JAXAスーパーコンピュータシステム利用成果報告(2025年2月～2026年1月)

報告書番号: R25JR0201

利用分野: 宇宙技術

PDF(準備中)

• 責任者: 落合治, 第一宇宙技術部門地球観測研究センター
• 問い合せ先: 第一宇宙技術部門 地球観測研究センター 久保田 拓志(kubota.takuji@jaxa.jp)
• メンバ: 吉岡真由美, 佐藤 正樹, 大石俊, 三好 建正, 小槻 峻司, 山本 晃輔, 久保田 拓志

事業概要

GSMaP, GPM/DPRやその他の衛星観測データを, 先端的のアンサンブルデータ同化手法により数値天気予報モデルに取り込み, 大気客観解析及びこれを初期値とした予報に改善をもたらすと共に, 衛星観測データと数値モデルの双方を活かした新たな降水プロダクトNEXRA(NICAM-LETKF JAXA Research Analysis)を作成する.

参照URL

https://www.eorc.jaxa.jp/theme/NEXRA/index_j.htm 参照.

JAXAスーパーコンピュータを使用する理由と利点

本研究では, 全球大気データ同化システム(NICAM-LETKF)による衛星観測データ同化及び予測計算を行うが, 大規模な全球大気モデル計算, 及び, アンサンブルデータ同化を行うために, JSS3は必須である.

今年度の成果

昨年度開発されたNEXRA3を引き続きJSS3上で運用し, 予報実験の結果をWebサイト「JAXA Realtime weather watch」(https://www.eorc.jaxa.jp/theme/NEXRA/index_j.htm) 上での公開を継続した. 先行するNEXRA2からモデル解像度を上げたNEXRA3についての性能比較を学術論文SOLAに報告した(Matsugishi et al., 2025). NEXRA3システムを利用し, 2025年夏季の線状降水事例の再現実験を行い解析中である. これまでの蓄積として公開したNEXRA2解析プロダクトのデータの後継としてNEXRA3の計算結果を使った解析プロダクトをデータセットとして公開するため検討を行い, 整備を進めている.

成果の公表

-査読付き論文

- Almeida, A. P., H. M. J. Barbosa, S. R. Garcia, D. J. Gagne, K. Zhou, T. Kubota, T. Ushio, S. Otsuka, S. Pfreundschuh, and A. J. P. Calheiros, 2026: A regional benchmark for deep learning-based hourly precipitation nowcasting in Latin America. IEEE Access, doi:10.1109/ACCESS.2026.3670767 (accepted).

- Amemiya, A., and T. Miyoshi, 2026: Impact of reduced non-Gaussianity on analysis and forecast accuracy by assimilating every-30 s radar observation with ensemble Kalman filter: Idealized experiments of deep convection. Nonlin. Processes Geophys., 33, 1-16, https://doi.org/10.5194/npg-33-1-2026

- Chang, C., B. Mu, W. Han, Y. Ham, G. J. Zhang, A. Damiani, F. Ling, and T. Miyoshi, 2025: AI weather and climate prediction and applications. Bull. Amer. Meteor. Soc., 106, E2571-E2578, https://doi.org/10.1175/BAMS-D-25-0260.1

- Guerrieri, J. M., M. Pulido, T. Miyoshi, A. Amemiya, and J. J. Ruiz, 2026: Localization in the mapping particle filter. Nonlin. Processes Geophys., 33, 33-49, https://doi.org/10.5194/npg-33-33-2026

- Hascoet, T., V. Pellet, S. Oishi, and T. Miyoshi, 2026: Differentiable river routing for end-to-end learning of hydrological processes. J. Geophys. Res.: Machine Learning and Computation, 3, e2025JH000760, https://doi.org/10.1029/2025JH000760

- Huo, Z., Y. Liu, J. Taylor, Y. Zhou, A. Amemiya, H. Fan, and T. Miyoshi, 2025: Incremental analysis updates in a convective-scale ensemble Kalman filter using minute-by-minute phased array radar observations. J. Adv. Model. Earth Syst., 17, e2024MS004802, https://doi.org/10.1029/2024MS004802

- Konduru, R. T., R. Bale, M. Tsubokura, and T. Miyoshi, 2025: Transforming urban wind engineering by taming extreme weather strong winds over urban skylines with ultra-high-resolution simulations on supercomputer Fugaku. Proc. Supercomputing Asia Conf. (SCA '25), 79-87, https://doi.org/10.1145/3718350.3718353

- Konduru, R. T., J. Liang, S. Otsuka, and T. Miyoshi, 2026: Observing systems simulation experiments of hypothetical hourly global coverage of microwave satellite radiances: Imbalance and adaptive observation error inflation. J. Geophys. Res. Atmos., in press.

