- 著者
- Noriko N. Ishizaki Motoki Nishimori Toshichika Iizumi Hideo Shiogama Naota Hanasaki Kiyoshi Takahashi
- 出版者
- Meteorological Society of Japan
- 雑誌
- SOLA (ISSN:13496476)
- 巻号頁・発行日
- vol.16, pp.80-85, 2020 (Released:2020-05-13)
- 参考文献数
- 25
- 被引用文献数
- 24
Bias corrected climate scenarios over Japan were developed using two distinct methods, namely, the cumulative distribution function-based downscaling method (CDFDM) and Gaussian-type Scaling approach (GSA). We compared spatial distribution, monthly variation, and future trends. The seasonal distribution of bias-corrected data using CDFDM closely followed the original general circulation model (GCM) outputs. GSA overestimated the amount of precipitation by 12-18% in every season because of an unsuitable assumption on the probability distribution. We also examined the contributions of each source of the uncertainty in daily temperature and precipitation indices. For daily temperature indices, GCM selection was the main source of uncertainty in the near future (2026-2050), while different Representative Concentration Pathways (RCPs) resulted in large variability at the end of the 21st century (2076-2100). We found large uncertainty using the bias-correction (BC) methods for daily precipitation indices even in the near future. Our results indicated that BC methods are an important source of uncertainty in climate risk assessments, especially for sectors where precipitation plays a dominant role. An appropriate choice of BC, or use of different BC methods, is encouraged for local mitigation and adaptation planning in addition to the use of different GCMs and RCPs.
- 著者
- Yasushi ISHIGOOKA Toshihiro HASEGAWA Tsuneo KUWAGATA Motoki NISHIMORI Hitomi WAKATSUKI
- 出版者
- The Society of Agricultural Meteorology of Japan
- 雑誌
- 農業気象 (ISSN:00218588)
- 巻号頁・発行日
- vol.77, no.2, pp.139-149, 2021 (Released:2021-04-10)
- 参考文献数
- 44
- 被引用文献数
- 15
Rice is the most important cereal crop in Japan, and therefore the impact of projected climate change on its production and quality has been assessed using rice growth models accounting for the effects of rising temperature and atmospheric CO2 concentration ([CO2]) on important growth processes. Recent experimental studies, however, have shown some negative effects of interactions between [CO2] and temperature on yield and quality of rice which were not accounted for by previous impact assessments. This study examined the importance of [CO2]×temperature interactions in the nationwide impacts of climate change on grain yield and quality of rice in Japan by 2100. We introduced new functions accounting for the effects of interactions on yield. Then we adopted the acceleration by elevated [CO2] in the estimation of the occurrence of chalky grains, an indicator of appearance quality of rice. We applied the modified model to Japan at a spatial resolution of 1 km using 10 climate scenarios (5 Global Circulation Models×2 representative concentration pathways [RCPs]) from 1981 to 2100. The effects of the newly introduced negative effects of [CO2]×temperature were evaluated by comparing simulations with and without the interaction in each scenario. Nationwide production was estimated to decrease by up to 28% and the percentage of white chalky grains to increase up to 16% relative to the previous assessment results, especially in RCP8.5, in which larger increases were projected in both temperature and [CO2]. The result suggests that the positive effect of elevated [CO2], which had been expected to offset the negative effect of increased temperature on rice productivity, may be limited in the future, and rice quality degradation may be more severe than predicted previously.
- 著者
- Noriko N. Ishizaki Motoki Nishimori Toshichika Iizumi Hideo Shiogama Naota Hanasaki Takahashi Kiyoshi
- 出版者
- Meteorological Society of Japan
- 雑誌
- SOLA (ISSN:13496476)
- 巻号頁・発行日
- pp.2020-014, (Released:2020-04-01)
- 被引用文献数
- 24
Bias corrected climate scenarios over Japan were developed using two distinct methods, namely, the cumulative distribution function-based downscaling method (CDFDM) and Gaussian-type Scaling approach (GSA). We compared spatial distribution, monthly variation, and future trends. The seasonal distribution of bias-corrected data using CDFDM closely followed the original general circulation model (GCM) outputs. GSA overestimated the amount of precipitation by 12-18% in every season because of an unsuitable assumption on the probability distribution. We also examined the contributions of each source of the uncertainty in daily temperature and precipitation indices. For daily temperature indices, GCM selection was the main source of uncertainty in the near future (2026-2050), while different Representative Concentration Pathways (RCPs) resulted in large variability at the end of the 21st century (2076-2100). We found large uncertainty using the bias-correction (BC) methods for daily precipitation indices even in the near future. Our results indicated that BC methods are an important source of uncertainty in climate risk assessments, especially for sectors where precipitation plays a dominant role. An appropriate choice of BC, or use of different BC methods, is encouraged for local mitigation and adaptation planning in addition to the use of different GCMs and RCPs.