62 Years Simulated Sakurajima Taisho Eruption Ashfall Deposit Data (1958-2019)

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. Please select the Version 2 of the dataset for the latest update.

本文发布一套基于大规模爆炸性火山喷发火山灰扩散模拟（ash dispersal simulation）得到的火山灰沉降物（ashfall deposit）与大气火山灰浓度（airborne ash concentration）数据集，为火山灰沉降灾害应对提供参考依据。本研究选取被认为是日本上个世纪最强喷发的樱岛火山大正（1914）喷发作为案例研究，为极端喷发情景构建基准参照。本研究采用单一喷发情景建模方法，在多种扩展气象条件下复刻该实际喷发过程，以展示其对当代日本的潜在影响。累计火山灰沉降会对火山周边及其他区域造成毁灭性影响，波及航空运输、社会经济活动与人体健康。因此，识别高火山灰沉降暴露概率的区域至关重要。依托该数据集的相关信息，可评估基础设施、人员生命与经济层面的附加风险，进而制定更完善的火山喷发应对预案。本研究通过火山灰扩散模型（volcanic ash dispersal model）与1958-2021年共64年的气象再分析数据，模拟大正喷发情景下的火山灰运移过程，进而生成该火山灰扩散数据集（ash dispersal dataset）。本文详细说明了该数据集的制作流程，并以多格式发布该数据集，以覆盖更广泛的用户群体。同时，本文阐明了该数据集的有效性，并明确了其存在的局限性与不确定性。如需获取最新版本，请选用该数据集的V2版本。