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Japan's new geostationary satellite Himawari-8, the first of a series of the third-generation geostationary meteorological satellites includingGOES-16, has been operational since July 2015. Himawari-8 produces highresolution observations with 16 frequency bands every 10 min for full disk, and every 2.5 min for local regions. This study aims to assimilate all-sky every-10-min infrared (IR) radiances from Himawari-8 with a regional numerical weather prediction model and to investigate its impact on real-world tropical cyclone (TC) analyses and forecasts for the first time. The results show that the assimilation of Himawari-8 IR radiances improves the analyzed TC structure in both inner-core and outer-rainband regions. The TC intensity forecasts are also improved due to Himawari-8 data because of the improved TC structure analysis. [ABSTRACT FROM AUTHOR]

With a goal of real-time, high-resolution, short-term prediction of heavy rainfall systems, the SCALE-LETKF was developed implementing the local ensemble transform Kalman filter with the Scalable Computing for Advanced Library and Environment-Regional Model (SCALE-RM). The system has been running in near real time experimentally since May 2015, configured for weather analyses and forecasts at 18-km resolution for a 5760×4320 km area around Japan. Among the data for more than one year, the near-real-time forecasts and the 3-km resolution downscaling simulations are demonstrated for a selected case of the September 2015 Kanto-Tohoku heavy rainfall associated with Typhoon Etau (2015). The typhoon track was successfully analyzed and predicted by the system, and the line-shaped rainband producing heavy rainfall can be reasonably forecasted by the downscaling simulation from the near-real-time data. [ABSTRACT FROM AUTHOR]

The Japan's Big Data Assimilation (BDA) project started in October 2013 and ends its 5.5-year period in March 2019. The BDA project aimed to fully take advantage of "big data" from advanced sensors such as the phased array weather radar (PAWR) and Himawari-8 geostationary satellite, which provide two orders of magnitude more data than the previous sensors. We have achieved successful case studies with newly-developed 30-second-update, 100-m-mesh numerical weather prediction (NWP) system based on RIKEN's SCALE model and local ensemble transform Kalman filter (LETKF) to assimilate PAWR in Osaka and Kobe. We achieved less than 20 seconds of the computer time using the Japan's "K" supercomputer for SCALE-LETKF at 250-m resolution, good for real-time 30-second forecast-analysis cycling. Compared with 100-m resolution, we found no clear forecast degradation at 250-m resolution. Also, we succeeded in assimilating Himawari-8 all-sky infrared radiances every 10 minutes effectively for strong typhoon and extreme-rain cases. This project also implemented a near-real-time SCALE-LETKF NWP system at 18-km resolution, producing 5-day forecasts every 4 times a day continuously. There was a record high precipitation event in early July 2018 over a broad area of western Japan, with more than 200 fatalities, the worst in the past 30 some years. The near-real-time prediction predicted well the extreme precipitation in this case. We have been investigating how effective the high-resolution, high-frequency NWP systems developed in the BDA project are for this historic disaster case. In this presentation, we will summarize what we have achieved in the past 5.5 years and will discuss our future perspectives based on the achievements. [ABSTRACT FROM AUTHOR]