- Kotsuki, S., K. Shiraishi, and A. Okazaki, 2025: Ensemble data assimilation to diagnose AI-based weather prediction models: A case with ClimaX version 0.3.1. Geosci. Model Dev., 18, 7215-7225, https://doi.org/10.5194/gmd-18-7215-2025

- Matsugishi, S., Y.-W. Chen, K. Terasaki, H. Yashiro, S. Kotsuki, K. Kanemaru, K. Yamamoto, M. Satoh, T. Kubota, and T. Miyoshi, 2025: Intercomparison of NICAM-LETKF JAXA research analysis (NEXRA) version 2 and 3. SOLA, https://doi.org/10.2151/sola.2025-035

- Matsugishi, S., Y.-W. Chen, K. Terasaki, K. Kanemaru, S. Kotsuki, H. Yashiro, K. Yamamoto, M. Satoh, T. Kubota, and T. Miyoshi, 2025: NICAM-LETKF JAXA research analysis (NEXRA) version 2.0. Geosci. Data J., 12, e70011, https://doi.org/10.1002/gdj3.70011

- Miyoshi, T., 2026: A duality principle for chaotic systems: From data assimilation to efficient control. Nonlinear Dyn., 114, 105, https://doi.org/10.1007/s11071-025-12021-2

- Mulia, I., U. Shimada, N. Ueda, T. Miyoshi, and M. Maulana, 2025: Multi-horizon prediction of tropical cyclone intensity and its interpretability with temporal fusion transformer. Sci. Rep., 15, https://doi.org/10.1038/s41598-025-15522-7

- Ohishi, S., Y. Kobayashi, and T. Miyoshi, 2025: Including cross correlation between forecast and observation errors in an ensemble Kalman filter. Mon. Wea. Rev., 153, 1035-1043, https://doi.org/10.1175/MWR-D-25-0016.1

- Ohishi, S., T. Miyoshi, and M. Kachi, 2025: Deterministic and ensemble forecasts of the Kuroshio south of Japan. Ocean Dyn., 75, 92, https://doi.org/10.1007/s10236-025-01736-w

- Satoh, M., T. Kawabata, T. Miyakawa, M. Nakano, H. Yashiro, T. Miyoshi, L. Duc, P.-Y. Wu, T. Oizumi, Y. Maejima, J. Taylor, R. Yoshimura, K. Terasaki, Y. Yamada, R. Masunaga, T. Kawasaki, and M. Tanoue, 2025: Achievements in atmospheric sciences by the large-ensemble and high-resolution forecasting studies using the supercomputer Fugaku. Prog. Earth Planet. Sci., 12, 64, https://doi.org/10.1186/s40645-025-00730-6

- 齋藤成津美, 塩尻大也, 小槻峻司 (2025): 拡散モデルにより生成される領域降水量アンサンブルの統計的検証. AI・データサイエンス論文集, 6(3), 489-496. doi:10.11532/jsceiii.6.3_489

-招待講演

- 2025/4/9 Miyoshi, Takemasa; Otsuka, Shigenori; Liang, Jianyu; Goodliff, Michael; Saliou, Gwendal; Ouala, Said; Tandeo, Pierre, RIKEN's activities to integrate DA and AI/ML, Workshop on data assimilation: Initial conditions and beyond, Part of ECMWF's 50th anniversary celebrations, Germany, Bonn

- 2025/5/6 Miyoshi, Takemasa, RIKEN's activities to integrate data assimilation and AI/ML, Meteorological-Geophysical Colloquium, Austria, Vienna

- 2025/5/14 Miyoshi, Takemasa, RIKEN's activities to integrate data assimilation and AI/ML, Seminar (DWD), Germany, Offenbach

- 2025/5/16 Miyoshi, Takemasa, RIKEN's activities to integrate data assimilation and AI/ML, SFB-Seminar, Germany, Potsdam

- 2025/5/25 Otsuka Shigenori, Global precipitation nowcasting with ConvLSTM and adversarial training, Japan Geoscience Union Meeting 2025, Japan, Chiba

