ABSTRACT This study investigates the applicability of a stochastic typhoon model, STM, for probabilistic forecasting of storm surge induced by a typhoon. When a typhoon forms and approaches the coast, the present STM generates a number of virtual typhoons with initial conditions specified by the recent history of the actual typhoon. Storm surge is then computed for each of the generated typhoons, and the probabilistic characteristics of the estimated storm surges are investigated. The present STM is based on the higher-order autoregressive model, which can account for the history of the characteristics of individual typhoons. The concept of minimal pressure was introduced to improve the predictive skills of the statistical characteristics of extreme typhoons. The model was applied to the cases of Typhoons Jebi and Trami, which hit Japan in 2018. The present system reasonably explained the contrasting characteristics of Jebi and Trami in terms of their peak storm surge levels in the inner part of Osaka Bay. Furthermore, the sensitivity analysis of the present probabilistic forecasting system suggested that a relatively large number of virtual typhoons are needed for forecasting of the worst storm surge conditions induced by the arbitrary actual typhoons approaching the target coast.

中文翻译：

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随机台风模型在台风诱发风暴潮概率预报中的适用性研究

摘要 本研究调查了随机台风模型 STM 在台风引起的风暴潮的概率预测中的适用性。当台风形成并接近海岸时，当前的 STM 会生成许多虚拟台风，其初始条件由实际台风的最近历史指定。然后为每个产生的台风计算风暴潮，并调查估计风暴潮的概率特征。目前的STM基于高阶自回归模型，可以解释单个台风的历史特征。引入最小压力的概念是为了提高对极端台风统计特征的预测能力。该模型应用于 2018 年袭击日本的台风飞燕和特拉米的案例。目前的系统合理地解释了飞燕和特拉米在大阪湾内部的峰值风暴潮水平的对比特征。此外，现有概率预报系统的敏感性分析表明，对于任意接近目标海岸的实际台风引起的最恶劣风暴潮情况的预报，需要相对大量的虚拟台风。