NIED | K-NET,KiK-net| MOWLAS | Research Division | STAR-E

Hisahiko KUBO

orcid.org/0000-0002-1933-7899 | Web of Science | Researchmap | KAKEN | Google Scholar | Scopus

Research fields:
     Strong motions, Earthquake source process, Application of machine learning to seismology

Publications

In preparation, in review, or in press

• Kubo, H. and K. Shiomi (2024) Toward an understanding of the utilization status of NIED MOWLAS data based on data DOI citation information, Zisin (Journal of the Seismological Society of Japan. 2nd ser.), in review.

Papers (peer reviewed)

• Kubo, H., M. Naoi, and M. Kano (2024) Recent Advances in Earthquake Seismology using Machine Learning, Earth, Planets and Space, 76, 36. https://doi.org/10.1186/s40623-024-01982-0
• Suzuki, W., T. Kimura, H. Kubo, and S. Senna (2023) Strong Motion Simulation of the Hypothetical M7 Intraplate Earthquake beneath Tokyo Metropolitan Area Using MeSO-net Observation Data, Journal of Japan Association for Earthquake Engineering, 23, 4, 4_54-4_69. https://doi.org/10.5610/jaee.23.4_54 (in Japanese with English abstract)
• Kubo, H., T. Kubota, W. Suzuki, and T. Nakamura (2023) On the use of tsunami-source data for high-resolution fault imaging of offshore earthquakes. Earth, Planets and Space, 75, 125. https://doi.org/10.1186/s40623-023-01878-5
• Kubo, H., T. Kimura, and K. Shiomi (2023) Exploratory Data Analysis of Earthquake Moment Tensor Catalog in Japan using Non-linear Graph-based Dimensionality Reduction, Pure and Applied Geophysics, 180, 2689-2703. https://doi.org/10.1007/s00024-023-03296-w
• Kubo, H., and T. Kunugi (2022) Prediction Approach of Rise Part of Real-Time Seismic Intensity, Journal of Japan Association for Earthquake Engineering, 22, 6, 6_22-6_38. https://doi.org/10.5610/jaee.22.6_22 *This paper is an English translation of a paper originally published in Japanese (Kubo and Kunugi 2022).
• Kubo, H., T. Kimura, and K. Yoshida (2022) APPLICATION OF BAYESIAN OPTIMIZATION TO CENTROID MOMENT TENSOR INVERSION, Intelligence, Informatics and Infrastructure, 3, J2, 209-214. https://doi.org/10.11532/jsceiii.3.J2_209
• Kubo, H., T. Kubota, W. Suzuki, S. Aoi, O. Sandanbata, N. Chikasada, and H. Ueda (2022) Ocean-wave phenomenon around Japan due to the 2022 Tonga eruption observed by the wide and dense ocean-bottom pressure gauge networks, Earth, Planets and Space, 74, 104. https://doi.org/10.1186/s40623-022-01663-w
