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| Job title |
Senior Researcher / The 3rd Lab. / Department of Observation and Data Assimilation Research |
| E-mail |
yasutaka.ikuta[at]mri-jma.go.jp |
| Personal |
researchmap |
| Expertise |
Data assimilation, Meso-scale meteorology |
| Degree |
Ph.D. |
| Publications |
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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