Long-term ash dispersal dataset of the Sakurajima Taisho eruption for ashfall disaster countermeasure

Abstract

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).

Uncertainty Analysis of the Prediction of Massive Ash Fallout From a Large Explosive Eruption at Sakurajima Volcano

“…The westerlies are prevalent in Japan and affect the direction and velocity of the upper winds across the country. These winds are strongest in winter and weakest in summer, moving from the west throughout the year (Maeda et al., 2012; Rahadianto et al., 2022). Past reports and studies confirm that this cycle influences the trajectory of the ash deposition process during an eruption of Sakurajima volcano (Biass et al., 2017; Poulidis et al., 2018; Rahadianto et al., 2022).…”

“…This product was then directly compared to the ground report and found it to be in good agreement with historical records. Detailed explanations on the process for finding the dates with similar weather data can be found in the prior publication's appendix (Rahadianto et al., 2022).…”

“…and are relatively unaffected by the direct effects of ashfall, it is more advantageous to include prediction results with higher reliability. Furthermore, we also investigated how the meteorological trend affects the uncertainty, as wind conditions in Japan are influenced by seasonality (Biass et al, 2017;Poulidis et al, 2017Poulidis et al, , 2018Rahadianto et al, 2022) and extreme weather, such as typhoons and heavy rains.…”

“…The data set description and generation process are available in Rahadianto et al. (2022). Meanwhile, the simulation outputs for historical prediction data for all lead times are publicly available on Zenodo with Creative Commons Attribution 4.0 International Public License (Rahadianto & Tatano, 2023) and can be accessed by the DOI: https://doi.org/10.5281/zenodo.8112825.…”

“…Eruption Source Parameters Used as Input for the Simulations of Historical Ashfall Predictions(Rahadianto et al, 2022) …”