• Kubo, H., and T. Kunugi (2022) Prediction Approach of Rise Part of Real-Time Seismic Intensity, Journal of Japan Association for Earthquake Engineering, 22, 1, 1_36-1_49. https://doi.org/10.5610/jaee.22.1_36 (in Japanese with English abstract)
• Yoshida, K., N. Uchida, H. Kubo, R. Takagi, and S. Xu (2022) Prevalence of updip rupture propagation in interplate earthquakes along the Japan trench, Earth and Planetary Science Letters, 578, 117306. https://doi.org/10.1016/j.epsl.2021.117306
• Kubo, H., W. Suzuki, and A. Noda (2022) Effect of fault discretization on geodetic source inversion and usefulness of the trans-dimensional inversion approach, Geophysical Journal International, 229, 2, 1063-1076. https://doi.org/10.1093/gji/ggab515
• Kubota, T., H. Kubo, K. Yoshida, N. Y. Chikasada, W. Suzuki, T. Nakamura, and H. Tsushima (2021) Improving the constraint on the M_w 7.1 2016 off-Fukushima shallow normal-faulting earthquake with the high azimuthal coverage tsunami data from the S-net wide and dense network: Implication for the stress regime in the Tohoku overriding plate, Journal of Geophysical Research: Solid Earth, 126, e2021JB022223. https://doi.org/10.1029/2021jb022223
• Miyamoto, T., T. Asakawa, H. Kubo, Y. Nomura and Y. Miyamori (2020) Research trends in machine learning from the perspective of disaster prevention applications, Intelligence, Informatics and Infrastructure, 1, J1, 242-251. https://doi.org/10.11532/jsceiii.1.J1_242.
• Kubo, H., K. Asano, T. Iwata, and S. Aoi (2020) Along-dip variation in seismic radiation of the 2011 Ibaraki-oki, Japan, earthquake (M_w 7.9) inferred using a multiple-period-band source inversion approach, Journal of Geophysical Research: Solid Earth, 125, e2020JB019936. https://doi.org/10.1029/2020JB019936
• Kubo, H., T. Kunugi, W. Suzuki, S. Suzuki, and S. Aoi (2020) Hybrid predictor for ground-motion intensity with machine learning and conventional ground motion prediction equation, Scientific Reports, 10, 11871. https://doi.org/10.1038/s41598-020-68630-x
• Kubo, H., and T. Nishikawa (2020) Relationship of preseismic, coseismic, and postseismic fault ruptures of two large interplate aftershocks of the 2011 Tohoku earthquake with slow-earthquake activity, Scientific Reports, 10, 12044. https://doi.org/10.1038/s41598-020-68692-x
• Kubo, H., A. Iwaki, W. Suzuki, S. Aoi, and H. Sekiguchi (2020) Estimation of the source process and forward simulation of long-period ground motion of the 2018 Hokkaido Eastern Iburi, Japan, earthquake, Earth, Planets and Space, 72, 20. https://doi.org/10.1186/s40623-020-1146-z
  [Source model data]

