Achievements in 2026
Peer-reviewed papers
- 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
- 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
- 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
- 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
- Konduru, R. T., Liang, J., 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
- 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
