Author(s): Akira Tai; Tatsuya Oku; Akihiro Hashimoto; Hideo Oshikawa; Yuji Sugihara; Nobuhiro Matsunaga; Toshimitsu Komatsu
Linked Author(s): Akira Tai, Akihiro Hashimoto, Hideo Oshikawa
Keywords: Global warming; D4PDF; Model bias; Heavy rain; Kyushu Island
Abstract: According to the IPCC Fifth Assessment Report, the intensity and frequency of concentrated torrential rain due to global warming will increase. Since the increase in torrential rain is most likely to have a big influence on human society, high accuracy prediction is necessary. However, in the previous prediction da tabase, there are not enough ensemble number of the predictions for probabilist ic evaluation of the uncertainty associated with extreme weather. Therefore, in this study, I used a large scale ensemble climate prediction database d4PDF composed of numerous ensemble experiment data. By analyzing d4PDF, I attempted to ver ify the probabilist ic evaluation of future predictions and the changes of extreme weather which is low-frequency and local-scale events. I used the regional experimental results in d4PDF which covers the entire Japan. I analyzed the data for 2,500 years of past experimental data and the data for 5,400 years of the 4°C rise experiment data and the data for 3,240 years of the 2°C rise experiment data in Kyushu Island. About annual total precipitation, I compared real data with past experimental data and confirmed that the 1 hour precipitation has a bias in the model and the 48 hours precipitation has no model bias. For the probability evaluation of torrential rain in entire Kyushu, I used the general polar of distribution. The conclusion is that the total annual precipitation will increase in entire Kyushu due to the effect of global warming, and both the intensity and frequency of torrential rain will increase. In addition, about the change in torrential rain, there are regional differences in the change of torrential rain - the precipitation is relatively sma ll in the northern Kyushu, but it is large in the southern Kyushu.
Year: 2020