We have been developing the SCALE-LETKF system, utilizing a regional weather model known as the Scalable Computing for Advanced Library and Environment-Regional Model (SCALE-RM) and an ensemble data assimilation method known as the Local Ensemble Transform Kalman Filter (LETKF). The primary goal of the system is to make use of observational data obtained from an advanced weather radar, the Phased Array Weather Radar (PAWR), in numerical weather prediction (NWP). This new type of weather radar can observe heavy precipitation systems densely both in space and in time, providing an important data source for advanced weather monitoring; however, its effective use in high-resolution NWP is a frontier research topic. We investigate this rapid-update, high-resolution data assimilation problem using the SCALE-LETKF. We have also been applying the SCALE-LETKF system for an experimental near-real-time NWP system in Japan and surrounding area. We run 5-day weather forecast for this area every 6 hours in near real time using the K computer. This has been running stably and has provided important guidance on the performance of the model and the data assimilation settings. In addition, this talk will also discuss about the computational aspect of the SCALE-LETKF development and some ongoing issues and prospects of the system.