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Authors: Barsotti, S.* 
Neri, A.* 
Scire, J. S.* 
Title: The VOL-CALPUFF model for atmospheric ash dispersal: 1. Approach and physical formulation
Issue Date: 12-Mar-2008
Series/Report no.: /113 (2008)
DOI: 10.1029/2006JB004623
Keywords: volcanic plume
ash dispersal
numerical modelling
Subject Classification04. Solid Earth::04.08. Volcanology::04.08.99. General or miscellaneous 
Abstract: We present a new modeling tool, named VOL-CALPUFF, that is able to simulate the transient and three-dimensional transport and deposition of volcanic ash under the action of realistic meteorological and volcanological conditions throughout eruption duration. The new model derives from the CALPUFF System, a software program widely used in environmental applications of pollutant dispersion, that describes the dispersal process in both the proximal and distal regions and also in the presence of complex orography. The main novel feature of the model is its capability of coupling a Eulerian description of plume rise with a Lagrangian representation of ash dispersal described as a series of diffusing packets of particles or puffs. The model is also able to describe the multiparticle nature of the mixture as well as the tilting effects of the plume due to wind action. The dispersal dynamics and ash deposition are described by using refined orography-corrected meteorological data with a spatial resolution up to 1 km or less and a temporal step of 1 h. The modeling approach also keeps the execution time to a few minutes on common PCs, thus making VOL-CALPUFF a possible tool for the production of ash dispersal forecasts for hazard assessment. Besides the model formulation, this paper presents the type of outcomes produced by VOL-CALPUFF, shows the effect of main model parameters on results, and also anticipates the fundamental control of atmospheric conditions on the ash dispersal processes. In the companion paper, Barsotti and Neri present a first thorough application of VOL-CALPUFF to the simulation of a weak plume at Mount Etna (Italy) with the specific aim of comparing model predictions with independent observations.
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