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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., 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, in press.
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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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