  *The previous paper (Kubo et al., 2019a) was retracted (Kubo et al., 2019b) because after the publication, I and the coauthors noticed that the source inversion was not done with the intended setting. The corrected version was published as Kubo et al. (2020).

• Kubo, H., T. Nakamura, W. Suzuki, Y. P. Dhakal, T. Kimura, T. Kunugi, N. Takahashi, and S. Aoi (2019) Ground-motion characteristics and nonlinear soil response observed by DONET1 seafloor observation network during the 2016 southeast off-Mie, Japan, earthquake, Bulletin of the Seismological Society of America. 109, 3, 976-986. https://doi.org/10.1785/0120170296
• Takemura, S., H. Kubo, T. Tonegawa, T. Saito, and K. Shiomi (2018) Modeling of long-period ground motions in the Nankai subduction zone: Model simulation using the accretionary prism derived from oceanfloor local S-wave velocity structures, Pure and Applied Geophysics, 176, 627-647. https://doi.org/10.1007/s00024-018-2013-8
• Kubo, H., T. Nakamura, W. Suzuki, T. Kimura, T. Kunugi, N. Takahashi, and S. Aoi (2018) Site amplification characteristics at Nankai seafloor observation network, DONET1, Japan, evaluated using spectral inversion, Bulletin of the Seismological Society of America, 108, 3A, 1210-1218. https://doi.org/10.1785/0120170254
• Takemura, S., T. Kimura, T. Saito, H. Kubo, and K. Shiomi (2018) Moment tensor inversion of the 2016 southeast offshore Mie earthquake in the Tonankai region using a three-dimensional velocity structure model: effects of the accretionary prism and subducting oceanic plate, Earth, Planets and Space, 70, 50. https://doi.org/10.1186/s40623-018-0819-3
• Urata, Y., K. Yoshida, E. Fukuyama, and H. Kubo (2017) 3-D dynamic rupture simulations of the 2016 Kumamoto, Japan, earthquake, Earth, Planets and Space, 69, 150. https://doi.org/10.1186/s40623-017-0733-0 (2018 Research Paper Award of the Seismological Society of Japan)
• Kubo, H., W. Suzuki, S. Aoi, and H. Sekiguchi (2017) Source rupture process of the 2016 central Tottori, Japan, earthquake (M_JMA 6.6) inferred from strong motion waveforms, Earth Planets Space, 69, 127. https://doi.org/10.1186/s40623-017-0714-3
  [Source model data]
• Kubo, H., W. Suzuki, T. Kunugi, and S. Aoi (2017) Attenuation Relationship Characteristics of Ground Motions for Deep-focus Earthquakes around the Ogasawara Islands, Japan, Journal of Japan Association for Earthquake Engineering, 17, 4, 13-29. https://doi.org/10.5610/jaee.17.4_13 (in Japanese with English abstract)
• Suzuki, W., S. Aoi, T. Kunugi, H. Kubo, N. Morikawa, H. Nakamura, T. Kimura, and H. Fujiwara (2017) Strong motions observed by K-NET and KiK-net during the 2016 Kumamoto earthquake sequence, Earth, Planets and Space, 69, 19. https://doi.org/10.1186/s40623-017-0604-8
• Kubo, H., W. Suzuki, S. Aoi, and H. Sekiguchi (2016) Source rupture processes of the 2016 Kumamoto, Japan, earthquakes estimated from strong motion waveforms, Earth, Planets and Space, 68, 161. https://doi.org/10.1186/s40623-016-0536-8
  [Source model data] ("Hot papers" in Web of Science)
• Dhakal, Y. P., H. Kubo, W. Suzuki, T. Kunugi, S. Aoi, and H. Fujiwara (2016) Analysis of strong ground motions and site effects at Kantipath, Kathmandu, from 2015 Mw 7.8 Gorkha, Nepal, earthquake and its aftershocks, Earth, Planets and Space, 68, 58. https://doi.org/10.1186/s40623-016-0432-2
• Kubo, H., Y. P. Dhakal, W. Suzuki, T. Kunugi, S. Aoi, and H. Fujiwara (2016) Estimation of source process of the 2015 Gorkha, Nepal, earthquake and simulation of long-period ground motions in Kathmandu basin using a one-dimensional basin structure model, Earth, Planets and Space, 68, 16. https://doi.org/10.1186/s40623-016-0393-5
• Kubo, H., K. Asano, T. Iwata, and S. Aoi (2016) Development of fully Bayesian multiple-time-window source inversion, Geophysical Journal International, 204(3), 1601-1609. https://doi.org/10.1093/gji/ggv540
• Tanaka, M., K. Asano, T. Iwata, and H. Kubo (2014) Source rupture process of the 2011 Fukushima-ken Hamadori earthquake: how did the two subparallel faults rupture?, Earth, Planets and Space, 66, 101. https://doi.org/10.1186/1880-5981-66-101 (2016 Research Paper Award of the Seismological Society of Japan)
• Kubo, H., K. Asano, and T. Iwata (2013) Source-Rupture Process of the 2011 Ibaraki-oki, Japan, Earthquake (M_w 7.9) Estimated from the Joint Inversion of Strong-Motion and GPS Data: Relationship with Seamount and Philippine Sea Plate, Geophysical Research Letters, 40, 3003-3007. https://doi.org/10.1002/grl.50558
  [Source model data]
• Kubo, H., and Y. Kakehi (2013) Source process of the 2011 Tohoku earthquake estimated from the joint inversion of teleseismic body waves and geodetic data including seafloor observation data: source model with enhanced reliability by using objectively determined inversion settings, Bulletin of the Seismological Society of America, 103, 1195-1220. https://doi.org/10.1785/0120120113

Papers (others)

