RIKEN Center for Computational Science Data Assimilation Research Team
Team Leader: Takemasa Miyoshi (Ph.D.)
Research Summary

Data assimilation (DA) is a cross-disciplinary science to synergize computer simulations and real-world data, using statistical methods and applied mathematics. As computers become more powerful and enable more precise simulations, it will become more important to compare the simulations with actual observations. DA Team performs cutting-edge research and development on advanced DA methods and their wide applications, aiming to integrate computer simulations and real-world data in the wisest way. Particularly, DA Team tackles challenging problems of developing efficient and accurate DA systems for “big simulations” with real-world “big data” from various sources including advanced sensors. The specific foci include 1) theoretical and algorithmic developments for efficient and accurate DA, 2) DA methods and applications by taking advantage of the world-leading supercomputer and “big data” from new advanced sensors, and 3) exploratory new applications of DA in wider simulation fields. These advanced DA studies will enhance simulation capabilities and lead to a better use of high-performance computers.
Main Research Fields
- Mathematical & Physical Sciences
Related Research Fields
- Informatics
Keywords
- Data Assimilation
- Numerical Weather Prediction
- Large Scale Simulation
- Ensemble Data Assimilation
- Natural disaster prediction
Research Subjects
- Ensemble-based data assimilation suitable to various high-dimensional simulations
- Theoretical research on challenging problems in data assimilation
- Wide applications of data assimilation
- Cutting-edge data assimilation research on geophysical applications
- Data assimilation using Big Data
Selected Publications
- 1.
H. Yashiro, K. Terasaki, Y. Kawai, S. Kudo, T. Miyoshi, T. Imamura, K. Minami, H. Inoue, T. Nishiki, T. Saji, M. Satoh, and H. Tomita
"A 1024-Member Ensemble Data Assimilation with 3.5-Km Mesh Global Weather Simulations"
in SC20: International Conference for High Performance Computing, Networking, Storage and Analysis (SC), Atlanta, GA, US, pp. 1-10. (2020). - 2.
Kotsuki, S., Pensoneault, A., Okazaki, A. and Miyoshi, T.
"Weight Structure of the Local Ensemble Transform Kalman Filter: A Case with an Intermediate AGCM."
Q. J. R. Meteorol. Soc., 146, Issue732, 3399-3415. (2020). - 3.
Otsuka, S., S. Kotsuki, M. Ohhigashi, and T. Miyoshi
"GSMaP RIKEN Nowcast: Global precipitation nowcasting with data assimilation"
J. Meteor. Soc. Japan, 97, 1099-1117. (2019). - 4.
Honda, T., S. Kotsuki, G.-Y. Lien, Y. Maejima, K. Okamoto and T. Miyoshi
"Assimilation of Himawari-8 All-Sky Radiances Every 10 Minutes: Impact on Precipitation and Flood Risk Prediction"
J. Geophys. Res., 123, 965-976 (2018). - 5.
Kotsuki, S., T. Miyoshi, K. Terasaki, G.-Y. Lien and E. Kalnay
"Assimilating the Global Satellite Mapping of Precipitation Data with the Nonhydrostatic Icosahedral Atmospheric Model NICAM"
J. Geophys. Res., 122, 631-650 (2017). - 6.
Arakida, H., T. Miyoshi, T. Ise, S. Shima and S. Kotsuki
"Non-Gaussian data assimilation of satellite-based Leaf Area Index observations with an individual-based dynamic global vegetation model"
Nonlinear Processes in Geophys., 24, 553-567 (2017). - 7.
Miyoshi, T., G.-Y. Lien, S. Satoh, T. Ushio, K. Bessho, H. Tomita, S. Nishizawa, R. Yoshida, S. A. Adachi, J. Liao, B. Gerofi, Y. Ishikawa, M. Kunii, J. Ruiz, Y. Maejima, S. Otsuka, M. Otsuka, K. Okamoto, and H. Seko
""Big Data Assimilation" toward Post-peta-scale Severe Weather Prediction: An Overview and Progress"
Proc. of the IEEE, 104, 2155-2179 (2016). - 8.
Miyoshi, T., M. Kunii, J. Ruiz, G.-Y. Lien, S. Satoh, T. Ushio, K. Bessho, H. Seko, H. Tomita, and Y. Ishikawa
""Big Data Assimilation" Revolutionizing Severe Weather Prediction"
Bull. Amer. Meteor. Soc., 97, 1347-1354 (2016). - 9.
Miyoshi, T., K. Kondo, and K. Terasaki
"Big Ensemble Data Assimilation in Numerical Weather Prediction"
Computer, 48, 15-21 (2015). - 10.
Miyoshi, T., K. Kondo, and T. Imamura
"The 10240-member ensemble Kalman filtering with an intermediate AGCM"
Geophys. Res. Lett., 41, 5264-5271 (2014).
Recent Research Results
Mar. 28, 2022
Chaos theory provides hints for controlling the weather
Related Links
Lab Members
Principal investigator
- Takemasa Miyoshi
- Team Leader
Core members
- Shigenori Otsuka
- Research Scientist
- James Taylor
- Research Scientist
- Michael Robert Goodliff
- Research Scientist
- Arata Amemiya
- Postdoctoral Researcher
- Shun Ohishi
- Postdoctoral Researcher
- Yasumitsu Maejima
- Postdoctoral Researcher
- Jianyu Liang
- Postdoctoral Researcher
- Rakesh Teja Konduru
- Postdoctoral Researcher
- Kota Takeda
- Junior Research Associate
- Hideyuki Sakamoto
- Technical Staff I
- Takahisa Ishimizu
- Technical Staff I
- Shu-Chih Yang
- Senior Visiting Scientist
- Juan Ruiz
- Visiting Scientist
- Atsushi Okazaki
- Visiting Scientist
- Shunji Kotsuki
- Visiting Scientist
- Tobias Marcel Necker
- Visiting Scientist
Careers
Position | Deadline |
---|---|
Seeking a few Senior Scientists, Research Scientists or Postdoctoral Researchers (R-CCS2121) | Open until filled |
Contact Information
7-1-26,Minatojima-minami-machi,
Chuo-ku,Kobe,Hyogo
650-0047,Japan
Email: da-team-desk [at] ml.riken.jp