- 著者
- Hideo Shiogama Rui Ito Yukiko Imada Toshiyuki Nakaegawa Nagio Hirota Noriko N. Ishizaki Kiyoshi Takahashi Izuru Takayabu Seita Emori
- 出版者
- Meteorological Society of Japan
- 雑誌
- SOLA (ISSN:13496476)
- 巻号頁・発行日
- vol.16, pp.75-79, 2020 (Released:2020-05-01)
- 参考文献数
- 22
- 被引用文献数
- 7
The ensemble average projections of the Coupled Model Inter-comparison Project Phase 5 (CMIP5) ensemble show future increases in shortwave radiation at the surface (SW) in Japan. We reveal that the Arctic Oscillation-like atmospheric circulation trends cause cloud cover decreases around Japan, leading to increases in the SW.In many cases, impact assessment studies use the outputs of only a few models due to limited research resources. We find that the four climate models used in the Japanese multisector impact assessment project, S-8, do not sufficiently capture the uncertainty ranges of the CMIP5 ensemble regarding the SW projections. Therefore, the impact assessments using the SW of these four models can be biased. We develop a novel method to select a better subset of models that are more widely distributed and are not biased, unlike the S-8 models.
- 著者
- Hideo Shiogama Rui Ito Yukiko Imada Toshiyuki Nakaegawa Nagio Hirota Noriko N. Ishizaki Kiyoshi Takahashi Izuru Takayabu Seita Emori
- 出版者
- Meteorological Society of Japan
- 雑誌
- SOLA (ISSN:13496476)
- 巻号頁・発行日
- pp.2020-013, (Released:2020-03-30)
- 被引用文献数
- 7
The ensemble average projections of the Coupled Model Inter-comparison Project Phase 5 (CMIP5) ensemble show future increases in shortwave radiation at the surface (SW) in Japan. We reveal that the Arctic Oscillation-like atmospheric circulation trends cause cloud cover decreases around Japan, leading to increases in the SW. In many cases, impact assessment studies use the outputs of only a few models due to limited research resources. We find that the four climate models used in the Japanese multisector impact assessment project, S-8, do not sufficiently capture the uncertainty ranges of the CMIP5 ensemble regarding the SW projections. Therefore, the impact assessments using the SW of these four models can be biased. We develop a novel method to select a better subset of models that are more widely distributed and are not biased, unlike the S-8 models.