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In this study, we use a long-term gridded dataset of daily precipitation and atmospheric fronts delineated on weather maps of Japan, the Northwestern Pacific, to identify rainfalls influenced by fronts within heavy rainfall periods occurring from June to August. We clarify the relationship between daily precipitation and the distance to fronts. The analytical targets are heavy rain events that occur for approximately four days each season. In the areas from Northwestern Kyushu to Western Tohoku, facing the Sea of Japan, the amount of precipitation from heavy rain events occurring within 500 km of fronts accounts for at least 80% of all heavy rain events. This is the same for the number of heavy rain events as well. Specifically, in Northwestern Kyushu, the amount of precipitation and the number of heavy rain events occurring within 200 km of fronts account for approximately 70% of all heavy rain events. [ABSTRACT FROM AUTHOR]

The estimation of extreme wind speeds, their directional variation, and potential future changes is essential for windresistant design and is possible using climate models. Accurate evaluations of local topographic winds such as downslope windstorms and gap winds require highresolution calculation and many ensemble years. However, few climate databases satisfy both requirements and none have been validated for extreme wind speeds. We assessed directional extreme wind speeds using a massive high-resolution ensemble climate dataset (d4PDF-5km-DS) for Hokkaido Island, Japan. Despite some issues due to limited reproducibility of spring extratropical cyclones, downslope windstorms caused by large mountains are reproduced well, indicating decreasing wind speed under predicted future climate. The findings suggest future climatic conditions may influence extreme topographic wind speeds. [ABSTRACT FROM AUTHOR]

This study investigates the change in extreme rainfall and river flooding for a large river basin due to climate change during the summer monsoon using a large ensemble dataset (d4PDF) coupled with the Integrated Flood Analysis System (IFAS). Frequent severe flooding causes significant damage in Japan. Therefore, we aim to provide useful information to mitigate flood damage. The study area is the Ishikari River basin (IRB) in Hokkaido, Japan. We used the d4PDF 5-km downscaled rainfall data as input for the IFAS model. The results showed that, for a given increase in extreme rainfall, the discharges from the IRB and its main sub-basins increase to a greater extent. The differences between the time of peak discharge at the reference stations in each tributary and the time of peak water level at the confluence points in the main river are evaluated. Climate change effects are significant in the southern sub-basins, wherein the amount of extreme rainfall increases by 29%- 35%, whereas the river discharge increases drastically (37%-56%). Additionally, the time difference decreases by 1.02-2.14 h. These findings will help policymakers develop future flood control measures in flood-prone areas. [ABSTRACT FROM AUTHOR]

Motivated by the problem of rainfall duration bias typically found in dynamical downscaling, its possible effect on hydrology was evaluated for heavy rainfall events over Kyushu, Japan, during summer. Heavy rainfall in western Kyushu is often related to a persistent Baiu rainband across Kyushu, while in eastern Kyushu it is related to the passage of typhoons near Kyushu. For typical heavy-rainfall periods, we ran a tank model for several target rivers to analyze runoff and water-depth sensitivity to the hyetograph by artificially extending the rainfall duration to 8 hours while maintaining the same total rainfall. This showed that a spike in peak runoff was suppressed by prolonged weak rainfall as typically found in downscaling outputs. The timing of rising runoff and water depth in the tank model was shifted earlier. [ABSTRACT FROM AUTHOR]