Calvari, Sonia

Effusion rate and degassing data collected at Mt. Etna volcano (Italy) in 2001 show variations occurring on time scales of hours to months. We use both long- and short-term data sets spanning January to August to identify this variation. The long data sets comprise a satellite- and ground-based time series of effusion rates, and the latter include field-based effusion rate and degassing data collected May 29–31. The satellite-derived effusion rates for January through August reveal four volumetric pulses that are characterized by increasing mean effusion rate values and lead up to the 2001 flank eruption. Peak effusion rates during these 23–57 day pulses were 1.2 m3 s-1 in Pulse 1 (1 Jan–4 Mar), 1.1 m3 s-1 in Pulse 2 (5 Mar–21 Apr), 4.2 m3 s-1 in Pulse 3 (24 Apr–18 Jun), 8.8 m3 s-1 in Pulse 4 (23 Jun–16 Jul), and 22.2 m3 s-1 during the flank eruption (17 Jul–9 Aug). Rank-order analysis of the satellite data shows that effusion rate values during the 2001 flank eruption define a statistically different trend than Etna's persistent activity from Jan 1 to Jul 17. Data prior to the flank eruption obey a power-law relationship that may define an effusion rate threshold of ~3–5 m3 s-1 for Etna's typical persistent activity. Our short-term data coincide with the satellite-derived peak effusion period of Pulse 3. Degassing (at-vent puff frequency) shows a general increase from May 29 to 31, with hour-long variations in both puff frequency and lava flow velocity (effusion rate). We identify five 3–14 h degassing periods that contain 26 shorter (19–126 min-long) oscillations. This variation shows some positive correlation with effusion rate measurements during the same time period. If a relationship between puff frequency and effusion rate is valid, we propose that their short-term variation is the result of changes in the supply rate of magma to the near-vent conduit system. Therefore, these short-term data provide some evidence that the clear weeks- to months-long variation in Etna's effusive activity (January–August 2001) was overprinted by a minutes- to hour-scale oscillation in shallow supply.

The idea of this special issue comes out of discussions at the workshop on “Uncertainty Quantification in Lava Flow Hazard Modeling and Real-Time Source Term Provision” held at the Istituto Nazionale di Geofisica e Vulcanologia (INGV) in Catania (Italy) during February 2017. The workshop was supported by the MeMoVolc network of the European Science Foundation, and was attended by delegates from Italy, France, UK, Germany, Spain, and the USA. At the workshop, researchers expert in lava’s physical properties, satellite volcano hot spot detection, lava flow modeling, and effusive crisis response were brought together to share experiences and perspectives on the current capabilities in application of remote sensing and modeling to better forecast hazards during effusive eruptions. In addition, the workshop led to a community-wide agreement that many scientific uncertainties still need to be resolved in model-based hazard assessments, and this requires support through the creation of a special working group. This special issue consists of 15 papers focused largely on the conclusions of the MeMoVolc workshop, as follows.

Lava flow surface morphologies are like pages of a book. If we are able to read the writing of that book, we can understand its content, and learn, act, and react accordingly. In the same way, if we understand lava surface morphology, recognise how it formed and the hazard it poses while flowing, we can adopt actions to protect from lava flow invasion our villages, infrastructures and local population. The surface of lava is a function of intrinsic and extrinsic qualities, and their combination results in different shapes, sizes, and complexities, as well as in different hazards. Initial sheet flows spreading at high speed have great potential for devastating land, as happened in Hawaii in May-August 2018 (Neal et al., 2018). However, their destructive potential significantly decreases with time and distance from the vent. Conversely, lava oozing from the distal exit of lava tubes moves slowly but allows the tubes to expand, increasing gradually and slowly the potential hazard for invasion of more remote lands. In this paper, I present an overview of diverse lava flow surfaces, morphologies and structures in a framework of their generating eruptive parameters, in order to suggest preliminary but prompt hazard evaluations that could be applied during the initial phases of effusive volcanic crises at basaltic volcanoes worldwide.

The 2021 eruption at Tajogaite (Cumbre Vieja) volcano (La Palma, Spain) was characterized by Strombolian eruptions, Hawaiian fountaining, white gasdominated and grey ash-rich plumes, and lava effusion from multiple vents. The variety of eruptive styles displayed simultaneously and throughout the eruption presents an opportunity to explore controls on explosivity and the relationship between explosive and effusive activity. Explosive eruption dynamics were recorded using ground-based thermal photography and videography. We show results from the analysis of short (<5 min) near-daily thermal videos taken throughout the eruption from multiple ground-based locations and continuous time-lapse thermal photos over the period November 16 to November 26. We measure the apparent radius, velocity, and volume flux of the high-temperature gas-and-ash jet and lava fountaining behaviors to investigate the evolution of the explosive activity over multiple time scales (seconds-minutes, hours, and daysweeks). We find fluctuations in volume flux of explosive material that correlate with changes in volcanic tremor and hours-long increases in explosive flux that are immediately preceded by increases in lava effusion rate. Correlated behavior at multiple vents suggests dynamic magma ascent pathways connected in the shallow (tens to hundreds of meters) sub-surface. We interpret the changes in explosivity and the relative amounts of effusive and explosivity to be the result of changes in gas flux and the degree of gas coupling.

