Long-term ash dispersal dataset of the Sakurajima Taisho eruption for ashfall disaster countermeasure
<p>A large volcanic eruption can generate large amounts of ash which affect the socio-economic activities of surrounding areas, affecting airline transportation, socio-economics activities, and human health. Accumulated ashfall has devastating impacts on areas surrounding the volcano and in ot...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2022-12-01
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| Series: | Earth System Science Data |
| Online Access: | https://essd.copernicus.org/articles/14/5309/2022/essd-14-5309-2022.pdf |
| _version_ | 1798016282770014208 |
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| author | H. Rahadianto H. Rahadianto H. Tatano M. Iguchi H. L. Tanaka T. Takemi S. Roy |
| author_facet | H. Rahadianto H. Rahadianto H. Tatano M. Iguchi H. L. Tanaka T. Takemi S. Roy |
| author_sort | H. Rahadianto |
| collection | DOAJ |
| description | <p>A large volcanic eruption can generate large amounts of
ash which affect the socio-economic activities of surrounding areas,
affecting airline transportation, socio-economics activities, and human
health. Accumulated ashfall has devastating impacts on areas surrounding the
volcano and in other regions, and eruption scale and weather conditions may
escalate ashfall hazards to wider areas. It is crucial to discover places
with a high probability of exposure to ashfall deposition. Here, as a
reference for ashfall disaster countermeasures, we present a dataset
containing the estimated distributions of the ashfall deposit and airborne
ash concentration, obtained from a simulation of ash dispersal following a
large-scale explosive volcanic eruption. We selected the Taisho (1914)
eruption of the Sakurajima volcano, as our case study. This was the
strongest eruption in Japan in the last century, and our study provides a
baseline for a worst-case scenario. We employed one eruption scenario (OES)
approach by replicating the actual event under various extended weather
conditions to show how it would affect contemporary Japan. We generated an
ash dispersal dataset by simulating the ash transport of the Taisho eruption
scenario using a volcanic ash dispersal model and meteorological reanalysis
data for 64 years (1958–2021). We explain the dataset production and
provide the dataset in multiple formats for broader audiences. We examine
the validity of the dataset, its limitations, and its uncertainties.
Countermeasure strategies can be derived from this dataset to reduce
ashfall risk. The dataset is available at the DesignSafe-CI Data Depot:
<span class="uri">https://www.designsafe-ci.org/data/browser/public/designsafe.storage.published/PRJ-2848v2</span>
or through the following DOI: <a href="https://doi.org/10.17603/ds2-vw5f-t920">https://doi.org/10.17603/ds2-vw5f-t920</a>
by selecting Version 2 (Rahadianto and Tatano,
2020).</p> |
| first_indexed | 2024-04-11T15:48:28Z |
| format | Article |
| id | doaj.art-c8bd17b1cfaa4bdaa08bc27309476164 |
| institution | Directory Open Access Journal |
| issn | 1866-3508 1866-3516 |
| language | English |
| last_indexed | 2024-04-11T15:48:28Z |
| publishDate | 2022-12-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Earth System Science Data |
| spelling | doaj.art-c8bd17b1cfaa4bdaa08bc273094761642022-12-22T04:15:28ZengCopernicus PublicationsEarth System Science Data1866-35081866-35162022-12-01145309533210.5194/essd-14-5309-2022Long-term ash dispersal dataset of the Sakurajima Taisho eruption for ashfall disaster countermeasureH. Rahadianto0H. Rahadianto1H. Tatano2M. Iguchi3H. L. Tanaka4T. Takemi5S. Roy6Department of Social Informatics, Graduate School of Informatics, Kyoto University, Kyoto 606-8501, JapanDisaster Prevention Research Institute, Kyoto University, Uji 611-0011, JapanDisaster Prevention Research Institute, Kyoto University, Uji 611-0011, JapanSakurajima Volcano Research Center, Disaster Prevention Research Institute, Kyoto University, Sakurajima 851-1419, JapanCenter for Computational Sciences, Division of Global Environmental Science, University of Tsukuba, Ibaraki 305-8577, JapanDisaster Prevention Research Institute, Kyoto University, Uji 611-0011, JapanDepartment of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247-667, India<p>A large volcanic eruption can generate large amounts of ash which affect the socio-economic activities of surrounding areas, affecting airline transportation, socio-economics activities, and human health. Accumulated ashfall has devastating impacts on areas surrounding the volcano and in other regions, and eruption scale and weather conditions may escalate ashfall hazards to wider areas. It is crucial to discover places with a high probability of exposure to ashfall deposition. Here, as a reference for ashfall disaster countermeasures, we present a dataset containing the estimated distributions of the ashfall deposit and airborne ash concentration, obtained from a simulation of ash dispersal following a large-scale explosive volcanic eruption. We selected the Taisho (1914) eruption of the Sakurajima volcano, as our case study. This was the strongest eruption in Japan in the last century, and our study provides a baseline for a worst-case scenario. We employed one eruption scenario (OES) approach by replicating the actual event under various extended weather conditions to show how it would affect contemporary Japan. We generated an ash dispersal dataset by simulating the ash transport of the Taisho eruption scenario using a volcanic ash dispersal model and meteorological reanalysis data for 64 years (1958–2021). We explain the dataset production and provide the dataset in multiple formats for broader audiences. We examine the validity of the dataset, its limitations, and its uncertainties. Countermeasure strategies can be derived from this dataset to reduce ashfall risk. The dataset is available at the DesignSafe-CI Data Depot: <span class="uri">https://www.designsafe-ci.org/data/browser/public/designsafe.storage.published/PRJ-2848v2</span> or through the following DOI: <a href="https://doi.org/10.17603/ds2-vw5f-t920">https://doi.org/10.17603/ds2-vw5f-t920</a> by selecting Version 2 (Rahadianto and Tatano, 2020).</p>https://essd.copernicus.org/articles/14/5309/2022/essd-14-5309-2022.pdf |
| spellingShingle | H. Rahadianto H. Rahadianto H. Tatano M. Iguchi H. L. Tanaka T. Takemi S. Roy Long-term ash dispersal dataset of the Sakurajima Taisho eruption for ashfall disaster countermeasure Earth System Science Data |
| title | Long-term ash dispersal dataset of the Sakurajima Taisho eruption for ashfall disaster countermeasure |
| title_full | Long-term ash dispersal dataset of the Sakurajima Taisho eruption for ashfall disaster countermeasure |
| title_fullStr | Long-term ash dispersal dataset of the Sakurajima Taisho eruption for ashfall disaster countermeasure |
| title_full_unstemmed | Long-term ash dispersal dataset of the Sakurajima Taisho eruption for ashfall disaster countermeasure |
| title_short | Long-term ash dispersal dataset of the Sakurajima Taisho eruption for ashfall disaster countermeasure |
| title_sort | long term ash dispersal dataset of the sakurajima taisho eruption for ashfall disaster countermeasure |
| url | https://essd.copernicus.org/articles/14/5309/2022/essd-14-5309-2022.pdf |
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