• Kubo, H. (2023) Application of Machine Learning Techniques to Ground-Motion Prediction, Reports of Coordinating Committee for Earthquake Prediction, 110, 459-461 (in Japanese).
• Kubo, H., W. Suzuki, S. Aoi, and H. Sekiguchi (2020) Rupture process of the 2019 off Yamagata prefecture earthquake derived from near-source strong-motion records, Reports of Coordinating Committee for Earthquake Prediction, 103, 73-77 (in Japanese).
  [Source model data]
• Kubo, H., W. Suzuki, S. Aoi, and H. Sekiguchi (2017) Rupture process of the 2016 off Fukushima prefecture earthquake derived from near-source strong-motion records, Reports of Coordinating Committee for Earthquake Prediction, 97, 58-61 (in Japanese).
• Kubo, H., W. Suzuki, S. Aoi, and H. Sekiguchi (2017) Rupture process of the 2016 Central Tottori prefecture earthquake derived from near-source strong-motion records, Reports of Coordinating Committee for Earthquake Prediction, 97, 360-364 (in Japanese).
• Kubo, H., and S. Aoi (2016), Strong ground motions in the Oita Prefecture caused by the induced event just after the 2016 Kumamoto earthquake (Apr. 16, M 7.3), Reports of Coordinating Committee for Earthquake Prediction, 96, 606-610 (in Japanese).
• Kubo, H., W. Suzuki, S. Aoi, and H. Sekiguchi (2016) Rupture process of the 2016 Kumamoto earthquake (Apr. 16, M 7.3) derived from near-source strong-motion records, Reports of Coordinating Committee for Earthquake Prediction, 96, 600-605 (in Japanese).
• Kubo, H., W. Suzuki, S. Aoi, and H. Sekiguchi (2016) Rupture process of the 2016 Kumamoto earthquake (Apr. 14, M 6.5) derived from near-source strong-motion records, Reports of Coordinating Committee for Earthquake Prediction, 96, 595-599 (in Japanese).
• Kubo, H., W. Suzuki, S. Aoi, and H. Sekiguchi (2016) Rupture process of the 2016 Urakawa-oki earthquake derived from near-source strong-motion records, Reports of Coordinating Committee for Earthquake Prediction, 96, 47-51 (in Japanese).
  [Source model data]
• Kubo, H., T. Kimura, W. Suzuki, S. Aoi, and H. Sekiguchi (2015) Rupture process of the 2015 Miyagi-oki earthquake derived from near-source strong-motion records, Reports of Coordinating Committee for Earthquake Prediction, 94, 64-70 (in Japanese).
  [Source model data]
• Kakehi, Y., and H. Kubo (2013) Structure of subduction zone and source model of huge interplate earthquake: possibility of fault-width saturation for the 2011 Tohoku earthquake, Report of Research Center for Urban Safety and Security, Kobe University, 17, 259-268 (in Japanese with English abstract).

Proceedings

• Kubo, H. and A. Iwaki (2023) Hybrid of GMPE and Machine Learning for Site-Specific Earthquake Ground-Motion Prediction, The 16th Japan Earthquake Engineering Symposium, Day2-C2-PB22, Yokohama.
• Kubo, H. (2023) An Attempt for Symbolic Regression of Earthquake Ground-Motion Prediction Equation Using AI Feynman, JSAI2023, 3Yin2-42, Kumamoto & Online. https://doi.org/10.11517/pjsai.JSAI2023.0_2B6GS302
• Kubo, H., T. Kimura, and K. Shiomi (2022) Similarity search of earthquakes based on a UMAP embedded map, JSAI2022, 3Yin2-42, Kyoto & Online. https://doi.org/10.11517/pjsai.JSAI2022.0_3Yin24
• Kubo, H., T. Nakamura, W. Suzuki, T. Kunugi, N. Takahashi, and S. Aoi (2020) Site characteristics of DONET1 seafloor observation network, Japan, evaluated by HVSR of coda waves and ambient noise, The 17th World Conference on Earthquake Engineering, Paper No C000923.
• Kubo, H., T. Kunugi, W. Suzuki, T. Kimura, and S. Aoi (2020) Construction of explainable random forest predictor for ground-motion intensity, JSAI2020, 4Rin1-94, Online (Kumamoto). https://doi.org/10.11517/pjsai.JSAI2020.0_4Rin194
• Kubo, H., T. Kunugi, S. Suzuki, W. Suzuki, and S. Aoi (2019) Attempt to reduce the effect of biased data-set on ground-motion prediction using machine learning, JSAI2019, 4K2-J-13-02, Niigata. https://doi.org/10.11517/pjsai.JSAI2019.0_4K2J1302
• Kubo, H., T. Kunugi, S. Suzuki, W. Suzuki, and S. Aoi (2018) Construction of ground motion prediction equation using random forest, JSAI2018, 4Pin1-35, Kagoshima. https://doi.org/10.11517/pjsai.JSAI2018.0_4Pin135
• Kubo, H., W. Suzuki, T. Kunugi, and S. Aoi (2017) An attenuation relationship for deep-focus earthquakes around the Ogasawara Islands, Japan, Proc. 16th World Conf. Earthq. Eng., Santiago, Chile, paper no. 1119.
• Iwata, T., H. Kubo, K. Asano, K. Sato, and S. Aoi (2016) Long-period ground motion characteristcs and simulation in the Osaka basin duitng the 2011 great Tohoku earthquake, Proc. 5th IASPEI/IAEE Int. Symp. on the Effects of Surface Geology on Seismic Motion, Taipei, Taiwan, paper no. I101A.

