第197回 第2部

The Big Data Assimilation (BDA) project started in October 2013 and ended its 5.5-year period in March 2019. Here, we developed a novel numerical weather prediction (NWP) system at 100-m resolution updated every 30 seconds for precise prediction of individual convective clouds. This system was designed to fully take advantage of the phased array weather radar (PAWR) whose dense and frequent observing capability generates about 100-times bigger data than the regular parabolic antenna radar. By the end of the 5.5-year project period, we achieved less than 30-second computational time using the K computer for past cases with all input data such as boundary conditions and observation data being ready to use. The direct follow-on project started in April 2019 under the Japan Science and Technology Agency (JST) AIP (Advanced Intelligence Project) Acceleration Research. We continued the development to achieve real-time operations of this novel 30-second-update NWP system for demonstration at the time of the Tokyo 2020 Olympic and Paralympic games. The games were postponed, but the project achieved real-time demonstration of the 30-second-update NWP system at 500-m resolution using the Oakforest-PACS supercomputer. A real-time test was performed during July 31 and August 7, 2020 and resulted in the actual lead time of more than 27 minutes for 30-minute prediction with very few exceptions of extended delay. This presentation will summarize the real-time demonstration and provide future perspectives including AI-aided model acceleration for enhancing the system’s portability.