- 2025/6/13 Miyoshi, Takemasa, Big Data Assimilation Revolutionizing Numerical Weather Prediction Using Fugaku, SEMINAIRE Sciences du climat, France, Paris

- 2025/6/18 Miyoshi, Takemasa, Big Data Assimilation - Revolutionizing Weather Prediction, Seminar (Department of Physics and Astronomy "Augusto Righi"), Italy, Bologna

- 2025/7/28 Takemasa Miyoshi, RIKEN's activities to integrate data assimilation and AI/ML, AOGS 2025, Singapore

- 2025/8/7 Miyoshi, Takemasa, Forging the Future of Weather Prediction: From Supercomputers to Societal Impact, CONAGUA2025, Argentina, Buenos Aires

- 2025/10/14 三好建正, AIxデータ同化:大阪・関西万博会場周辺のゲリラ豪雨予報から将来展望へ, CEATEC'2025, 幕張

- 2025/11/16 Miyoshi, Takemasa, From Gordon Bell Finalist to the Osaka Expo: The Evolution of Real-Time Forecasting on Fugaku, SC25, United States, St. Louis

- 2025/11/29 佐藤正樹, 2025: 全球ストーム解像モデルと地球観測衛星との連携研究. 千葉大学環境リモートセンシング研究センター創立30周年記念式, 千葉

- 2025/12/25 三好建正, 「富岳」が捉えた万博のゲリラ豪雨, 第5回スーパーコンピュータ「富岳」成果創出加速プログラム・政策対応利用課題シンポジウム「富岳百景」, オンライン

- 2026/1/26 Otsuka Shigenori, Rapid-update precipitation predictions with HPC and AI, SupercomputingAsia 2026/The International Conference on High Performance Computing in Asia-Pacific Region 2026, Japan, Osaka

- 2026/2/19 三好建正, ビッグデータ同化:ゲリラ豪雨予測から気象制御への挑戦, 第10回気象ビジネスフォーラム～AIと気象ビジネス～, 東京

- 2026/3/6 Takemasa Miyoshi, "Osaka Expo 2025 Weather on Fugaku: Synergizing Big Data Assimilation and AI", JAMSTEC International Weather and Climate Modeling(IWCM) Workshop 2026, Yokohama

-口頭発表

- 2025/4/27 Miyoshi, Takemasa; Otsuka, Shigenori; Liang, Jianyu; Goodliff, Michael; Saliou, Gwendal; Ouala, Said; Tandeo, Pierre, RIKEN's activities to integrate DA and AI/ML, EGU2025, Austria, Vienna

- 2025/5/13 Miyoshi, Takemasa, Can we control chaotic extreme weather? -- what we learned from Japan's moonshot program, Meteorological Colloquium, Germany, Munich

- 2025/5/25 Miyoshi, Takemasa; Ohishi, Shun; Liang, Jianyu; Goodliff, Michael; Otsuka, Shigenori; Tomita, Hirofumi; Kanemaru, Kaya; Yashiro, Hisashi; Terasaki, Koji; Okamoto, Kozo; Kotsuki, Shunji; Matsugishi, Shuhei; Satoh, Masaki; Bishop, Craig; Kubota, Takuji; Kachi, Misako, Advancement and AI integration of satellite data assimilation of clouds, precipitation, and the ocean, Japan Geoscience Union Meeting 2025, Japan, Chiba

- 2025/6/23 Goodliff Michael, Using Data Assimilation to Improve Data Driven Surrogate Models, IMT-Atlantique & RIKEN joint Data Assimilation workshop, France, Brest

- 2025/6/26 Tarumi Yuta, Deep Bayesian Filter for SPEEDY, an Intermediate-Complexity Atmospheric GCM, IMT-Atlantique & RIKEN joint Data Assimilation workshop, France, Brest

- 2025/6/26 Otsuka Shigenori, Data-driven approaches for precipitation nowcasting, IMT-Atlantique & RIKEN joint Data Assimilation workshop, France, Brest

- 2025/7/28 Goodliff Michael, Using Data Assimilation To Improve Data-driven Models, AOGS 2025, Singapore

- 2025/8/18 Miyoshi, Takemasa, Big Data Assimilation Revolutionizing Numerical Weather Prediction Using Fugaku, IA CORRIENTES, TECH WEEK, Argentina, Corrientes

