Sensitivity of Volcanic Ash Dispersion Modelling to Input Grain Size Distribution Based on Hydromagmatic and Magmatic Deposits
The size distribution of volcanic ash is rarely measured in real time and Volcanic Ash Advisory Centres (VAACs) often rely on a default particle size distribution (PSD) to initialise their dispersion models when forecasting the movement of ash clouds. We conducted a sensitivity study to investigate...
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ftmdpi:oai:mdpi.com:/2073-4433/11/6/567/ 2023-08-20T04:06:21+02:00 Sensitivity of Volcanic Ash Dispersion Modelling to Input Grain Size Distribution Based on Hydromagmatic and Magmatic Deposits Sara Osman Frances Beckett Alison Rust Eveanjelene Snee agris 2020-05-29 application/pdf https://doi.org/10.3390/atmos11060567 EN eng Multidisciplinary Digital Publishing Institute Air Quality https://dx.doi.org/10.3390/atmos11060567 https://creativecommons.org/licenses/by/4.0/ Atmosphere; Volume 11; Issue 6; Pages: 567 volcanic ash particle size distributions total grain size distributions dispersion modelling Text 2020 ftmdpi https://doi.org/10.3390/atmos11060567 2023-07-31T23:33:56Z The size distribution of volcanic ash is rarely measured in real time and Volcanic Ash Advisory Centres (VAACs) often rely on a default particle size distribution (PSD) to initialise their dispersion models when forecasting the movement of ash clouds. We conducted a sensitivity study to investigate the impact of PSD on model output and consider how best to apply default PSDs in operational dispersion modelling. Compiled grain size data confirm that, when considering particles likely to be in the distal ash cloud (< 125 µm diameter), magma composition and eruption size are the dominant controls on grain size distribution. Constraining the PSD is challenging but we find that the grain size of deposits from large hydromagmatic eruptions remains relatively constant with distance, suggesting that total (whole-deposit) grain size distributions (TGSDs) for these eruptions could be estimated from a few samples. We investigated the sensitivity of modelled ash mass loadings (in the air and on the ground) to input PSDs based on coarse to fine TGSDs from our dataset. We found clear differences between modelled mass loadings and the extent of the plume. Comparing TGSDs based on ground-only and ground-plus-satellite data for the Eyjafjallajökull 2010 eruption, we found that basing input PSDs on TGSDs from deposits alone (likely missing the finest particles) led to lower modelled peak ash concentrations and a smaller plume. Text Eyjafjallajökull MDPI Open Access Publishing Atmosphere 11 6 567 |
institution |
Open Polar |
collection |
MDPI Open Access Publishing |
op_collection_id |
ftmdpi |
language |
English |
topic |
volcanic ash particle size distributions total grain size distributions dispersion modelling |
spellingShingle |
volcanic ash particle size distributions total grain size distributions dispersion modelling Sara Osman Frances Beckett Alison Rust Eveanjelene Snee Sensitivity of Volcanic Ash Dispersion Modelling to Input Grain Size Distribution Based on Hydromagmatic and Magmatic Deposits |
topic_facet |
volcanic ash particle size distributions total grain size distributions dispersion modelling |
description |
The size distribution of volcanic ash is rarely measured in real time and Volcanic Ash Advisory Centres (VAACs) often rely on a default particle size distribution (PSD) to initialise their dispersion models when forecasting the movement of ash clouds. We conducted a sensitivity study to investigate the impact of PSD on model output and consider how best to apply default PSDs in operational dispersion modelling. Compiled grain size data confirm that, when considering particles likely to be in the distal ash cloud (< 125 µm diameter), magma composition and eruption size are the dominant controls on grain size distribution. Constraining the PSD is challenging but we find that the grain size of deposits from large hydromagmatic eruptions remains relatively constant with distance, suggesting that total (whole-deposit) grain size distributions (TGSDs) for these eruptions could be estimated from a few samples. We investigated the sensitivity of modelled ash mass loadings (in the air and on the ground) to input PSDs based on coarse to fine TGSDs from our dataset. We found clear differences between modelled mass loadings and the extent of the plume. Comparing TGSDs based on ground-only and ground-plus-satellite data for the Eyjafjallajökull 2010 eruption, we found that basing input PSDs on TGSDs from deposits alone (likely missing the finest particles) led to lower modelled peak ash concentrations and a smaller plume. |
format |
Text |
author |
Sara Osman Frances Beckett Alison Rust Eveanjelene Snee |
author_facet |
Sara Osman Frances Beckett Alison Rust Eveanjelene Snee |
author_sort |
Sara Osman |
title |
Sensitivity of Volcanic Ash Dispersion Modelling to Input Grain Size Distribution Based on Hydromagmatic and Magmatic Deposits |
title_short |
Sensitivity of Volcanic Ash Dispersion Modelling to Input Grain Size Distribution Based on Hydromagmatic and Magmatic Deposits |
title_full |
Sensitivity of Volcanic Ash Dispersion Modelling to Input Grain Size Distribution Based on Hydromagmatic and Magmatic Deposits |
title_fullStr |
Sensitivity of Volcanic Ash Dispersion Modelling to Input Grain Size Distribution Based on Hydromagmatic and Magmatic Deposits |
title_full_unstemmed |
Sensitivity of Volcanic Ash Dispersion Modelling to Input Grain Size Distribution Based on Hydromagmatic and Magmatic Deposits |
title_sort |
sensitivity of volcanic ash dispersion modelling to input grain size distribution based on hydromagmatic and magmatic deposits |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2020 |
url |
https://doi.org/10.3390/atmos11060567 |
op_coverage |
agris |
genre |
Eyjafjallajökull |
genre_facet |
Eyjafjallajökull |
op_source |
Atmosphere; Volume 11; Issue 6; Pages: 567 |
op_relation |
Air Quality https://dx.doi.org/10.3390/atmos11060567 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/atmos11060567 |
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Atmosphere |
container_volume |
11 |
container_issue |
6 |
container_start_page |
567 |
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