- 著者
- 
             
             Hideo Shiogama
             
             Yukiko Imada
             
             Masato Mori
             
             Ryo Mizuta
             
             Dáithí Stone
             
             Kohei Yoshida
             
             Osamu Arakawa
             
             Mikiko Ikeda
             
             Chiharu Takahashi
             
             Miki Arai
             
             Masayoshi Ishii
             
             Masahiro Watanabe
             
             Masahide Kimoto
             
          
- 出版者
- (公社)日本気象学会
- 雑誌
- SOLA (ISSN:13496476)
- 巻号頁・発行日
- vol.12, pp.225-231, 2016 (Released:2016-08-07)
- 参考文献数
- 37
- 被引用文献数
- 
             
             4
             
             
             25
             
             
          
        
        We describe two unprecedented large (100-member), long-term (61-year) ensembles based on MRI-AGCM3.2, which were driven by historical and non-warming climate forcing. These ensembles comprise the “Database for Policy Decision making for Future climate change (d4PDF)”. We compare these ensembles to large ensembles based on another climate model, as well as to observed data, to investigate the influence of anthropogenic activities on historical changes in the numbers of record-breaking events, including: the annual coldest daily minimum temperature (TNn), the annual warmest daily maximum temperature (TXx) and the annual most intense daily precipitation event (Rx1day). These two climate model ensembles indicate that human activity has already had statistically significant impacts on the number of record-breaking extreme events worldwide mainly in the Northern Hemisphere land. Specifically, human activities have altered the likelihood that a wider area globally would suffer record-breaking TNn, TXx and Rx1day events than that observed over the 2001-2010 period by a factor of at least 0.6, 5.4 and 1.3, respectively. However, we also find that the estimated spatial patterns and amplitudes of anthropogenic impacts on the probabilities of record-breaking events are sensitive to the climate model and/or natural-world boundary conditions used in the attribution studies.