Data Assimilation Research Team Achievements

Peer-reviewed papers

1. Tonoyama, S. K., A. Suzuki, T. Miyoshi, 2026: A variational approach to estimating the state of a magma reservoir from observed displacement, JSIAM letter (accepted)
2. G. Ogita, T. Miyoshi, and T. Shibata 2026: Kalman-filter Force Inference: an estimation framework for cellular forces from temporal evolution of epithelial morphogenesis, Journal of the Royal Society Interface 23, 240, doi.org/10.1098/rsif.2026.0017.
3. S. K. Tonoyama, and A. W. Woods 2026: Experiments on entrainment and mixing in particle-driven gravity currents, J. Fluid Mech., in press.
4. K. Takeda, and T. Miyoshi 2026: Noise-scaled accuracy of the ensemble Kalman filter with an instability-based minimum ensemble size, Nonlinear Processes in Geophysics 33, 335, doi.org/10.5194/npg-33-335-2026.
5. Arcucci, R., Healy, S., Dance, S., T. Miyoshi , et al, 2026: The convergence of machine learning and data assimilation in Earth system science. npj Artif. Intell. 2, 48, doi.org/10.1038/s44387-026-00107-0
6. Amemiya, A. and T. Miyoshi, 2026: Impact of reduced non-Gaussianity on analysis and forecast accuracy by assimilating every-30s radar observation with ensemble Kalman filter: idealized experiments of deep convection, Nonlinear Processes in Geophysics, 33, 1-16, doi:10.5194/npg-33-1-2026
7. Miyoshi, T., 2026: A duality principle for chaotic systems: from data assimilation to efficient control, Nonlinear Dyn., 114, 105, doi:10.1007/s11071-025-12021-2
8. 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, doi:10.1029/2025JH000760
9. Guerrieri, J. M., M. Pulido, T. Miyoshi, A. Amemiya, and J. J. Ruiz, 2026: Localization in the mapping particle filter, Nonlinear Processes in Geophysics, 33, 33-49, doi:10.5194/npg-33-33-2026
10. 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. - Atmosphere, 131, e2025JD044041, doi.org:10.1029/2025JD044041
11. Almeida, A. P., H. M. J. Barbosa, M. J. Henrique, 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, 14, 38306-38331, doi:10.1109/ACCESS.2026.3670767
12. Fujisawa, Y., S. Murakami, N. Sugimoto, N. Komori, M. Takagi, T. Imamura, T. Horinouchi, G. L. Hashimoto, M. Ishiwatari, T. Enomoto, T. Miyoshi, H. Kashimura, and Y.-Y. Hayashi, 2026: ALERA-V version 1.0: an objective analysis dataset of the Venus atmosphere, Geoscience Data Journal, 13, e70080, doi:10.1002/gdj3.70080
13. Taylor, J., A. Amemiya, T. Honda, S. Otsuka, Y. Maejima, and T. Miyoshi, 2026: Rapid 30-second-update numerical nowcasting with multi-parameter phased array radar observations: skill comparison with an advection model, SOLA, 22, 29 (2026), doi:10.1007/s44393-026-00032-0

Invited Presentations

1. Takemasa Miyoshi: Harnessing the Butterfly Effect: A Duality-Based Framework for the Efficient Control of Extreme Weather, EGU General Assembly 2026, Vienna, Austria, May 4, 2026
2. Takemasa Miyoshi: From Real-Time Big Data Assimilation on Fugaku to Synergistic Development of DA and AI: Osaka Expo 2025 and Beyond, 5th ECMWF-ESA Machine Learning Workshop, Bologna, Italy, April 16, 2026
3. Shigenori Otsuka, Takemasa Miyoshi: Rapid-update precipitation predictions with HPC and AI, SupercomputingAsia 2026 / The International Conference on High Performance Computing in Asia-Pacific Region 2026, Osaka, Japan, January 26, 2026
4. Takemasa Miyoshi: 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～, Tokyo, Japan, February 19, 2026
5. Tatsuro Iwanaka, Takeshi Imamura, Shohei Aoki, Hideo Sagawa: 金星大気の物質循環, 惑星圏シンポジウム2026, Sendai, Japan, March 2, 2026
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, Japan, March 6, 2026

Honors and Awards