Availability of Newly Developled Reginal Climate Data for Improving Reproducibility of Extreme Events

Accurate prediction of extreme weather information is crucial for disaster risk management, social and economic development security, and climate change research. However, state-of-the-art regional climate models still have difficulties in simulating extreme weather such as extreme precipitation. In order to take appropriate measures to reduce the risk of water-related disasters, which are expected to become more severe with climate change, there is an urgent need to develop technologies that can accurately represent predict localized weather patterns by regional weather models.

We have investigated the predictability of extreme rainfall event in Japan with utilizing two global reanalysis products (JRA-55, ERA-5) which are widely used in regional weather modelling studies. As compared total precipitation on two reanalysis products with observation data, the results indicated that JRA-55 tended to overestimate daily precipitation whereas ERA-5 tended to underestimate it. In this presentation, we utilized newly developed high-resolution regional atmospheric reanalysis for Japan, called as RRJ-ClimCORE (Nakamura et al., 2022) to be compared with two global products to clarify the predictability of summertime extreme rainfall events in regional weather models.