Article ; Online: Long-term ash dispersal dataset of the Sakurajima Taisho eruption for ashfall disaster countermeasure
Earth System Science Data, Vol 14, Pp 5309-
2022 Volume 5332
Abstract: 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 ... ...
| Abstract | 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: https://www.designsafe-ci.org/data/browser/public/designsafe.storage.published/PRJ-2848v2 or through the following DOI: https://doi.org/10.17603/ds2-vw5f-t920 by selecting Version 2 (Rahadianto and Tatano, 2020). |
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| Keywords | Environmental sciences ; GE1-350 ; Geology ; QE1-996.5 |
| Subject code | 333 |
| Language | English |
| Publishing date | 2022-12-01T00:00:00Z |
| Publisher | Copernicus Publications |
| Document type | Article ; Online |
| Database | BASE - Bielefeld Academic Search Engine (life sciences selection) |
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