Enhanced Precipitation Induced by a Volcanic Eruption Acting as an Obstacle to Atmospheric Flow
Bibliographic record
Abstract
Abstract At 2020 UTC 16 March 2024, the Sundhnúksgígar crater row located north of the town of Grindavík on the Reykjanes Peninsula, Iceland, erupted. Forty minutes after the start of the eruption, a significant rain shower started 20 km downwind of the eruption site to the west of the Keflavík International Airport. Since there was no precipitation over the peninsula prior to the eruption and the precipitation event started shortly after the eruption and downwind from the volcano, we were led to believe that it was linked to the eruption. In the style of a mystery novel, we sought to elucidate the mechanism linking the eruption and the rain shower. Two different mechanisms were initially investigated: 1) the volcano heat and moisture led to convection and 2) the volcanic ash created condensation nuclei. Using radar data, ground-based measurements, and model soundings, it was found that the eruption could not be directly responsible for the precipitation event through either of these mechanisms. As such, another process had to be involved, namely, that the eruption acted as an obstacle to the atmospheric flow causing precipitation. Significance Statement Shortly after a volcano in southwest Iceland erupted, an unforecasted heavy rain shower started west of the Keflavík International Airport, the main airport deserving Reykjavik, Iceland. Such a heavy shower could have disrupted the airport activities and might have been a hazard to landing and departing aircraft should it have occurred over the airport. We investigated how the volcano caused the rainstorm as the rain started shortly after and downwind of the eruption. The uncovered process proved to be unexpected, justifying this publication: It appears that the eruption acted as an obstacle that wind had to leap over, and this sudden ascending motion quickly produced significant precipitation downwind.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".