- 著者
- Hideo Shiogama Noriko N. Ishizaki Naota Hanasaki Kiyoshi Takahashi Seita Emori Rui Ito Toshiyuki Nakaegawa Izuru Takayabu Yasuaki Hijioka Yukari N. Takayabu Ryosuke Shibuya
- 出版者
- Meteorological Society of Japan
- 雑誌
- SOLA (ISSN:13496476)
- 巻号頁・発行日
- vol.17, pp.57-62, 2021 (Released:2021-04-03)
- 参考文献数
- 20
- 被引用文献数
- 1 18
Climate change impact assessment studies often use future projections of only a few global climate models (GCMs) due to limited research resources. Here we develop a novel method to select a small subset of GCMs that widely capture the uncertainty range of large ensemble. By applying this method, we select a subset of five GCM projections from the Coupled Model Intercomparison Project Phase 6 (CMIP6) ensemble for impact and adaptation studies in Japan. At first, we omit GCMs whose global warming projections have been evaluated to be overestimated in the recent literature. Then, we select a subset of five GCMs that widely captures the uncertainty ranges for 8 climate variables and have good performances in present-climate simulations. These selected GCM simulations will be used to provide better climate scenarios for impact and adaptation studies than those in the previous impact assessment project.
- 著者
- Hideo Shiogama Noriko N. Ishizaki Naota Hanasaki Kiyoshi Takahashi Seita Emori Rui Ito Toshiyuki Nakaegawa Izuru Takayabu Yasuaki Hijioka Yukari N. Takayabu Ryosuke Shibuya
- 出版者
- Meteorological Society of Japan
- 雑誌
- SOLA (ISSN:13496476)
- 巻号頁・発行日
- pp.2021-009, (Released:2021-02-16)
- 被引用文献数
- 18
Climate change impact assessment studies often use future projections of only a few global climate models (GCMs) due to limited research resources. Here we develop a novel method to select a small subset of GCMs that widely capture the uncertainty range of large ensemble. By applying this method, we select a subset of five GCM projections from the Coupled Model Intercomparison Project Phase 6 (CMIP6) ensemble for impact and adaptation studies in Japan. At first, we omit GCMs whose global warming projections have been evaluated to be overestimated in the recent literature. Then, we select a subset of five GCMs that widely captures the uncertainty ranges for 8 climate variables and have good performances in present-climate simulations. These selected GCM simulations will be used to provide better climate scenarios for impact and adaptation studies than those in the previous impact assessment project.