Reconstructing volcanic plume evolution integrating satellite and ground-based data: application to the 23 November 2013 Etna eruption

Poret, Matthieu; Corradini, Stefano; Merucci, Luca; Costa, Antonio; Andronico, Daniele; Montopoli, Mario; Vulpiani, G.; Freret-Lorgeril, Valentin

doi:10.5194/acp-18-4695-2018

Cited by 32 publications

(31 citation statements)

References 63 publications

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“…Figure 7 also shows satellite images retrieved at 10:00 GMT and the tephra deposits obtained for 12 August 2011, and 23 November 2013, following our approach. Results for 23 November 2013, are in good agreement with the isomass map reported in [51], as shown in Figure 8. The computed mass loading is in fact inside one-fifth and five times the observed thresholds that are used for modelling validation purposes [27].…”

Section: Application To Two Past Lava-fountain-fed Plumessupporting

confidence: 87%

“…08:00 09:00 10:00 11:00 Computed value kg m 2 Figure 8. Comparison between the punctual tephra mass loading measured on the ground and reported in [51], and values computed with TEPHRA2 for the event on 23 November 2013. Dashed lines indicate over and under estimation of one-fifth and five times the observed values.…”

Section: Application To Two Past Lava-fountain-fed Plumesmentioning

confidence: 99%

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Near-Real-Time Tephra Fallout Assessment at Mt. Etna, Italy

et al. 2019

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During explosive eruptions, emergency responders and government agencies need to make fast decisions that should be based on an accurate forecast of tephra dispersal and assessment of the expected impact. Here, we propose a new operational tephra fallout monitoring and forecasting system based on quantitative volcanological observations and modelling. The new system runs at the Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo (INGV-OE) and is able to provide a reliable hazard assessment to the National Department of Civil Protection (DPC) during explosive eruptions. The new operational system combines data from low-cost calibrated visible cameras and satellite images to estimate the variation of column height with time and model volcanic plume and fallout in near-real-time (NRT). The new system has three main objectives: (i) to determine column height in NRT using multiple sensors (calibrated cameras and satellite images); (ii) to compute isomass and isopleth maps of tephra deposits in NRT; (iii) to help the DPC to best select the eruption scenarios run daily by INGV-OE every three hours. A particular novel feature of the new system is the computation of an isopleth map, which helps to identify the region of sedimentation of large clasts (≥5 cm) that could cause injuries to tourists, hikers, guides, and scientists, as well as damage buildings in the proximity of the summit craters. The proposed system could be easily adapted to other volcano observatories worldwide. medium lapilli has been widely considered as a primary risk agent related to explosive volcanic activity, fallout of coarse lapilli to small blocks falling from plume margins has been underrated. As an example, during the event at Etna on 23 November 2013, clasts from several centimeters to decimeters fell within 5-6 km from the summit and hit hikers who were in the touristic areas [8]. Although the assessment of tephra fallout and dispersal in distal areas has been largely considered [9][10][11][12], the reduction of volcanic impacts in proximal areas and within the first hour from the beginning of the eruption is still a challenge. As a matter of fact, regardless of the importance of this information for emergency responders and government agencies, the operational systems capable of monitoring tephra dispersal and fallout in near-real-time (NRT) and returning the expected impact assessment are still limited and not fully adapted to the growing requirements of precision and reliability.A good example of NRT tephra detection in volcano observatories is represented by the Alaska Volcano Observatory (AVO), which monitors volcanoes within the North Pacific region [13]. The AVO system analyzes data from different satellite sensors. They use a 24/7 automated ash cloud detection algorithm that sends emails and phone text alerts to the AVO members, who are, in turn, responsible for verifying if the automatic alert can be considered as true or false [13]. The Kamchatka Volcanic Eruption Response Team (KVERT) monitors 36 active volcanoes in ...

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Section: Application To Two Past Lava-fountain-fed Plumessupporting

confidence: 87%

Section: Application To Two Past Lava-fountain-fed Plumesmentioning

confidence: 99%

Near-Real-Time Tephra Fallout Assessment at Mt. Etna, Italy

et al. 2019

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“…Indeed, we assume that for a limited range within the TGSD (i.e., PM 10 ), the lognormal distribution can approximate the empirical distribution we used for characterizing the PM 10 . For the sake of simplicity, we used an empirical power law dependence of the fraction with Φ according to the following relationship (Poret et al, ):

X ((), {normalΦ}_{i}) = X ((), {normalΦ}_{4}) \times γ^{({normalΦ}_{i} - {normalΦ}_{4})}, normalΦ \geq 5

where X (Φ i ) is the fraction (in weight %) allocated to the i th bin, X (Φ 4 ) is the fraction obtained for Φ = 4, and γ is the empirical factor ( γ < 1). Although PM 10 refers to Φ ≥ 6, the Field TGSD does not permit calculating from Φ = 5 implying to start at Φ = 4 (see Figure b).…”

Section: Observational Data and Methodologymentioning

confidence: 99%

“…The best simulations are selected when k is minimized. Additionally, we calculated also the bias (to be minimized), the correlation (to be maximized), and the Student t test (Folch et al, ; Poret et al, ).…”

Section: Observational Data and Methodologymentioning

confidence: 99%

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Modeling Eruption Source Parameters by Integrating Field, Ground‐Based, and Satellite‐Based Measurements: The Case of the 23 February 2013 Etna Paroxysm

et al. 2018

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Volcanic plumes from Etna volcano (Italy) are governed by easterly winds driving ash over the Ionian Sea. The limited land tephra deposit makes total grain‐size distribution (TGSD) assessment and its fine ash fraction highly uncertain. On 23 February 2013, a lava fountain produced a ~9‐km‐high column above sea level (a.s.l.). The atypical north‐easterly wind direction dispersed the tephra from Etna to the Puglia region (southern Italy) allowing sampling up to very distal areas. This study uses field measurements to estimate the field‐based TGSD. Very fine ash distribution (particle matter below 10 μm—PM10) is explored parameterizing the field‐TGSD through a bi‐lognormal and bi‐Weibull distribution. However, none of the two latter TGSDs allow simulating any far‐traveling airborne ash up to distal areas. Accounting for the airborne ash retrieved from satellite (Spinning Enhanced Visible and Infrared Imager), we proposed an empirical modification of the field‐based TGSD including very fine ash through a power law decay of the distribution. The input source parameters are inverted by comparing simulations against measurements. Results suggest a column height of ~8.7 km a.s.l., a total erupted mass of ~4.9 × 109 kg, a PM10 content between 0.4 and 1.3 wt%, and an aggregate fraction of ~2 wt% of the fine ash. Aerosol optical depth measurements from the AErosol RObotic NETwork are also used to corroborate the results at ~1,700 km from the source. Integrating numerical models with field, ground‐based, and satellite‐based data aims at providing a better TGSD estimation including very fine ash, crucial for air traffic safety.

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