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Akihiko Murata, Shun-ichi I. Watanabe, Hidetaka Sasaki, Hiroaki Kawase, and Masaya Nosaka


Goodness of fit in daily precipitation frequency to a gamma distribution was examined, focusing on adverse effects originating from the shortage of sampled tropical cyclones, using precipitation data with and without the influence of tropical cyclones. The data used in this study were obtained through rain gauge observations and regional climate model simulations under the RCP8.5 scenario and the present climate. An empirical cumulative distribution function (CDF), calculated from a sample of precipitation data for each location, was compared with a theoretical CDF derived from two parameters of a gamma distribution. Using these two CDFs, the root-mean-square error (RMSE) was calculated as an indicator of the goodness of fit. The RMSE exhibited a decreasing tendency when the influence of tropical cyclones was removed. This means that the empirical CDF derived from sampled precipitation more closely resembled the theoretical CDF when compared with the relationship between empirical and theoretical CDFs, including precipitation data associated with tropical cyclones. Future changes in the two parameters of the gamma distribution, without the influence of tropical cyclones, depend on regions in Japan, indicating a regional dependence on changes in the shape and scale of the CDF. The magnitude of increases in no-rain days was also dependent on regions of Japan, although the number of no-rain days increased overall. This simplified approach is useful for analyzing climate change from a broad perspective.

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Hiroaki Kawase, Yukiko Imada, Hiroshige Tsuguti, Toshiyuki Nakaegawa, Naoko Seino, Akihiko Murata, and Izuru Takayabu
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Ryo Mizuta, Akihiko Murata, Masayoshi Ishii, Hideo Shiogama, Kenshi Hibino, Nobuhito Mori, Osamu Arakawa, Yukiko Imada, Kohei Yoshida, Toshinori Aoyagi, Hiroaki Kawase, Masato Mori, Yasuko Okada, Tomoya Shimura, Toshiharu Nagatomo, Mikiko Ikeda, Hirokazu Endo, Masaya Nosaka, Miki Arai, Chiharu Takahashi, Kenji Tanaka, Tetsuya Takemi, Yasuto Tachikawa, Khujanazarov Temur, Youichi Kamae, Masahiro Watanabe, Hidetaka Sasaki, Akio Kitoh, Izuru Takayabu, Eiichi Nakakita, and Masahide Kimoto


An unprecedentedly large ensemble of climate simulations with a 60-km atmospheric general circulation model and dynamical downscaling with a 20-km regional climate model has been performed to obtain probabilistic future projections of low-frequency local-scale events. The climate of the latter half of the twentieth century, the climate 4 K warmer than the preindustrial climate, and the climate of the latter half of the twentieth century without historical trends associated with the anthropogenic effect are each simulated for more than 5,000 years. From large ensemble simulations, probabilistic future changes in extreme events are available directly without using any statistical models. The atmospheric models are highly skillful in representing localized extreme events, such as heavy precipitation and tropical cyclones. Moreover, mean climate changes in the models are consistent with those in phase 5 of the Coupled Model Intercomparison Project (CMIP5) ensembles. Therefore, the results enable the assessment of probabilistic change in localized severe events that have large uncertainty from internal variability. The simulation outputs are open to the public as a database called “Database for Policy Decision Making for Future Climate Change” (d4PDF), which is intended to be utilized for impact assessment studies and adaptation planning for global warming.

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