- 2025/8/22 Miyoshi, Takemasa, How a Breakthrough in Chaos Theory Inspired a National Mission to Control Extreme Weather, Ciclo de Charlas de Actualizacion y Divulgacion Cientifica, Tecnologica y de Innovacion, Argentina, Corrientes

- 2025/9/29 Miyoshi, Takemasa, Chaos implies effective controllability but only after the predictability limit, ISDA2025, Australia, Melbourne

- 2025/9/29 Goodliff Michael, Impacts of Model Errors on Convergence of Iterative Data Driven Model Refinement with Data Assimilation, 11th International Symposium for Data Assimilation, Australia, Melbourne

- 2025/9/29 Tarumi Yuta, Deep Bayesian Filtering for High-Dimensional Atmospheric Models - Scalable Data Assimilation with SPEEDY, 11th International Symposium on Data Assimilation, Australia, Melbourne

- 2025/10/5 Miyoshi, Takemasa, Big data assimilation for weather prediction, 65th ISI World Statistics Congress, Netherlands, Hague

- 2025/10/20 Miyoshi, Takemasa, Advancement and AI integration of satellite data assimilation of clouds, precipitation and the ocean, FY2025 The Joint PI Meeting of JAXA Earth Observation Missions, Japan, Tokyo

- 2025/10/23 三好建正, マルチスケール極端気象予測を目指した「ビッグデータ同化」とAIの融合研究, 第12 回「富岳」を中核とするHPCI システム利用研究課題成果報告会, 東京

- 2025/10/27 Goodliff Michael, Using Data Assimilation to Improve Data-Driven Models, AIP CREST Challenge Meeting, Japan, Tokyo

- 2025/10/27 Otsuka Shigenori, ConvLSTMと敵対的学習を用いた全球降水ナウキャスト, 第01回地球科学におけるAI応用研究ワークショップ, 金沢市

- 2025/11/4 三好建正, カオスによる予測可能性限界と制御可能性, 日本気象学会2025年度秋季大会, 福岡

- 2025/11/17 Miyoshi, Takemasa; Otsuka, Shigenori; Liang, Jianyu; Goodliff, Michael; Tarumi, Yuta; Saliou, Gwendal; Ouala, Said; Tandeo, Pierre, RIKEN's activities to integrate data assimilation and AI/ML, WS on NHM 2025, Japan, Morioka

- 2025/11/20 Ohishi Shun, LETKF-based Ocean Research Analysis (LORA) for a quasi-global domain, The Joint PI Meeting of JAXA Earth Observation Missions FY2025, Japan, Tokyo

- 2025/12/15 Miyoshi, Takemasa, Harnessing the Butterfly Effect: A Duality-Based Framework for the Efficient Control of Extreme Weather, AGU2025, United States, New Orleans

- 2025/12/15 Miyoshi, Takemasa; Otsuka, Shigenori; Liang, Jianyu; Goodliff, Michael; Tarumi, Yuta; Saliou, Gwendal; Ouala, Said; Tandeo, Pierre, RIKEN's activities to integrate data assimilation and AI/ML, AGU25, United States, New Orleans

- 2026/1/25 Miyoshi, Takemasa; Otsuka, Shigenori; Liang, Jianyu; Goodliff, Michael; Tarumi, Yuta; Saliou, Gwendal; Ouala, Said; Tandeo, Pierre, Riken's Activities to Integrate Data Assimilation and AI/ML, AMS2026, 106th annual meeting, United States, Houston

- 2026/2/18-20 寺崎康児, 新しいNICAM-LETKFフレームワークの開発, NICAM開発者会議2025

- 2026/2/22 Ohishi Shun, Deterministic and ensemble forecasts of Kuroshio south of Japan, Ocean Sciences Meeting 2026, United Kingdom, Scotland

-ポスター

- 2025/5/25 Miyoshi, Takemasa; Ohishi, Shun; Tomita, Hirofumi; Taylor, James; Goodliff, Michael; Liang, Jianyu; Konduru, Rakesh Teja; Satoh, Masaki; Matsugishi, Shuhei; Kotsuki, Shunji; Okazaki, Atsushi; Honda, Takumi; Okamoto, Kozo; Ikuta, Yasutaka; Terasaki, Koji; Yashiro, Hisashi; Kanemaru, Kaya; Yamazaki, Akira, A platform to design and pre-evaluate frequent satellite observing systems for innovating weather, ocean and land surface prediction, Japan Geoscience Union Meeting 2025, Japan, Chiba

