
doi: 10.1002/2014jb011556
AbstractOver the past decade, a proliferation of new technologies has pushed forward our ability to measure the dynamics of volcanic emissions as they exit, and ascend above, the vent. Measuring parameters of all particles as they exit the vent during an explosive eruption is the best way to gather parameters such as size, shape, velocity, and mass for the solid (particulate) fraction of the plume, in our case this being the lapilli and bomb component. We compute particle velocities and size distributions using high spatial resolution (centimeter‐sized pixel) thermal infrared imagery collected at 200 Hz for small explosive eruptions at Stromboli (Italy). Our study covers 13 eruptions from Stromboli's southwest crater that occured in October 2012, plus 13 eruptions from the southwest crater, and 5 eruptions from the northeast crater in May 2014. We obtain a statistically robust database for size, mass, and velocity of 83,000 particles. Most particles have sizes of 5 to 15 cm so that the majority of individual particle masses are below 0.4 kg. However, 4950 (6%) of the particles are heavier than 5 kg and represent 59% of the total mass erupted. We also show that the smallest particles detected have the highest velocities with the maximum recorded vent‐leaving velocity being 240 m/s. While the thermal data provide insights into particle emission and launch dynamics, correlation with seismic data sheds light on the source mechanism. Our results lead us to suggest that pyroclast‐dominated explosions are a consequence of the presence of a viscous, degassed cap at the head of the magma column, whereas gas‐dominated events are a consequence of slug bursting in a “cleaner” conduit, the cap having been lost by convective overturn.
[SDU] Sciences of the Universe [physics], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [SDU]Sciences of the Universe [physics], [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, [INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG]
[SDU] Sciences of the Universe [physics], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [SDU]Sciences of the Universe [physics], [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, [INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG]
| citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 36 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
