassing behavior as context. Much recent progress has been made in quantifying global volcanic emissions of sulfur dioxide (SO2) and other gas species by expanding the coverage of ground-based sensor networks and through analysis of decadal-scale satellite datasets. Combined, these advances have provided valuable constraints on the magnitude and variability of SO2 emissions at over 120 actively degassing volcanoes worldwide. Being less constrained by the style or location of volcanic activity, satellite measurements can provide greater insight into trends in volcanic degassing during eruption cycles. Here, we present an analysis of ~15 years of volcanic SO2 measurements by the ultraviolet (UV) Ozone Monitoring Instrument (OMI) aboard NASA’s Aura satellite, focused on observed trends in SO2 emissions spanning eruptions of varying magnitude. The Aura/OMI measurements have been used to estimate annual mean SO2 emissions at ~100 volcanoes active between 2005 and 2020, around 80 of which erupted during the 15-year period. Superposed epoch analysis (SEA) of SO2 emission trends for the erupting volcanoes (with eruption magnitudes ranging from Volcanic Explosivity Index [VEI] 2 to 4) provides evidence that volcanoes exhibiting higher levels of SO2 emission in the years prior to eruption typically produce eruptions of lower magnitude, and vice versa. Post-eruptive SO2 degassing exceeds pre-eruptive emissions for several years after eruptions with VEI 3-4 and may scale with eruption size; perhaps consistent with larger eruptions being supplied by larger magma intrusions which continue to degas in subsequent years. The SEA is most robust for eruptions of intermediate magnitude (VEI 3) which are the most common events in the recent global eruption record covered by the OMI measurements. Limited observations of larger eruptions (VEI 5+) suggest significant differences in degassing trends during these larger events. Future work will extend the satellite-based estimates of volcanic SO2 emissions both forward and backward in time using other UV satellite instruments, generating longer records of SO2 degassing (extending back to 1978 for the strongest volcanic sources of SO2) that will be used to further explore and constrain these relationships.
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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 | 0.002 | 0.002 |
| 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 | 0.000 |
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".