Prediction of Future Rainfall Variations after global warming in the Kyushu Island by Large Ensemble
Akira Tai, Tatsuya Oku, Yuji Sugihara, Nobuhiro Matsunaga and Toshimitsu Komatsu (Kyushu University, Japan)
Akihiro Hashimoto (Fukuoka University, Japan), Hideo Oshikawa (Saga University, Japan)
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According to the Intergovernmental Panel on
Climate Change (IPCC) Fifth Report, Humanand activity
continues to affect the Earth's energy budget throughchanges in land surface properties and changes inatmospheric concentrations caused by emissions ofgases and aerosols that are important in thermalradiation. Therefore, it is highly probable that extreme
rainfall will increase in the future. In order to evaluate theimpact of global warming on precipitation and toformulate efficient and effective flood adaptation
measures, it is essential to predict climate change andFigure 1. Analysis target area
quantitatively evaluate the uncertainties involved. The
recently developed ensemble climate prediction database (database for Policy Decision
making for Future climate change, hereafter d4PDF), which contributes to global warming
countermeasures, can statistically evaluate the frequency and intensity of precipitation by
performing a number of ensemble experiments. This study focuses on the Kyushu region(Figure 1), where many flood disasters have already occurred, and examines thecharacteristics of rainfall change after warming using d4PDF.

1. Verification of model bias

Data and method
d4PDF consists of a global experiment using the Meteorological Research Institute
Global Atmosphere Model MRI-AGCM3.2 with a horizontal resolution of about 60 km anda regional experiment using the Meteorological Research Institute Regional Climate
Model NHRCM with a horizontal resolution of about 20 km. In this study, analysis wasperformed using the results of the latter regional experiment covering Japan.
We used four datasets from d4PDF: (1) past experimental data (2500 years), (2)2 ℃ rise experiment data (3240 years), (3) 4 ℃ rise experiment data (5400 years), and(4) actual measurement data from the Meteorological Agency AMeDAS. The pastexperimental data is a data set obtained from experiments reproducing past climates, the4 ℃ rising experimental data is a data set obtained from experiments expressing aclimate in which the global average surface temperature rose 4 ℃ compared to before
the Industrial Revolution, The experimental data of 2 ℃ rise is a data set obtained froman experiment expressing a climate in which the global average surface temperaturerises 2 ℃ compared to before the Industrial Revolution.

Verification of model bias by creating a histogram of 1hour (5mm increments) and 48 hours annual maximum
precipitation (25mm increments) of d4PDF past experimental
data closest to each observation point at 92 points in theKyushu region was performed. As a result of verification at allpoints, it was thought that the trend was generally represented
in the Kyushu region, and only the result of Maehara, Fukuoka
prefecture is shown in Figure 2 and Figure 3. The line graphdrawn by the blue line shows the past experimental data, andthe bar graph drawn by the blue line shows the measured dataof the Japan Meteorological Agency. From Figure 2, it can beseen that 1 hour annual maximum precipitation differs greatly
between past experiments and measured data, and that themeasured data has higher intensity precipitation more
frequently. On the other hand, from Figure 3, it can be seen thatfor the 48 hours annual maximum rainfall, high intensity
precipitation occurs more frequently in the measured data, but
the bias is relatively small. In the future, it is necessary tocorrect the bias when assessing the specific flood risk.

past0.2

frequency

Results and discussions
observation

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00

10 20 30 40 50 60 70 80 90 100 110 120

precipitation (mm)Figure 2. 1-hour maximum
precipitation in Maebara
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past0.2

frequency

Introduction

observation

0.100100 200 300 400 500 600 700 800 900 1000

precipitation (mm)Figure 3. 48-hour maximum
precipitation in Maebara

2. Future change in annual maximum precipitation with a recurrence
interval of 50 years
By applying the Gev distribution
to all ensemble data at 176 points inthe target area, the spatial distribution
and change characteristics of theannual maximum rainfall at arecurrence interval of 50 years werev e r i f i e d . F r o m t h e r e s u l t s , t h e (a) Past experimental data (b) 2℃ experimental data (c) 4℃ experimental data
maximum rainfall for 1 hour and with Figure 4. Future change of 1-hour maximum precipitation
50-year probability was calculated.
Figure 4 (a), (b) and (c), it can be confirmed that as the global warming progresses, thecolor changes from cool to warm and the precipitation increases.

Conclusion✔The model bias was confirmed in d4PDF data by comparison with the measured data.
✔It was found that the annual maximum hourly rainfall increased throughout Kyushu as the temperature increased due to the effects of global warming.