Stromboli volcano has a persistent activity that is almost exclusively explosive. Predomi- nated by low intensity events, this activity is occasionally interspersed with more powerful episodes, known as major explosions and paroxysms, which represent the main hazards for the inhabitants of the island. Here, we propose a machine learning approach to distinguish between paroxysms and major explosions by using satellite-derived measurements. We investigated the high energy explosive events occurring in the period January 2018–April 2021. Three distinguishing features are taken into account, namely (i) the temporal variations of surface temperature over the summit area, (ii) the magnitude of the explosive volcanic deposits emplaced during each explosion, and (iii) the height of the volcanic ash plume produced by the explosive events. We use optical satellite imagery to compute the land surface temperature (LST) and the ash plume height (PH). The magnitude of the explosive volcanic deposits (EVD) is estimated by using multi-temporal Synthetic Aperture Radar (SAR) intensity images. Once the input feature vectors were identified, we designed a k-means unsupervised classifier to group the explosive events at Stromboli volcano based on their similarities in two clusters: (1) paroxysms and (2) major explosions. The major explosions are identified by low/medium thermal content, i.e., LSTI around 1.4 ◦C, low plume height, i.e., PH around 420 m, and low production of explosive deposits, i.e., EVD around 2.5. The paroxysms are extreme events mainly characterized by medium/high thermal content, i.e., LSTI around 2.3 ◦C, medium/high plume height, i.e., PH around 3330 m, and high production of explosive deposits, i.e., EVD around 10.17. The centroids with coordinates (PH, EVD, LSTI) are: Cp (3330, 10.7, 2.3) for the paroxysms, and Cme (420, 2.5, 1.4) for the major explosions.

A number of tumuli formed on the aa-dominated lava fan complex which developed in the medial zone of the 1983 flow-field of Mount Etna during the later stages of the eruption. This complex flow-field formed on shallow sloping ground below a scarp between 1900 and 1700 m asl. A major tube system fed a branching tube network in the fan complex. Numerous tumuli and break-outs of lava formed in the fan. Three main types of tumulus are identified: (1) Focal tumuli, which are formed from the break-up and uplift of `old´, thick lava crust and themselves become sustained sites for the distribution of lava both as flows and within distributary tubes. These focal tumuli are significant centres associated with major tubes. (2) Satellite tumuli, which are typically elongate, whale-back shaped features that branch out from focal tumuli. These satellite tumuli were initially lava flows erupted from a focal tumulus. The crust of the flow slowed or came to a halt and the rigid crust became uplifted and fractured, forming a dome-shaped ridge feature. These satellite tumuli continued to be fed from the focal tumulus and became sites of lava emission with numerous break-outs. (3) Distributary tumuli formed on the fan associated with short-lived break-outs from tubes and are relatively simple structures formed from limited effusion of toey lobes and pahoehoe lava. The major tumuli on the fan complex show distinct dilation fractures. The fracture surfaces provide good exposure of the crust and three distinct zones are recognised – an upper zone showing columnar jointing, a middle zone consisting of planar fracture surfaces and a basal zone with distinctive banded planar fracture surfaces showing evidence of both brittle and ductile formation. Using these data a model is proposed for tumulus growth. Field analysis of the fan complex shows how it was fed by a branching tube system, leading to flow thickening, formation of tumuli and numerous ephemeral boccas.

Forest destruction by ‘a‘ ̄a lava flow is common. However, mechanical and thermal interactions between the invading lava and the invaded forest are poorly constrained. We complete mapping, thermal image and sample analyses of a channel-fed ‘a‘a ̄ lava flow system that invaded forest on the NE flank of Mt. Etna (Italy) in 2002. These lava flows destroyed 231,000 trees, only 2% of which are still visible as felled trunks on the levees or at the channel-levee contact. The remaining 98% were first felled by the flow front, with the trunks then buried by the flow. Rare tree molds can be found at the rubble levee base where trees were buried by avalanching hot breccia and then burnt through, with a time scale for total combustion being a few days. Protruding trunks fell away from the flow, if felled by blocks avalanching down the levee flank, or became aligned with the flow if falling onto the moving stream. Estimated cooling rates (0.1–5.5 ◦C km− 1) are normal for well-insulated ‘a‘a ̄ flow, suggesting no thermal interaction. We find the highest phenocryst concentrations (of 50–60%, above an expected value of 30–40%) in low velocity (<0.5 m s− 1) locations. These low velocity zones are also characterized by high trunk concentrations. Thus, the common factor behind crystal and trunk deposition is velocity. That is, when the lava slows down, crystal settling occurs and trunks are preferentially deposited. Thus, although we find no thermal or textural effects due to the presence of the forest, we do find mechanical and environmental in- teractions where the trees are consumed to become part of the flow.

