Eruption Source Parameters for forecasting ash dispersion and deposition from vulcanian eruptions at Tungurahua volcano: Insights from field data from the July 2013 eruption

Parra, René; Bernard, Benjamin; Narváez, Diego; Pennec, Jean–Luc Le; Hasselle, Nathalie; Folch, Arnau

doi:10.1016/j.jvolgeores.2015.11.001

Cited by 31 publications

(44 citation statements)

References 31 publications

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“…The meteorological outputs were used into the Eulerian FALL3DV7.1.4 [16] model to simulate the ash dispersion. Table 1 shows the ESP, emissions, timescales, and options used for modeling these four eruptions [4], [12]. We selected into FALL3DV7.1.4, the model proposed by Mastin et al [17], to estimate the emissions of volcanic ash.…”

Section: Methodsmentioning

confidence: 99%

“…So, the meteorological component of Atmospheric Transport Models (ATMs) (e.g. [3], [4]), provides key information when modeling the dispersion of volcanic ash. ATMs also require volcanological inputs, the Eruption Source Parameters (ESP) [5], which include information about particle grain size distribution, and the characterization of the source term (i.e., plume height, eruption duration, mass eruption rate, and vertical distribution of mass along the eruptive column).…”

Section: Introductionmentioning

confidence: 99%

“…Since then, ash fallout was the most frequent volcanic hazard [7], [8]. Based on field and modeling studies, ESP were proposed for forecasting ash dispersion due to Vulcanian eruptions at this volcano [4]. Fig.…”

Section: Introductionmentioning

confidence: 99%

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Influence of Spatial Resolution in Modeling the Dispersion of Volcanic Ash in Ecuador

Parra

2019

WIT Transactions on Ecology and the Environment

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Volcanic ash produces air pollution and other impacts. Regions potentially affected require information about the possible ash dispersion trajectories and affected zones by ash fallout. In the last 19 years, five volcanoes in Ecuador have produced moderate to large explosive eruptions. Information about the volcanic ash dispersion in forecasting time is a priority in Ecuador. Eulerian models can provide results with high spatial and temporal resolutions. However, they need to solve huge amounts of equations, demanding plenty of computational resources when using high spatial resolutions. It is necessary to define a pragmatic spatial resolution, suitable to compute volcanic ash dispersion, both in forecasting time and with enough accuracy. For this purpose, we simulated the meteorology over Ecuador, using the Weather Research and Forecasting (WRF3.7.1) model with spatial resolutions of 36 km, 12 km, 4 km, and 1 km. Meteorological outputs were used into the FALL3DV7.1.4 model to simulate ash dispersion from four eruptions (

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Influence of Spatial Resolution in Modeling the Dispersion of Volcanic Ash in Ecuador

Parra

2019

WIT Transactions on Ecology and the Environment

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“…3200 m above local topography) and extremely steep flanks (up to 40°). On 14 July 2013, after two months of quiescence, an unusually large Vulcanian explosion occurred at 06h46 (local time = UTC -5 hours), producing an eruption column that rose up to 8.8 km above the crater level and left a millimetre-thick fallout deposit to the west of the vent (Parra et al, 2016). PDCs were generated immediately after the first explosion and traversed the river valleys of Achupashal (runout 7.5 km) and Juive (runout 6.7 km) on the northwest and northern flanks of the volcano (Figure 1) respectively (Hall et al, 2015).…”

Section: July 2013 Vulcanian Eventmentioning

confidence: 99%

Triggering of the powerful 14 July 2013 Vulcanian explosion at Tungurahua Volcano, Ecuador

Gaunt

Burgisser

Mothes

et al. 2020

Journal of Volcanology and Geothermal Research

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The 14 July 2013 Vulcanian explosion at Tungurahua occurred after two months of quiescence and was extremely powerful, generating some of the highest infrasound energies recorded worldwide. Here we report on how a combination of geophysical data, textural measurements, and physical and mechanical tests on eruptive products allowed us to determine the processes that led to the pressurization of the conduit and triggering of this large Vulcanian event. Two weeks prior to the 14 July event, daily seismic counts and radial tilt began to steadily increase, indicating the probable intrusion of a new batch outgassing, formed a dense (< 2 % porosity), highly crystalline plug. This plug had a very low matrix permeability (10-17 to 10-18 m 2) and high tensile strength (9 to 13 MPa), forming an efficient rigid seal and preventing significant outgassing from the conduit. 2) Just below the plug, a high porosity zone (up to 50%) formed, acting as a gas storage zone, with pressurisation occurring partly under closed-system degassing. 3) The shallow conduit became pressurised due to the combination of both gas accumulation and the resistance of the plug to magma column extrusion in response to a new influx of magma. 4) On the 14 th of July a critical gas over-pressure was reached, overcoming the strength of the dense plug of magma, trigging extreme decompression and evacuation of the top two kilometres of the conduit. 5) The newly intruded magma was not directly involved in the explosion and continued to ascend during the week following the explosion.

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“…Sulpizio et al, 2012;Bonasia et al, 2013;Biass et al, 2014;Scaini et al, 2014), obtaining relevant eruption source parameters (e.g. Folch et al, 2012;Parra et al, 2016;Poret et al, 2017), impacts of past super-eruptions on climate, environment, and humans (e.g. Costa et al, 2012Costa et al, , 2014Martí et al, 2016), operational forecast of ash clouds and tephra fallout (e.g.…”

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confidence: 99%

FALL3D-8.0: a computational model for atmospheric transport and deposition of particles, aerosols and radionuclides. Part I: model physics and numerics

Folch¹,

Mingari²,

Gutiérrez³

et al. 2019

Preprint

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Abstract. This manuscript presents FALL3D-8.0, the last version release of an open-source code with 15+ years of track record and a growing number of users in the volcanological and atmospheric communities. The code has been redesigned and rewritten from scratch in the framework of the EU Center of Excellence for Exascale in Solid Earth (ChEESE) in order to overcome legacy issues and allow for successive optimisations that are already planned in the preparation of the code towards extreme-scale computing. However, this baseline version already contains substantial improvements in terms of model physics, solving algorithms, and code accuracy and performance. The code, originally conceived for atmospheric dispersal and deposition of tephra particles, has been extended to model other types of particles, aerosols and radionuclides. The solving strategy has also been changed, replacing the former central-differences scheme for a high-resolution central-upwind scheme derived from finite volumes, which minimises numerical diffusion even in presence of sharp concentration gradients and discontinuities. The parallelisation strategy, Input/Output (I/O), model pre-process workflows and memory management have also been reconsidered, leading to substantial improvements on code scalability, efficiency, and overall capability to handle much larger problems. This paper details the FALL3D-8.0 model physics and the numerical implementation of the code.

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Eruption Source Parameters for forecasting ash dispersion and deposition from vulcanian eruptions at Tungurahua volcano: Insights from field data from the July 2013 eruption

Cited by 31 publications

References 31 publications

Influence of Spatial Resolution in Modeling the Dispersion of Volcanic Ash in Ecuador

Influence of Spatial Resolution in Modeling the Dispersion of Volcanic Ash in Ecuador

Triggering of the powerful 14 July 2013 Vulcanian explosion at Tungurahua Volcano, Ecuador

FALL3D-8.0: a computational model for atmospheric transport and deposition of particles, aerosols and radionuclides. Part I: model physics and numerics

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