幾田　泰酵　／　IKUTA, Yasutaka

事項	詳細
所属・職名	気象観測研究部・第三研究室・主任研究官
連絡先
個人ページ	researchmap
専門分野	データ同化、メソ気象学
学位	博士（理学）
受賞歴、委員等	東京大学大気海洋研究所外来研究員 JAXA 地球観測に関する科学アドバイザリ委員会 EarthCARE分科会 PMM分科会 Quality Working Group NASA Atmosphere Observing System Modeling and Data Assimilation Working group
発表論文	Ikuta, Y., M. Satoh, W. Roh, S. Matsugishi, N. Kuba, T. Seiki, A. Umehara, and H. Eito, 2025: Improvement of a single-moment cloud microphysics scheme consistent with dual-polarization radar. Journal of Geophysical Research: Atmospheres, 130, e2024JD042139, https://doi.org/10.1029/2024JD042139. Yamaguchi, M., Y. Ikuta, K. Ito, and M. Satoh, 2025: Tropical Cyclone Track and Intensity Predictions in the Western North Pacific Basin Using Pangu-Weather and JMA Initial Conditions, J. Meteor. Soc. Japan, https://doi.org/10.2151/jmsj.2025-018. Hamada, A., C. Yokoyama, H. Tsuji, Y. Ikuta, S. Shige, M. Yamaji, T. Kubota, and Y. N. Takayabu, 2025: Spectral Latent Heating Retrieval for the Midlatitudes Using GPM DPR. Part II: Development and Consistency Check of the Retrieval Algorithm. J. Appl. Meteor. Climatol., 64, 45–61, https://doi.org/10.1175/JAMC-D-23-0218.1. Yokoyama, C., A. Hamada, Y. Ikuta, S. Shige, M. Yamaji, H. Tsuji, T. Kubota, and Y. N. Takayabu, 2025: Spectral Latent Heating Retrieval for the Midlatitudes Using GPM DPR. Part I: Construction of Lookup Tables. J. Appl. Meteor. Climatol., 64, 21–43, https://doi.org/10.1175/JAMC-D-23-0217.1. Yoshida, S., T. Sakai, T. Nagai, Y. Ikuta, T. Kato, K. Shiraishi, R. Kato, and H. Seko, 2024: Water Vapor Lidar Observation and Data Assimilation for a Moist Low-Level Jet Triggering a Mesoscale Convective System. Mon. Wea. Rev., 152, 1119–1137, https://doi.org/10.1175/MWR-D-23-0094.1. Ikuta, Y., and U. Shimada, 2024: Impact of Assimilation of the Tropical Cyclone Strong Winds Observed by Synthetic Aperture Radar on Analyses and Forecasts. Mon. Wea. Rev., https://doi.org/10.1175/MWR-D-23-0103.1. Yokota, S., T. Banno, M. Oigawa, G. Akimoto, K. Kawano, Y. Ikuta, 2024: JMA Operational Hourly Hybrid 3DVar with Singular Vector-Based Mesoscale Ensemble Prediction System. J. Meteor. Soc. Japan, 102, 129–150, https://doi.org/10.2151/jmsj.2024-006. Ikuta, Y., M. Sawada, and M. Satoh, 2023: Determining the Impact of Boundary Layer Schemes on the Secondary Circulation of Typhoon Faxai Using Radar Observations in the Gray Zone. J. Atmos. Sci., 80, 961–981, https://doi.org/10.1175/JAS-D-22-0169.1. Satoh, M., S. Matsugishi, W. Roh, Y. Ikuta, N. Kuba, T. Seiki, T. Hashino, and H. Okamoto, 2022: Evaluation of cloud and precipitation processes in regional and global models with ULTIMATE (ULTra-sIte for Measuring Atmosphere of Tokyo metropolitan Environment): a case study using the dual-polarization Doppler weather radars. Prog. Earth Planet Sci., 9, 51, https://doi.org/10.1186/s40645-022-00511-5. Yoshida, S., T. Sakai, T. Nagai, Y. Ikuta, Y. Shoji, H. Seko, and K. Shiraishi, 2022: Lidar Observations and Data Assimilation of Low-Level Moist Inflows Causing Severe Local Rainfall Associated with a Mesoscale Convective System. Mon. Wea. Rev., 150, 1781–1798, https://doi.org/10.1175/MWR-D-21-0213.1. Ikuta, Y., H. Seko, and Y. Shoji, 2022: Assimilation of shipborne precipitable water vapour by Global Navigation Satellite Systems for extreme precipitation events. Quart. J. Roy. Meteor. Soc., 148, 57–75, https://doi.org/10.1002/qj.4192. Ikuta, Y., T. Fujita, Y. Ota, and Y. Honda, 2021: Variational Data Assimilation System for Operational Regional Models at Japan Meteorological Agency. J. Meteor. Soc. Japan, 99, 1563–1592, https://doi.org/10.2151/jmsj.2021-076. Ikuta, Y. 2021: Chapter 23 - Radar data assimilation in numerical weather prediction models. Precipitation Science Measurement, Remote Sensing, Microphysics and Modeling, Elsevier, 743–756. https://doi.org/10.1016/B978-0-12-822973-6.00012-3. Ikuta, Y., M. Satoh, M. Sawada, H. Kusabiraki,and T. Kubota, 2021: Improvement of the Cloud Microphysics Scheme of the Mesoscale Model at the Japan Meteorological Agency Using Spaceborne Radar and Microwave Imager of the Global Precipitation Measurement as Reference. Mon. Wea. Rev., 149, 3803–3819. https://doi.org/10.1175/MWR-D-21-0066.1. Barreyat, M., P. Chambon, J.-F. Mahfouf, G. Faure, and Y. Ikuta, 2021: A 1D Bayesian inversion applied to GPM Microwave Imager observations: Sensitivity studies. J. Meteor. Soc. Japan, 99, 1045–1070. https://doi.org/10.2151/jmsj.2021-050. Ikuta, Y., K. Okamoto, and T. Kubota, 2021: One‐dimensional maximum‐likelihood estimation for spaceborne precipitation radar data assimilation. Quart. J. Roy. Meteor. Soc., 147, 858–875. https://doi.org/10.1002/qj.3950. Gustafsson, N., T. Janjić, C. Schraff, D. Leuenberger, M. Weissmann, H. Reich, P. Brousseau, T. Montmerle, E. Wattrelot, A, Bučánek, M. Mile, R. Hamdi, M. Lindskog, J. Barkmeijer, M. Dahlbom, B. Macpherson, S. Ballard, G. Inverarity, J. Carley, C. Alexander, D. Dowell, S. Liu, Y. Ikuta, and T. Fujita, 2018: Survey of data assimilation methods for convective‐scale numerical weather prediction at operational centres. Quart. J. Roy. Meteor. Soc., 144, 1218–1256. https://doi.org/10.1002/qj.3179.
担当課題リスト	気象研究所 基盤技術研究「データ同化技術と観測解析技術の高度化に関する研究」 「富岳」気象学的および数理的アプローチによる線状降水帯のメカニズム解明 令和７年度東京大学大気海洋研究所共同利用外来研究員「メソ気象における雲降水プロセスの解明とデータ同化に関する研究」 JAXA第4回地球観測研究公募（代表）「日本周辺におけるkmスケールの現象を対象とした雲降水データ同化の高度化」 科研費基盤研究C（代表）「集中豪雨の発達機構を解明する水物質同化手法の研究」