Abstract. We present the ashfall deposit and airborne ash concentration dataset from ash dispersal simulation of a large-scale explosive volcanic eruption as a reference for ashfall disaster countermeasure. We select the Taisho (1914) eruption in Sakurajima volcano, regarded as the strongest eruption in Japan in the last century, as our case study to provide a baseline for the worst-case scenario. We employ one eruption scenario approach by replicating the actual eruption under various extended weather conditions to show how it would affect contemporary Japan. Accumulated ashfall has devastating impacts on both surrounding areas of the volcano and other regions, affecting airline transportation, socio-economics activities, and human health. Therefore, it is crucial to discover places with a high probability of exposure to ashfall deposition. This knowledge can help assess the additional risk in the infrastructures, human lives, and economic impacts to make a better volcanic eruption response plan. We generate the ash dispersal dataset by simulating the ash transport of the Taisho eruption scenario with a volcanic ash dispersal model and meteorological reanalysis data for 64 years (1958–2021). We explain the dataset production process and provide the dataset in multiple formats for broader audiences. We also clarify the validity of the dataset with its limitations and uncertainties. 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 DOI: https://www.doi.org/10.17603/ds2-vw5f-t920 by selecting Version 2 (Rahadianto and Tatano, 2020).

中文翻译：

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用于应对灰烬灾害的樱岛大正喷发的长期灰烬扩散数据集

摘要。我们展示了一次大规模火山爆发的灰烬扩散模拟中的灰烬沉积物和空气中的灰烬浓度数据集，作为灰烬灾害对策的参考。我们选择樱岛火山的大正（1914）喷发，被认为是上个世纪日本最强烈的喷发，作为我们的案例研究，为最坏的情况提供基线。我们采用一种喷发情景方法，通过在各种扩展天气条件下复制实际喷发来展示它将如何影响当代日本。累积的灰烬对火山周边地区和其他地区造成毁灭性影响，影响航空运输、社会经济活动和人类健康。因此，发现有高概率接触灰烬沉积的地方至关重要。这些知识可以帮助评估基础设施、人类生活和经济影响方面的额外风险，以制定更好的火山喷发响应计划。我们通过使用火山灰扩散模型和 64 年（1958-2021 年）的气象再分析数据模拟大正喷发情景的灰烬迁移来生成灰烬扩散数据集。我们解释了数据集的制作过程，并为更广泛的受众提供了多种格式的数据集。我们还阐明了数据集的有效性及其局限性和不确定性。该数据集可在 DesignSafe-CI 数据仓库获得：https://www.designsafe-ci.org/data/browser/public/designsafe.storage.published/PRJ-2848v2 或通过 DOI：https://www。 doi.org/10.17603/ds2-vw5f-t920，选择版本 2（Rahadianto 和 Tatano，2020）。