Tephra2 Probabilistic Runner

By Costanza Bonadonna1, Laura J Connor2, Chuck B Connor2, Leah Michelle Courtland2

1. University of Geneva, Switzerland 2. University of South Florida (USF)

Will vary the wind field for a given eruption in order to determine the most probable mass loading of tephra on the ground.

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Archive Version 1.1
Published on 09 Aug 2016, unpublished on 31 Oct 2024 All versions

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Abstract

Numerical models used for tephra hazard assessment (Hazard Models) typically result from the combination and integration of different theories and modeling approaches depending on the specific eruptive scenario and mitigation program required. They can be grouped within two main categories: particle-tracking models and advection-diffusion models. Particle-tracking models are Eulerian or Lagrangian models that can forecast volcanic-cloud position at specific times and space. They are mainly used for aviation-safety purposes. Advection-diffusion models are Eulerian models that describe the solution of the equations of particle diffusion, transport, and sedimentation and can forecast tephra accumulation on the ground relative to a particle-release source. These models are mainly used for civil protection purposes, such as giving public warnings and planning mitigation measures. TEPHRA2 is written in C and is used to forecast tephra accumulation following explosive volcanic eruptions. The code uses a closed-form solution of the advection-diffusion equation, particle fall velocities that depend on local Reynold’s number, and stratified wind field to forecast tephra accumulation, expressed as kilogram per cubic meter, particle size distribution at specific locations from the vent, and maximum clast size expected as a function of distance from the vent. In practice, deposits of specific eruptions can be modeled if sufficient field data are available.

Cite this work

Researchers should cite this work as follows:

  • Costanza Bonadonna; Laura J Connor; Chuck B Connor; Leah Michelle Courtland (2012), "Tephra2 Probabilistic Runner," https://theghub.org/resources/tephra2prob.

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