Achievements in 2024

Peer-reviewed papers

  1. Terasaki, K. and T. Miyoshi, 2024: Including the horizontal observation error correlation in the ensemble Kalman filter: idealized experiments with NICAM-LETKF. Mon. Wea. Rev., 152, 277-293. doi:10.1175/MWR-D-23-0053.1
  2. Liang, J., N. Sugimoto, and T. Miyoshi, 2024: Analyzing the Instabilities in the Venus Atmosphere Using Bred Vectors. Journal of Geophysical Research: Planets, 129, e2023JE008067. doi:10.1029/10.1029/2023JE008067
  3. Ohishi, S., T. Miyoshi, and M. Kachi, 2024: Impact of atmospheric forcing on SST in the LETKF-based ocean research analysis (LORA), Ocean Modelling, 189, 102357. doi:10.1016/j.ocemod.2024.102357
  4. Takeda, K., S. Kaji, and T. Miyoshi, 2024: Topological regularization on numerical simulations of the advection equation, JSIAM Letters, 16, 53-56. doi:10.14495/jsiaml.16.53
  5. Furukawa, K., H. Sakamoto, M. Ohhigashi, S. Shima, T. Sluka, and T. Miyoshi, 2024: Particle filter data assimilation for ubiquitous unstable trajectories of two-dimensional three-state cellular automata. Nonlinear Dyn., doi:10.1007/s11071-024-09803-5
  6. Ohishi, S., T. Miyoshi, T. Ando, T. Higashiuwatoko, E. Yoshizawa, H. Murakami, and M. Kachi, 2024: LETKF-based Ocean Research Analysis (LORA) version 1.0, Geoscience Data Journal, 11, 995-1006. doi:10.1002/gdj3.271
  7. Takeda, K., and T. Sakajo, 2024: Uniform error bounds of the ensemble transform Kalman filter for chaotic dynamics with multiplicative covariance inflation, SIAM/ASA Journal on Uncertainty Quantification, 12(4), 1315-1335. doi:10.1137/24M1637192
  8. Li, L., J. Li, and T. Miyoshi, 2024: Chaos suppression through Chaos enhancement, Nonlinear Dyn., doi:10.1007/s11071-024-10426-z

Invited Presentations

  1. K. Furukawa, Well-Posedness of One-Dimensional Drift-Diffusion Equations under Dynamic Conditions and the Fourth Boundary Condition, The 25th Northeastern Symposium on Mathematical Analysis, Hokkaido University, Sapporo, February 20, 2024
  2. Takemasa Miyoshi, Advances and applications of satellite data assimilation of clouds, precipitation, and the ocean, DA Forum by University of Melbourne, Bureau of Meteorology, Melbourne, Australia, March 15, 2024
  3. Takemasa Miyoshi, Tokyo Olympics/Paralympics forecast experiment with phased array weather radar, Deepdive session at IMT Atlantique, Brest, France, April 3, 2024
  4. Takemasa Miyoshi, Every 30-second Phased Array Radar Data Assimilation Proven Effective for Short-range Convective Weather Forecast, 8th WMO Workshop on the Impact of Various Observing Systems on Numerical Weather Prediction and Earth System Prediction, Norrköping, Sweden, May 28, 2024, Keynote
  5. Takemasa Miyoshi, Big Data Assimilation: Real-time 30-Second-Refresh Heavy Rain Forecast Using Fugaku during Tokyo Olympics and Paralympics, Central Weather Administration, Chinese Taipei, June 18, 2024
  6. Takemasa Miyoshi, Toward next 100 years of data assimilation and numerical weather prediction, MSROC Centennial Celebration and Symposium, Central Weather Administration, Chinese Taipei, June 19, 2024, Keynote
  7. Takemasa Miyoshi, Big Data Assimilation Revolutionizing Numerical Weather Prediction Using Fugaku, 24th International Conference on Computational Science (ICCS2024), Malaga, Spain, July 2, 2024, Keynote

Honors and Awards

  1. Yasumitsu Maejima: RIKEN Oubu Research Incentive Award, Observing System Simulation Experiments of a Rich Phased Array Weather Radar Network Covering Kyushu for the July 2020 Heavy Rainfall Event, 12th March 2024.

Working with us

Please contact us if you are interested in working on cutting-edge data assimilation research.

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Data Assimilation Research Team

7-1-26, Minatojima-minami-machi, Chuo-ku, Kobe, Hyogo 650-0047, Japan
RIKEN Center for Computational Science (R-CCS) Data Assimilation Research Team

E-mail: da-team-desk(please remove here)@ml.riken.jp

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