Achievements in atmospheric sciences by the large-ensemble and high-resolution forecasting studies using the supercomputer Fugaku
Abstract This article reviews the outcomes of a three-year project utilizing "Fugaku," Japan's flagship supercomputer, to conduct high-resolution ensemble simulations using atmosphere or atmosphere–ocean coupled models for both the Japan region and the entire globe. The project name w...
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| Main Authors: | , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-08-01
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| Series: | Progress in Earth and Planetary Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40645-025-00730-6 |
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| Summary: | Abstract This article reviews the outcomes of a three-year project utilizing "Fugaku," Japan's flagship supercomputer, to conduct high-resolution ensemble simulations using atmosphere or atmosphere–ocean coupled models for both the Japan region and the entire globe. The project name was "Large Ensemble Atmospheric and Environmental Prediction for Disaster Prevention and Mitigation." The primary objective is to enhance the accuracy of numerical weather forecasting and provide probabilistic prediction information. To address the increasing severity of extreme weather events associated with global warming, such as torrential rainfall and tropical cyclones, high-resolution large-number ensemble atmospheric forecasting experiments have been conducted across timescales ranging from a few minutes to several weeks, extending to seasonal scales. This project aims to investigate advanced methodology using high-performance computing that provides probabilistic forecasts with sufficient lead time for effective disaster prevention and mitigation. Three sub-themes are explored: 1. meso-scale and regional modeling studies; 2. global and seasonal to sub-seasonal studies; and 3. innovative approaches to environmental studies. Central to this effort are high-resolution simulations that accurately represent cumulonimbus clouds and meso-scale systems, which are crucial for predicting severe weather phenomena alongside improved initial conditions derived from observational big data. These advancements are essential for predicting meteorological disasters caused by extreme events. Furthermore, the integration of probability information with improved accuracy significantly enhances disaster risk management, thereby increasing the practical utility of forecasts. This research also aims to develop pioneering innovative numerical weather and atmospheric environment forecasting technologies by incorporating big data from trace gas observations in addition to conventional meteorological data. |
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| ISSN: | 2197-4284 |