Open AccessOver 5,000 Years of Ensemble Future Climate Simulations by 60-km Global and 20-km Regional Atmospheric Models
Author(s) -
Ryo Mizuta,
Akihiko Murata,
Masayoshi Ishii,
Hideo Shiogama,
Kenshi Hibino,
Nobuhito Mori,
Osamu Arakawa,
Yukiko Imada,
Kohei Yoshida,
Toshio Aoyagi,
Hiroaki Kawase,
Masato Mori,
Y. Okada,
Tomoya Shimura,
Toshiharu Nagatomo,
Mikiko Ikeda,
Hirokazu Endo,
Masaya Nosaka,
Miki Arai,
Chiharu Takahashi,
Kenji Tanaka,
Tetsuya Takemi,
Yasuto Tachikawa,
Temur Khujanazarov,
Youichi Kamae,
Masahiro Watanabe,
Hirokazu Sasaki,
Akio Kitoh,
Izuru Takayabu,
Eiichi Nakakita,
Masahide Kimoto
Publication year - 2017
Publication title -
bulletin of the american meteorological society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.367
H-Index - 197
eISSN - 1520-0477
pISSN - 0003-0007
DOI - 10.1175/bams-d-16-0099.1
Subject(s) - downscaling , coupled model intercomparison project , climatology , climate model , environmental science , probabilistic logic , climate change , precipitation , general circulation model , statistical model , meteorology , geography , computer science , geology , oceanography , artificial intelligence , machine learning
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.