使用大型集合数据的随机降水模型

IF 0.7 Q4 GEOSCIENCES, MULTIDISCIPLINARY Journal of Disaster Research Pub Date : 2023-12-01 DOI:10.20965/jdr.2023.p0868
Mizuki Shinohara, Masaru Inatsu
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引用次数: 0

摘要

建立了一个降水数据集,用于估算非寿险部门随机洪水风险评估的几千年再现期。将前人研究建立的自然灾害风险评估随机降水模型应用于大型集合数据。利用该模式分别获得了平均温度升高+2 K和+4 K对近期和未来气候的降水集合。我们成功创建了1万年的降水数据,这使得获得1000年的降水数据成为可能。
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Stochastic Precipitation Model Using Large Ensemble Data
A precipitation dataset is created to estimate a reproduction period of several thousand years for stochastic flood risk assessment in the non-life insurance sector. A stochastic precipitation model for natural hazard risk assessment developed in a previous study was applied to a large ensemble data. The model was used to obtain the precipitation ensembles for the recent and future climate by +2 K and +4 K increases in mean temperature, respectively. We successfully created 10,000 years of precipitation data, which makes it possible to obtain precipitation data over a 1,000-year return period.
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来源期刊
Journal of Disaster Research
Journal of Disaster Research GEOSCIENCES, MULTIDISCIPLINARY-
CiteScore
1.60
自引率
37.50%
发文量
113
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