Recent presentations at the international meeting    *Please see Researchmap for the full list

• Kubo, H., T. Kimura, and K. Shiomi (2023) Visualization of Temporal Changes in Seismic Activity around Japan by Applying Graph-Based Dimensionality Reduction to the Regional Moment Tensor Catalog, 2023 AGU Fall Meeting, S31E-0386, Sanfrancisco.
• Kubo, H., and A. Iwaki (2022) Development of hybrid site-specific ground motion model of response spectra using GMPE and machine learning, 2022 AGU Fall Meeting, S41C-10, Chicago & Virtual.
• Kubo, H., A. Iwaki, and T. Miyamoto (2021) Development of a site-specific ground motion model with a machine learning technique, 2021 AGU Fall Meeting, S35C-0232, Virtual.
• Kubo, H., T. Nakamura, W. Suzuki, T. Kunugi, N. Takahashi, and S. Aoi (2021) Site characteristics of DONET1 seafloor observation network, Japan, evaluated by HVSR of coda waves and ambient noise, The 17th World Conference on Earthquake Engineering, Paper No C000923, Virtual.
• Kubo, H. and T. Nishikawa (2021) Relationship of preseismic, coseismic, and postseismic fault ruptures of large interplate earthquakes with slow-earthquake activity along the Japan Trench, IAGA-IASPEI 2021, Virtual.
• Kubo, H. and W. Suzuki (2020) Development of the spatiotemporal trans-dimensional source inversion, 2020 AGU Fall Meeting, S037-0002, Virtual.
• Kubo, H., W. Suzuki, and A. Noda (2019) Application of trans-dimensional inversion to source-process estimation using geodetic data, 2019 AGU Fall Meeting, S31D-0546, San Francisco.
• Kubo, H., T. Nakamura, W. Suzuki, T. Kimura, T. Kunugi, N. Takahashi, and S. Aoi (2017) Site amplification at Nankai seafloor observation network DONET1 in Japan evaluated by spectral inversion, IAG-IASPEI 2017, J07, Kobe.
• Kubo, H., W. Suzuki, S. Aoi, and H. Sekiguchi (2016) Estimation of source processes of the 2016 Kumamoto earthquakes from strong motion waveforms, 2016 AGU Fall Meeting, S53B-2863, San Francisco.
• S. Aoi, T. Kunugi, W. Suzuki, H. Kubo, N. Morikawa, and H. Fujiwara (2016) Strong ground motion of the 2016 Kumamoto earthquake, 2016 AGU Fall Meeting, S52C-02, San Francisco.
• Kubo, H., T. Iwata, K. Asano, and S. Aoi (2015) Period-dependent seismic radiation for the 2011 Tohoku-oki earthquake estimated by multiple-period-band source modelling, The 26th General Assembly of IUGG, S05p-373.

