Big Data Assimilation: Real-time 30-second-refresh Heavy Rain Forecast Using Fugaku During Tokyo Olympics and Paralympics

SC '23: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis(2023)

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摘要
Real-time 30-second-refresh numerical weather prediction (NWP) was performed with exclusive use of 11,580 nodes (~7%) of supercomputer Fugaku during Tokyo Olympics and Paralympics in 2021. Total 75,248 forecasts were disseminated in the 1-month period mostly stably with time-to-solution less than 3 minutes for 30-minute forecast. Japan's Big Data Assimilation (BDA) project developed the novel NWP system for precise prediction of hazardous rains toward solving the global climate crisis. Compared with typical 1-hour-refresh systems, the BDA system offered two orders of magnitude increase in problem size and revealed the effectiveness of 30-second refresh for highly nonlinear, rapidly evolving convective rains. To achieve the required time-to-solution for real-time 30-second refresh with high accuracy, the core BDA software incorporated single precision and enhanced parallel I/O with properly selected configurations of 1000 ensemble members and 500-m-mesh weather model. The massively parallel, I/O intensive real-time BDA computation demonstrated a promising future direction.
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关键词
Big Data,Heavy Rain,Data Assimilation,Tokyo Olympics,Precise Prediction,Problem Size,Exclusive Use,Real-time Estimation,Ensemble Members,Numerical Weather Prediction,1-month Period,Single Precision,Problem Size Increases,Data File,Risk Management,Real-world Applications,Refresh Rate,Real-time Prediction,Data Transfer,Ensemble Forecasts,Weather Radar,Time Stamp,Forecast Skill,Numerical Weather Prediction Models,Double Precision,Kalman Filter,Grid Spacing
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