Supplementary Material to "geophysical Fingerprint of the 4–11 July 2024 Eruptive Activity at Stromboli Volcano, Italy"
crossref(2024)
Abstract
Abstract. Paroxysmal eruptions, characterized by sudden and vigorous explosive activity, are common events at many open-vent volcanoes. Stromboli volcano, Italy, is well-known for its nearly continuous degassing activity and mild explosions from the summit craters, occasionally punctuated by energetic, short-lived paroxysms. Here, we analyse multi-parameter geophysical data recorded at Stromboli in early July 2024, during activity that led to a paroxysmal eruption on 11 July. We use seismic, infrasound and ground deformation data, complemented by visual and Unoccupied Aircraft System observations, to identify key geophysical precursors to the explosive activity and reconstruct the sequence of events. Elevated levels of volcanic tremor and Very Long Period (VLP) seismicity accompanied moderate explosive activity, lava emission and small collapses from the north crater, leading to a major explosion on 4 July, 2024 at 12:16 (UTC). Collapse activity from the North crater area continued throughout July 7, while effusive activity occurred from two closely-spaced vents located on the Sciara del Fuoco slope, on the Northwest flank of the volcano. On 11 July, a rapid increase in ground deformation preceded, by approximately 10 minutes, a paroxysmal event at 12:08 (UTC); the explosion produced a 5 km-high eruptive column and pyroclastic density currents along Sciara del Fuoco. We infer that the early activity in July was linked to eruption of resident magma within the shallowest parts of the volcano plumbing. This was followed by lowering of the magma level within the conduit system as indicated by the location of newly opened effusive vents The rapid inflation observed before the paroxysmal explosion on 11 July is consistent with the rapid expansion of gas-rich magma rising from depth, as frequently suggested at Stromboli during energetic explosive events. Our results provide additional valuable insights into the eruptive dynamics of Stromboli and other open-conduit volcanoes, and emphasize the importance of integrated geophysical observations for understanding eruption dynamics, their forecasting and associated risk mitigation.
MoreTranslated text
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper