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Title
Japanese: 
English:A 0.01-degree gridded precipitation dataset for Japan, 1926-2020 
Author
Japanese: 鳩野 美佐子, 木口 雅司, 芳村 圭, 鼎 信次郎, 蔵治 光一郎, 沖 大幹.  
English: Misako Hatono, Masashi Kiguchi, Kei Yoshimura, Shinjiro Kanae, Koichiro Kuraji, Taikan Oki.  
Language English 
Journal/Book name
Japanese: 
English:Scientific Data 
Volume, Number, Page 9        422
Published date July 19, 2022 
Publisher
Japanese: 
English:Nature Publishing Group UK 
Conference name
Japanese: 
English: 
Conference site
Japanese: 
English: 
Official URL https://www.nature.com/articles/s41597-022-01548-3
 
Abstract We developed a 0.01-degree gridded precipitation dataset of Japan based on historical observation datasets covering 1926 to 2020. Historical observations conducted by the Japan Meteorological Agency and other Japanese bureaucratic agencies were spatially interpolated using the inverse distance weighting method at daily and hourly temporal resolutions. Optimal parameterization for our interpolation process was selected by comparing interpolated results of various parameter combinations with precipitation observation conducted by the University of Tokyo Forests. We conducted cross-validation for over 1,000 stations with sufficient data throughout our data period and verified our product can reproduce the temporal variability of local precipitation. The strong points of our precipitation dataset are its high spatiotemporal resolution and the abundance of point precipitation source data. We expect our dataset to be highly relevant to various future studies as it can serve multiple purposes such as forcing data for hydrological models or a database for analyzing the characteristics of historical rainfall events.

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