Stromboli’s 5 April 2003 explosion sent an ash plume to 4 km and blocks to 2 km, representing one of the most powerful events over the last 100 years. A thermal sensor 450 m east of the vent and a helicopter-flown thermal camera captured the event dynamics allowing detailed reconstruction. This review links previous studies providing a complete collation and clarification of the actual event chronology, while showing how relatively inexpensive thermal sensors can be used to provide great insight into processes that cannot be observed from locations outside of the eruption cloud. The eruption progressed through four phases, comprised 29 discrete explosions and lasted 373 s. The opening phase (phase 1) comprised ~30 s of precursory ash emission, with stronger emission beginning after 17 s. This was abruptly terminated by the main blast of phase 2 which comprised emission of a rapidly expanding ash cloud followed, after 0.4 s, by a powerful jet with velocities of up to 320 m/s. A second explosive phase (phase 3) began 38 s later and involved ascent of a phoenix cloud and explosive emission above a lateral vent lasting 75 s. This was followed by a 175-s-long phase of weaker, pulsed emission. The eruption was terminated by a series of three explosions (phase 4) sending ash to ~600 m at velocities of 27-45 m/s and lasting 87 s. Together these results have shown that a low energy opening phase was followed by the highest energy phase. Each phase itself comprised groups of discrete explosions, with energy of the explosions diminishing during the two final phases.

In the paper by Gouhier, M., Harris, A., Calvari, S., Labazuy, P., Guéhenneux, Y., Donnadieu, F., Valade, S, entitled “Lava discharge during Etna’s January 2011 fire fountain tracked using MSG-SEVIRI” (Bull Volcanol (2012) 74:787–793, DOI 10.1007/s00445-011-0572-y), we present data from a Doppler radar (VOLDORAD 2B). This ground-based Lband radar has been monitoring the eruptive activity of the summit craters of Mt. Etna in real-time since July 2009 from a site about 3.5 km SSE of the craters. Examples of applications of this type of radar are reviewed by Donnadieu (2012) and shown on the VOLDORAD website (http://wwwobs. univbpclermont.fr/SO/televolc/voldorad/). Although designed and owned by the Observatoire de Physique du Globe in Clermont-Ferrand (OPGC), France, VOLDORAD 2B is operated jointly with the INGV-Catania (Italy) in the framework of a technical and scientific collaboration agreement between the INGV of Catania, the French CNRS and the OPGC-Université Blaise Pascal in Clermont- Ferrand. The system also utilizes a dedicated micropatch antenna designed at the University of Calabria (Boccia et al. 2010) and owned by INGV. The objective of the joint acquisition of the radar data by INGV-Catania and the OPGC is twofold: (1) to mitigate volcanic risks at Etna by better assessing the hazards arising from ash plumes and (2) to allow detailed study of volcanic activity and its environmental impact. In the paper by Gouhier et al. (2012), we failed to highlight this important collaboration between the INGV Catania and the OPGC; a cooperation essential for the past, current and future generation of such valuable data sets. Specifically we wish to acknowledge the roles of Mauro Coltelli, Michele Prestifilippo and Simona Scollo for their important input into this project, and pivotal role in setting up, and maintaining, this collaborative deployment.

Measurement of effusion rate is a primary objective for studies that model lava flow and magma system dynamics, as well as for monitoring efforts during on-going eruptions. However, its exact definition remains a source of confusion, and problems occur when comparing volume flux values that are averaged over different time periods or spatial scales, or measured using different approaches. Thus our aims are to: (1) define effusion rate terminology; and (2) assess the various measurement methods and their results. We first distinguish between instantaneous effusion rate, and time-averaged discharge rate. Eruption rate is next defined as the total volume of lava emplaced since the beginning of the eruption divided by the time since the eruption began. The ultimate extension of this is mean output rate, this being the final volume of erupted lava divided by total eruption duration. Whether these values are total values, i.e. the flux feeding all flow units across the entire flow field, or local, i.e. the flux feeding a single active unit within a flow field across which many units are active, also needs to be specified. No approach is without its problems, and all can have large error (up to ∼50%). However, good agreement between diverse approaches shows that reliable estimates can be made if each approach is applied carefully and takes into account the caveats we detail here. There are three important factors to consider and state when measuring, giving or using an effusion rate. First, the time-period over which the value was averaged; second, whether the measurement applies to the entire active flow field, or a single lava flow within that field; and third, the measurement technique and its accompanying assumptions.