Books and reports

• Unusual tsunami due to the 2022 Tonga volcanic eruption, NIED NEWS, 219, Dec. 2022 (Joint authorship).
  https://doi.org/10.24732/NIED.00003924
• Young Scientist Award, Comments from winners of SSJ awards in 2021, SSJ News Letter, 71, 1.
  https://www.zisin.jp/publications/pdf/newsletter/75NL1.pdf
• Earthquake Research Project: STAR-E (Seismology TowArd Research innovation with data of Earthquake) Project, Research and Development for Semi-real-time Spatio-temporal Forecasting of Seismic Activity and Associated Ground Motion Considering Incompleteness of Seismic Data -NIED-, The Headquarters for Earthquake Research Promotion News, 14, 3, 2021 Winter.
  https://www.jishin.go.jp/main/herpnews/2021/win/herpnews2021win.pdf
• Predicting earthquake ground motions with a hybrid of AI and physical model, NIED NEWS, 214, Nov. 2021.
  https://www.bosai.go.jp/information/news/pdf/k_news214.pdf
• Predicting earthquake ground motions with a hybrid of machine learning and physical model, Earthquake Journal, 71, 56-59, June 2021.
  https://www.adep.or.jp/public/img/71.pdf
• Cover, SSJ Newsletter, 74, NL1, May 2021.
  http://www.zisin.jp/newsletter/74NL1.pdf
• Efforts of Research Institutes: Hybrid Approach of Machine Learning and Physical Model for Better Ground Motion Prediction -NIED-, The Headquarters for Earthquake Research Promotion News, 13, 2, 2020 Autumn.
  https://www.jishin.go.jp/main/herpnews/2020/aut/herpnews2020aut.pdf
• Special Edition: Earthquake Engineering from the Perspective of Young Researchers and Engineers, Bulletin of JAEE, 41, October 2020.
  http://www.jaee.gr.jp/jp/stack/mag-j
• Towards Utilization of Earthquake and Tsunami Data on N-net, NIED NEWS, 209, June 2020 (Joint authorship).
  https://www.bosai.go.jp/information/news/pdf/k_news209.pdf
• 2017 young-researcher paper award--Attenuation Relationship Characteristics of Ground Motions for Deep-focus Earthquakes around the Ogasawara Islands, Japan, JAEE NEWSLETTER, 7, 2, August 2018.
  http://www.jaee.gr.jp/jp/wp-content/uploads/2018/09/JAEE2018_vol7_no2_21_2.pdf
• Cover, SSJ Newsletter, 69, NL2, July 2016.
  http://www.zisin.jp/newsletter/69NL2.pdf
• Voice of young researcher, DPRI Newsletter, 72, May 2014.
  http://www.dpri.kyoto-u.ac.jp/web_j/dprinews/news72/pdf/news72.pdf

Prizes

• Intelligence, Informatics and Infrastructure Highlighted Paper Award 2022 (Miyamoto et al., 2022)
• 2022 Young Scientist Award of the Seismological Society of Japan
• 2018 Research Paper Award of the Seismological Society of Japan (Urata et al., 2017)
• 2017 Young-researcher Paper Award of the Japan Association for Earthquake Engineering (Kubo et al., 2017)
• 2016 Research Paper Award of the Seismological Society of Japan (Tanaka et al., 2014)
• Student Outstanding Presentation Award of Seismological Society of Japan 2014 Fall Meeting
• Student Outstanding Presentation Award of Japan Geoscience Union Meeting 2014
• Outstanding Presentation Award of Disaster Prevention Research Institute Annual Meeting 2014

Affiliated societies

• Seismological Society of Japan
  
• Japan Association for Earthquake Engineering
  
• Japan Geoscience Union
  
• American Geophysical Union
  

Experiences

Education

• Mar. 2015 D.Sc. in Geophysics, Graduate School of Science, Kyoto University
• Mar. 2012 M.Sc. in Geophysics, Graduate School of Science, Kobe University
• Mar. 2010 B.Sc. in Geophysics, Faculty of Science, Kobe University

Research

• Jan. 2022 - Chief Researcher, National Research Institute for Earth Science and Disaster Resilience
• July 2019 - Dec. 2021 Researcher, National Research Institute for Earth Science and Disaster Resilience
• Apr. 2015 - June 2019 Research Fellow, National Research Institute for Earth Science and Disaster Resilience
• Apr. 2014 - Mar. 2015 JSPS Research Fellow (DC2)
• Apr. 2013 - Mar. 2014 Research Assistant, Disaster Prevention Research Institute, Kyoto University
• Apr. 2012 - Mar. 2013 Research Assistant, Disaster Prevention Research Institute, Kyoto University

Grant

• Jul. 2021 - Mar. 2026 MEXT Project for Seismology toward Research Innovation with Data of Earthquake (STAR-E) Grant Number JPJ010217, Research and development for semi-real-time spatio-temporal forecasting of seismic activity and associated ground motion considering incompleteness of seismic data (Principal Investigator)
• Apr. 2021 - Mar. 2024 Grant-in-Aid for Young Scientists, 21K14019, JSPS (Principal Investigator)
• Apr. 2017 - Mar. 2022 Grant-in-Aid for Young Scientists (B), 17K14384, JSPS (Principal Investigator)
• Apr. 2014 - Mar. 2015 Grant-in-Aid for JSPS Fellows, 14J06763, JSPS

To NIED, Earthquake and Tsunami Research Division
Last update: 2024-03-04