Sensitivity of dispersion model forecasts of volcanic ash clouds to the physical characteristics of the particles
This study examines the sensitivity of atmospheric dispersion model forecasts of volcanic ash clouds to the physical characteristics assigned to the particles. We show that the particle size distribution (PSD) used to initialise a dispersion model has a significant impact on the forecast of the mass...
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ftunivgeneve:oai:unige.ch:unige:77956 2023-05-15T16:09:31+02:00 Sensitivity of dispersion model forecasts of volcanic ash clouds to the physical characteristics of the particles Beckett, F. M. Witham, C.S. Hort, M.C. Stevenson, J.A. Bonadonna, Costanza Millington, S.C. 2015 https://archive-ouverte.unige.ch/unige:77956 eng eng info:eu-repo/semantics/altIdentifier/doi/10.1002/2015JD023609 unige:77956 https://archive-ouverte.unige.ch/unige:77956 info:eu-repo/semantics/embargoedAccess ISSN: 2169-897X Journal of geophysical research. Atmospheres, Vol. 120, No 22 (2015) pp. 11,636-11,652 info:eu-repo/classification/ddc/550 Text Article scientifique info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion 2015 ftunivgeneve https://doi.org/10.1002/2015JD023609 2022-06-19T23:40:05Z This study examines the sensitivity of atmospheric dispersion model forecasts of volcanic ash clouds to the physical characteristics assigned to the particles. We show that the particle size distribution (PSD) used to initialise a dispersion model has a significant impact on the forecast of the mass loading of the ash particles in the atmosphere. This is because the modeled fall velocity of the particles is sensitive to the particle diameter. Forecasts of the long-range transport of the ash cloud consider particles with diameters between 0.1 μm and 100 μm. The fall velocity of particles with diameter 100 μm is over 5 orders of magnitude greater than a particle with diameter 0.1 μm, and 30 μm particles fall 88% slower and travel up to 5× further than a 100 μm particle. Identifying the PSD of the ash cloud at the source, which is required to initialise a model, is difficult. Further, aggregation processes are currently not explicitly modeled in operational dispersion models due to the high computational costs associated with aggregation schemes. We show that using a modified total grain size distribution (TGSD) that effectively accounts for aggregation processes improves the modeled PSD of the ash cloud and deposits from the eruption of Eyjafjallajökull in 2010. Knowledge of the TGSD of an eruption is therefore critical for reducing uncertainty in quantitative forecasts of ash cloud dispersion. The density and shape assigned to the model particles have a lesser but still significant impact on the calculated fall velocity. Accounting for the density distribution and sphericity of ash from the eruption of Eyjafjallajökull in 2010, modeled particles can travel up to 84% further than particles with default particle characteristics that assume the particles are spherical and have a fixed density. Article in Journal/Newspaper Eyjafjallajökull Université de Genève: Archive ouverte UNIGE Journal of Geophysical Research: Atmospheres 120 22 11,636 11,652 |
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Université de Genève: Archive ouverte UNIGE |
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info:eu-repo/classification/ddc/550 |
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info:eu-repo/classification/ddc/550 Beckett, F. M. Witham, C.S. Hort, M.C. Stevenson, J.A. Bonadonna, Costanza Millington, S.C. Sensitivity of dispersion model forecasts of volcanic ash clouds to the physical characteristics of the particles |
topic_facet |
info:eu-repo/classification/ddc/550 |
description |
This study examines the sensitivity of atmospheric dispersion model forecasts of volcanic ash clouds to the physical characteristics assigned to the particles. We show that the particle size distribution (PSD) used to initialise a dispersion model has a significant impact on the forecast of the mass loading of the ash particles in the atmosphere. This is because the modeled fall velocity of the particles is sensitive to the particle diameter. Forecasts of the long-range transport of the ash cloud consider particles with diameters between 0.1 μm and 100 μm. The fall velocity of particles with diameter 100 μm is over 5 orders of magnitude greater than a particle with diameter 0.1 μm, and 30 μm particles fall 88% slower and travel up to 5× further than a 100 μm particle. Identifying the PSD of the ash cloud at the source, which is required to initialise a model, is difficult. Further, aggregation processes are currently not explicitly modeled in operational dispersion models due to the high computational costs associated with aggregation schemes. We show that using a modified total grain size distribution (TGSD) that effectively accounts for aggregation processes improves the modeled PSD of the ash cloud and deposits from the eruption of Eyjafjallajökull in 2010. Knowledge of the TGSD of an eruption is therefore critical for reducing uncertainty in quantitative forecasts of ash cloud dispersion. The density and shape assigned to the model particles have a lesser but still significant impact on the calculated fall velocity. Accounting for the density distribution and sphericity of ash from the eruption of Eyjafjallajökull in 2010, modeled particles can travel up to 84% further than particles with default particle characteristics that assume the particles are spherical and have a fixed density. |
format |
Article in Journal/Newspaper |
author |
Beckett, F. M. Witham, C.S. Hort, M.C. Stevenson, J.A. Bonadonna, Costanza Millington, S.C. |
author_facet |
Beckett, F. M. Witham, C.S. Hort, M.C. Stevenson, J.A. Bonadonna, Costanza Millington, S.C. |
author_sort |
Beckett, F. M. |
title |
Sensitivity of dispersion model forecasts of volcanic ash clouds to the physical characteristics of the particles |
title_short |
Sensitivity of dispersion model forecasts of volcanic ash clouds to the physical characteristics of the particles |
title_full |
Sensitivity of dispersion model forecasts of volcanic ash clouds to the physical characteristics of the particles |
title_fullStr |
Sensitivity of dispersion model forecasts of volcanic ash clouds to the physical characteristics of the particles |
title_full_unstemmed |
Sensitivity of dispersion model forecasts of volcanic ash clouds to the physical characteristics of the particles |
title_sort |
sensitivity of dispersion model forecasts of volcanic ash clouds to the physical characteristics of the particles |
publishDate |
2015 |
url |
https://archive-ouverte.unige.ch/unige:77956 |
genre |
Eyjafjallajökull |
genre_facet |
Eyjafjallajökull |
op_source |
ISSN: 2169-897X Journal of geophysical research. Atmospheres, Vol. 120, No 22 (2015) pp. 11,636-11,652 |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1002/2015JD023609 unige:77956 https://archive-ouverte.unige.ch/unige:77956 |
op_rights |
info:eu-repo/semantics/embargoedAccess |
op_doi |
https://doi.org/10.1002/2015JD023609 |
container_title |
Journal of Geophysical Research: Atmospheres |
container_volume |
120 |
container_issue |
22 |
container_start_page |
11,636 |
op_container_end_page |
11,652 |
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1766405388380405760 |