Chief Scientist Laboratories Prediction Science Laboratory
Chief Scientist: Takemasa Miyoshi (Ph.D.)
Integrating the Simulation Science (3rd science) and Data Science (4th science), our long-term goal is to establish the new “Science of Prediction” as the 5th scientific paradigm. Prediction and control have long been studied, but it is still a challenge to apply the traditional methods to large-scale, complex problems. Here we aim to establish the science for prediction and control for large and complex real-world problems. Human society is facing difficult problems such as environmental change, natural resources, population, medicine and health, at the individual level to the global scale. The “Prediction Science” will be a hub connecting a wide range of human knowledge, providing an objective, scientific approach based on prediction to the sustainable development of human society.
Main Research Fields
- Interdisciplinary Science & Engineering
Related Research Fields
- Environmental Science
- Complex Systems
- Mathematical & Physical Sciences
- Computational Science
- Fundamentals of Information Science
- Earth and Planetary Science
- optimal control
- dynamical systems
- data assimilation
Kotsuki, S., K. Kurosawa, S. Otsuka, K. Terasaki, and T. Miyoshi.:
"Global Precipitation Forecasts by Merging Extrapolation-Based Nowcast and Numerical Weather Prediction with Locally Optimized Weights"
Wea. Forecasting, 34, 701–714 (2019).
- 2.Kotsuki S., Kurosawa K., and Miyoshi T.:
"On the Properties of Ensemble Forecast Sensitivity to Observations"
Quarterly Journal of the Royal Meteorological Society, 145, 1897-1914 (2019).
- 3.Kondo, K., and Miyoshi, T.:
"Non-Gaussian statistics in global atmospheric dynamics: a study with a 10 240-member ensemble Kalman filter using an intermediate atmospheric general circulation model"
Nolin. Processes Geophs., 26, 211-225 (2019).
- 4.Shigenori OTSUKA, Shunji KOTSUKI, Marimo OHHIGASHI, Takemasa MIYOSHI:
"GSMaP RIKEN Nowcast: Global Precipitation Nowcasting with Data Assimilation"
Journal of the Meteorological Society of Japan. Ser. II, 2019, Volume 97, Issue 6, Pages 1099-1117 (2019).
- 5.Kotsuki, S., Sato, Y., & Miyoshi, T.:
"Data assimilation for climate research: Model parameter estimation of large‐scale condensation scheme"
Journal of Geophysical Research: Atmospheres, 125, e2019JD031304 (2020).
- Takemasa Miyoshi
- Chief Scientist
- Iyan Mulia
- Research Scientist
- Ken Furukawa
- Postdoctoral Researcher
- Tianfeng Hou
- Postdoctoral Researcher
|Seeking a Research Scientist or Postdoctoral Researcher (CPR-PS2002)||Open until filled|
Email: da-team-desk [at] ml.riken.jp