- 2025/5/25 Ohishi Shun, Intercomparison and Ensemble of Coastal Ocean Prediction Models in Japan: A Case Study in the Goto-nada, Japan Geoscience Union Meeting 2025, Japan, Chiba

- 2025/5/25 Goodliff Michael, Using Data Assimilation to Improve Data-Driven Models, JpGU 2025, Japan, Chiba

- 2025/7/6 Tarumi Yuta, Deep Bayesian Filter for Bayes-Faithful Data Assimilation, International Conference on Machine Learning, Canada, Vancouver

- 2025/7/20 Ohishi Shun, Intercomparison and Ensemble of Coastal Ocean Prediction Models in Japan: A Case Study in the Goto-nada, Busan IAMAS-IACS-IAPSO Joint Assembly 2025, Korea, Busan

- 2025/11/25 Goodliff Michael, Using Data Assimilation to Improve Data-Driven Models, International Workshop on Hydrometeorological Predictions, Japan, Kobe

- 2025/11/25 Ohishi Shun, Deterministic and Ensemble forecasts of Kuroshio south of Japan, International Workshop on Hydrometeorological Predictions, Japan, Kobe

- 2025/12/8 Ohishi Shun, LETKF-based Ocean Research Analysis for a quasi-global domain, ハビタブル日本全体会議, 広島市

- 2025/12/22 Otsuka Shigenori, Global precipitation nowcasting using a ConvLSTM with adversarial training, RIKEN-Nagoya Univ. (Zhang - Sogabe Lab) Joint Workshop on Prediction Science, Japan, Nagoya

- 2026/1/26 Unashish Mondal, Evaluation of EarthCARE Cloud Profiling Radar Observations with a 3.5-km-Resolution NICAM Simulation, SCA/HPCAsia 2026, Japan, Osaka

- 2026/1/26 Tarumi Yuta, Deep Bayesian Filter for SPEEDY: an Intermediate-Complexity Atmospheric Circulation Model, SCA/HPCAsia 2026, Japan, Osaka

- 2026/1/26 Goodliff Michael, Using Data Assimilation to Improve Data-Driven Models, SCA/HPC Asia 2026, Japan, Osaka

- 2026/1/26 Ohishi Shun, Development of an ensemble ocean data assimilation system, SCA/HPCAsia 2026, Japan, Osaka

- 2026/1/26 Otsuka Shigenori, Global precipitation nowcasting with ConvLSTM and adversarial training, SupercomputingAsia 2026/The International Conference on High Performance Computing in Asia-Pacific Region 2026, Japan, Osaka

- 2026/1/26 Unashish Mondal, Evaluation of EarthCARE Cloud Profiling Radar Observations with a 3.5-km-Resolution NICAM Simulation, SCA/HPCASIA 2026, Japan, Osaka

- 2026/2/5 Goodliff Michael, Using Data Assimilation to Improve Data-Driven Models, RIKEN-Fudan University joint workshop on atmospheric science, DA and ML, Japan, Kobe

- 2026/3/2 Goodliff Michael, Comparing Ensemble Data Assimilation and Variational Data Assimilation Methods for Data-Driven Surrogate Model Generation, AIP Challenge Meeting, Japan, Tokyo

-その他

JAXA Visualizing our Earth from Space (JAXA「地球が見える」記事:「宇宙から天気をもっと正確に!ー「世界の気象リアルタイムNEXRA3」がリニューアル, 新旧システムの性能比較(論文解説)」)

JSS利用状況

計算情報

• プロセス並列手法: MPI
• スレッド並列手法: OpenMP
• プロセス並列数: 4 - 1024
• 1ケースあたりの経過時間: 30 分

JSS3利用量

総資源に占める利用割合※1(%): 1.21

内訳

JSS3のシステム構成や主要な仕様は、JSS3のシステム構成をご覧下さい。

※1 総資源に占める利用割合：3つの資源(計算, ファイルシステム, アーカイバ)の利用割合の加重平均.

※2 資源の利用割合：対象資源一年間の総利用量に対する利用割合.

ISV利用量

※2 資源の利用割合：対象資源一年間の総利用量に対する利用割合.

JAXAスーパーコンピュータシステム利用成果報告(2025年2月～2026年1月)