External Surface Water Influence on Explosive Eruption Dynamics, With Implications for Stratospheric Sulfur Delivery and Volcano-Climate Feedback
Bibliographic record
Abstract
Explosive volcanic eruptions can inject sulfur dioxide (SO2) into the stratosphere to form aerosol particles that modify Earth’s radiation balance and drive surface cooling. Eruptions involving interactions with shallow layers (≤500 m) of surface water and ice modify the eruption dynamics that govern the delivery of SO2 to the stratosphere. External surface water controls the evolution of explosive eruptions in two ways that are poorly understood: 1) by modulating the hydrostatic pressure within the conduit and at the vent, and 2) through the ingestion and mixing of external water, which governs fine ash production and eruption column buoyancy flux. To make progress, we couple one-dimensional models of conduit flow and atmospheric column rise through a novel “magma-water interaction” model that simulates the occurrence, extent and consequences of water entrainment depending on the depth of a surface water layer. We explore the effects of hydrostatic pressure on magma ascent in the conduit and gas decompression at the vent, and the conditions for which water entrainment drives fine ash production by quench fragmentation, eruption column collapse, or outright failure of the jet to breach the water surface. We show that the efficiency of water entrainment into the jet is the predominant control on jet behavior. For an increase in water depth of 50–100 m, the critical magma mass eruption rate required for eruption columns to reach the tropopause increases by an order of magnitude. Finally, we estimate that enhanced emission of fine ash leads to up to a 2-fold increase in the mass flux of particles < 125 μm to spreading umbrella clouds, together with up to a 10-fold increase in water mass flux, conditions that can enhance the removal of SO2 via chemical scavenging and ash sedimentation. On average, compared to purely magmatic eruptions, we suggest that hydrovolcanic eruptions will be characterized by reduced climate forcing. Our results suggest one possible mechanism for volcano-climate feedback: temporal changes with climate in surface distributions of water and ice may modify the relative global frequency or dominance of hydrovolcanic eruption processes, modulating, in turn, global patterns in volcano-climate forcing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".