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研究室情報: 千葉大学・CEReS・小槻研究室のHPへは こちらへアクセスしてください。(2021/04/01)

■BRIEF INTRODUCTION :: Shunji Kotsuki, Ph. D. (小槻 峻司)

(1) Professor, Institute for Advanced Academic Research (IAAR), Chiba University, Japan (2) Visiting Scientist, R-CCS & CPR, RIKEN, Japan (3) Research Advisor, TOYOTA KONPON Research Institute, Japan (1) 千葉大学 国際高等研究基幹 教授 (2) 理化学研究所 計算科学研究センター/開拓研究本部 客員研究員 (3) トヨタ コンポン研究所 リサーチアドバイザー

■BRIEF NARRATIVE SUMMARY

Dr. Shunji Kotsuki is a Professor of Institute for Advanced Academic Research (IAAR), Chiba University, and leading environmental prediction science. He received his B.S. (2009), M.S. (2011) and Ph. D. (2013) degrees in civil engineering from Kyoto University. He experienced his professional career as Post-doctoral Researcher (2014-2017), and Research Scientist (2017-2019) at RIKEN Center for Computational Science (R-CCS). He started leading his research laboratory at CEReS, Chiba University since November, 2019. He became to be a Professor of IAAR of Chiba U. since July 2022.

Dr. Kotsuki is a leading scientist on data assimilation and numerical weather prediction with over 10 years of research experience in development of the global atmospheric data assimilation system (a.k.a. NICAM-LETKF). His research interests are in data assimilation mathematics, model parameter estimation, observation diagnosis including impact estimates, satellite data analysis, hydrological modeling, and atmospheric and hydrological disaster predictions. His techniques for ensemble data assimilation have been incorporated in the RIKEN’s global atmospheric data assimilation system, and improved its weather forecasts significantly. The NICAM-LETKF is running operationally as NEXRA since 2017 on the JAXA’s supercomputing system.

He has been recognized by several prestigious awards such as the Thesis Award for Young Scientists from Japan Society of Hydrology and Water Resources Engineering (2013), RIKEN Ohbu Research Incentive Award (2019), Chiba University Award for Distinguished Researcher (2020), and Young Scientist Award of MEXT (2022). In 2017, Dr. Kotsuki was selected as an Excellent Young Researcher by Ministry of Education, Culture, Sports, Science and Technology, Japan. He is also a visiting scientist of R-CCS, and exploring data-driven approaches for the environmental prediction science.

He is currently the project manager for Goal 8 of Japan's Moonshot Program, where he leads an interdisciplinary research team. This team includes experts in meteorology, disaster mathematics, information science, computer vision, ethics, and legal studies, all working together to achieve a weather-controlled society.

Please see [Full Version of CV (PDF file)] for more detail.

■ TEN SELECTED PUBLICATIONS [Link to All Publication List]

1. Kotsuki, S.*, Terasaki, K., Satoh, M., and Miyoshi, T. (2023): Ensemble-based Data Assimilation of GPM DPR Reflectivity: Cloud Microphysics Parameter Estimation with the Nonhydrostatic Icosahedral Atmospheric Model (NICAM). J. Geophys. Res., (in print). doi: 10.1029/2022JD037447 [JGR-A; IF=5.22]
2. Kotsuki, S.*, Miyoshi, T., Kondo K., and Potthast R. (2022): A Local Particle Filter and Its Gaussian Mixture Extension Implemented with Minor Modifications to the LETKF. Geosci. Model Dev., 15, 8325-8348. doi: 10.5194/gmd-15-8325-2022 [GMD; IF=6.135]
3. Kotsuki, S., and Bishop, H. C. (2022): Implementing Hybrid Background Error Covariance into the LETKF with Attenuation-based Localization: Experiments with a Simplified AGCM. Mon. Wea. Rev., 150, 283-302. doi: 10.1175/MWR-D-21-0174.1
4. Kotsuki S., Sato Y., and Miyoshi T. (2020): Data Assimilation for Climate Research: Model Parameter Estimation of Large Scale Condensation Scheme. J. Geophys. Res., 125, e2019JD031304. doi: 10.1029/2019JD031304 [JGR-A]
5. Kotsuki S., Kurosawa K., Otsuka S., Terasaki K. and Miyoshi T. (2019): Global Precipitation Forecasts by Merging Extrapolation-based Nowcast and Numerical Weather Prediction with Locally-optimized Weights. Wea. and Forecasting, 34, 701-714. doi:10.1175/WAF-D-18-0164.1 [WAF]
6. Kotsuki S., Kurosawa K., and Miyoshi T. (2019): On the Properties of Ensemble Forecast Sensitivity to Observations. Q. J. R. Meteorol. Soc., 145, 1897-1914. doi: 10.1002/qj.3534 [QJRMS]
7. Kotsuki S., Terasaki K., Kanemaru K., Satoh M., Kubota T. and Miyoshi T. (2019): Predictability of Record-Breaking Rainfall in Japan in July 2018: Ensemble Forecast Experiments with the Near-real-time Global Atmospheric Data Assimilation System NEXRA. SOLA, 15A, 1-7. doi: 10.2151/sola.15A-001 [SOLA]
8. Kotsuki S., Ota Y., and Miyoshi T. (2017): Adaptive covariance relaxation methods for ensemble data assimilation: Experiments in the real atmosphere. Quarterly Journal of the Royal Meteorological Society, 143, 2001-2015. doi: 10.1002/qj.3060 [QJRMS]
9. Kotsuki S., Miyoshi T., Terasaki K., Lien G.Y. and Kalnay E. (2017): Assimilating the Global Satellite Mapping of Precipitation Data with the Nonhydrostatic Icosahedral Atmospheric Model NICAM. Journal of Geophysical Research: Atmospheres, 122, 631-650. doi:10.1002/2016JD025355 [JGR-A]
10. Kotsuki S. and Tanaka K. (2015): SACRA - a method for the estimation of global high-resolution crop calendars from a satellite-sensed NDVI. Hydrology and Earth System Sciences, 19, 4441-4461. doi: 10.5194/hess-19-4441-2015 [HESS] [Discussion] [OpenDATA]