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In this talk, we review our achievement in regional-scale data assimilation with Himawari-8 satellite radiances. In July 2015, the Japan Meteorological Agency (JMA) started full operations of their new geostationary satellite “Himawari-8”, the first of a series of the third-generation geostationary meteorological satellites. Himawari-8 can produce high-resolution observations with 16 frequency bands every 10 minutes for full disk. To assimilate Himawari-8 radiances, we implemented a radiative transfer model into a regional-scale data assimilation system known as SCALE-LETKF, consists of the Scalable Computing for Advanced Library and Environment-Regional Model (SCALE-RM) and the Local Ensemble Transform Kalman Filter (LETKF). We assimilated all-sky every-10-minute infrared (IR) radiances from Himawari-8. The results showed that assimilating the every-10-minute Himawari-8 IR radiances improves the analyzed tropical cyclone (TC) structure and intensity forecasts. In another case in September 2015, the heavy precipitation forecasts are greatly improved by assimilating the Himawari-8 IR observations. We ran a rainfall-runoff model using the improved precipitation forecasts and found that assimilating the Himawari-8 observations frequently may give longer lead times in terms of the flood risk. We also show other case studies on a different TC case and the extremely-heavy precipitation event in July 2018.