Research for data assimilation of satellite global rainfall map
JAXA Supercomputer System Annual Report February 2025-January 2026
Report Number: R25ER0201
Subject Category: Space Technology
- Responsible Representative: Osamu Ochiai, Director, Space technology Directorate I, Earth Observation Research Center
- Contact Information: Space technology Directorate I, Earth Observation Research Center, Takuji Kubota(kubota.takuji@jaxa.jp)
- Members: Mayumi Yoshioka, Masaki Satoh, Shun Ohishi, Takemasa Miyoshi, Shunji Kotsuki, Kosuke Yamamoto, Takuji Kubota
Abstract
This study explores an effective use of satellite data including GSMaP and GPM/DPR through an advanced ensemble data assimilation method for improving numerical weather prediction (NWP) and pioneering a new precipitation product based on an NWP model and satellite observations, named as NICAM-LETKF JAXA Research Analysis (NEXRA).
Reference URL
Please refer to https://www.eorc.jaxa.jp/theme/NEXRA/index_e.htm .
Reasons and benefits of using JAXA Supercomputer System
In this study, the JSS3 is used for the NICAM-LETKF experiments to assimilate satellite observations and to conduct NWP model forecasts. The JSS3 is an essential infrastructure for our study to conduct massive computations for the ensemble-based data assimilation and ensemble atmospheric simulations.
Achievements of the Year
The NEXRA3 system developed in FY2024 was continuously operated on JSS3, and the results of the forecast experiments have been continuously visualized and published on the JAXA Realtime Weather Watch website (https://www.eorc.jaxa.jp/theme/NEXRA/index_j.htm). The letter reporting a performance comparison between NEXRA3 performed at a higher resolution and the preceding NEXRA2 system was published in the journal Scientific Online Letters on the Atmosphere (SOLA) (Matsugishi et al. 2025).
Using the NEXRA3 system, hindcast experiments for line-shaped precipitation events that occurred during the summer of 2025 were conducted, and analyses are currently underway.
The NEXRA2 analysis products produced by continuous forecast experiments have been released. As a successor dataset, new analysis products based on NEXRA3 simulation results are being prepared for public release in FY2026.
Publications
- Peer-reviewed papers
- 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
- Invited Presentations
- 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
- 2025/11/16 Miyoshi, Takemasa, From Gordon Bell Finalist to the Osaka Expo: The Evolution of Real-Time Forecasting on Fugaku, SC25, United States, St. Louis
- 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
- 2026/3/6 Takemasa Miyoshi, "Osaka Expo 2025 Weather on Fugaku: Synergizing Big Data Assimilation and AI", JAMSTEC International Weather and Climate Modeling(IWCM) Workshop 2026, Yokohama
- Oral Presentations
- 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
- 2025/10/27 Goodliff Michael, Using Data Assimilation to Improve Data-Driven Models, AIP CREST Challenge Meeting, Japan, Tokyo
- 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
- 2026/2/22 Ohishi Shun, Deterministic and ensemble forecasts of Kuroshio south of Japan, Ocean Sciences Meeting 2026, United Kingdom, Scotland
- Poster Presentations
- 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
- 2025/12/22 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
Usage of JSS
Computational Information
- Process Parallelization Methods: MPI
- Thread Parallelization Methods: OpenMP
- Number of Processes: 4 - 1024
- Elapsed Time per Case: 30 Minute(s)
JSS3 Resources Used
Fraction of Usage in Total Resources*1(%): 1.21
Details
Please refer to System Configuration of JSS3 for the system configuration and major specifications of JSS3.
| System Name | CPU Resources Used(Core x Hours) | Fraction of Usage*2(%) |
|---|---|---|
| TOKI-SORA | 31384456.57 | 1.42 |
| TOKI-ST | 45.56 | 0.00 |
| TOKI-GP | 0.00 | 0.00 |
| TOKI-XM | 0.00 | 0.00 |
| TOKI-LM | 0.00 | 0.00 |
| TOKI-TST | 14.93 | 0.00 |
| TOKI-TGP | 0.00 | 0.00 |
| TOKI-TLM | 0.00 | 0.00 |
| File System Name | Storage Assigned(GiB) | Fraction of Usage*2(%) |
|---|---|---|
| /home | 2048.00 | 3.28 |
| /data and /data2 | 307200.00 | 2.02 |
| /ssd | 61440.00 | 3.73 |
| Archiver Name | Storage Used(TiB) | Fraction of Usage*2(%) |
|---|---|---|
| J-SPACE | 123.18 | 0.37 |
*1: Fraction of Usage in Total Resources: Weighted average of three resource types (Computing, File System, and Archiver).
*2: Fraction of Usage：Percentage of usage relative to each resource used in one year.
ISV Software Licenses Used
| ISV Software Licenses Used(Hours) | Fraction of Usage*2(%) | |
|---|---|---|
| ISV Software Licenses(Total) | 0.00 | 0.00 |
*2: Fraction of Usage：Percentage of usage relative to each resource used in one year.
JAXA Supercomputer System Annual Report February 2025-January 2026