Yousuke Sato


SCALE Library

Self Introduction


Doctoral Desertation

Professional Experience

Teaching Experience


Survice activities


Public Lecture

  1. 2015 Jul.: Public Lecture on cloud, Public discourse by Hydrospheric Atmospheric Research Center (HyARC), Nagoya University (in Japanese)

  2. 2016 Oct.: Interview to Researcher (Lecture for high-school students)No. 3, Computational Science for All vol. 11, (in Japanese)

Press Release

  1. 2016 May.:Current atmospheric models underestimate the dirtiness of Arctic air

  2. 2018 Mar.:Scientists accurately model the action of aerosols on clouds



    1. M. Satoh, A. T. Noda, T. Seiki, Y.-W. Chen, C. Kodama, Y. Yamada, N. Kuba, and Y. Sato, (2018), Toward reduction of the uncertainties in climate sensitivity due to cloud processes using a global non-hydrostatic atmospheric model, Prog. Earth Planet. Sci., 5:67, doi:10.1186/s40645-018-0226-1 Journal page(Springer)

    2. Y. Sato, M. Takigawa, T. T. Sekiyama, M. Kajino, H. Terada, H. Nagai, H. Kondo, J. Uchida, D. Goto, D. Quélo, A. Mathieu, A. Quérel, S. Fang, Y. Morino, P. von Schoenberg, H. Grahn, N. Brännström, S. Hirao, H. Tsuruta, H. Yamazawa, and T. Nakajima, (2018), Model intercomparison of atmospheric 137Cs from the Fukushima Daiichi Nuclear Power Plant accident: Simulations based on identical input data, J. Geophys. Res.: Atmosphere, 123, doi:10.1029/2018JD029144 Journal page(AGU)

    3. Y. Sato, S. Shima, and H. Tomita, (2018), Numerical convergence of shallow convection cloud field simulations: Comparison between double-moment Eulerian and particle-based Lagrangian microphysics coupled to the same dynamical core, J. Adv. Model. Earth Sys., 10, 1495-1512, doi:10.1029/2018MS001285 Journal page(AGU)

    4. Y. Sato, D. Goto, T. Michibata, K. Suzuki, T. Takemura, H. Tomita, and T. Nakajima, (2018), Aerosol effects on cloud water amounts were successfully simulated by a global cloud-system resolving model, Nature Communications, 9, 985, doi:10.1038/s41467-018-03379-6 Journal page(NPG)

    5. T. Enoto, Y. Wada, Y. Furuta, K. Nakazawa, T. Yuasa, K. Okuda, K. Makishima, M. Sato, Y. Sato, T. Nakano, D. Uemoto, and H. Tsuchiya, (2017), Photonuclear reactions triggered by lightning discharge, Nature, 551, 481-485, doi:10.1038/nature24630 Journal page(NPG)

    6. Y. Sato, S. Shima, and H. Tomita, (2017), A grid refinement study of trade wind cumuli simulated by a Lagrangian cloud microphysical model: the super-droplet method, Atmos. Sci. Lett., 18, 350-365, doi:10.1002/asl.764 Journal page(RMetS)

    7. R. Yoshida, S. Nishizawa, H. Yashiro, S. A. Adachi, Y. Sato, T. Yamaura, and H. Tomita, (2017), CONeP: A cost-effective online nesting procedure for regional atmospheric models, Parallel Computing, 65, 21-31, doi:10.1016/j.parco.2017.04.004 Journal page(ELSEVIER)

    8. T. Michibata, K. Suzuki, Y. Sato, and T. Takemura(2016), The source of discrepancies in aerosol-cloud-precipitation interactions between GCM and A-Train retrievals, Atoms. Chem. Phys., 16, 15413-15424, doi:10.5194/acp-16-15413-2016 Journal page(Copernicus Publications)

    9. Y. Sato, A. Higuchi, A. Takami, A. Murakami, Y. Masutomi, K. Tsuchiya, D. Goto, and T. Nakajima(2016), Regional variability in the impacts of future land use on summertime temperatures in Kanto region, the Japanese megacity, Urban For. Urban Green., 20, 43-55, doi:10.1016/j.ufug.2016.07.012 Journal page(ELSEVIER)

    10. Y. Sato, H. Miura, H. Yashiro, D. Goto, T. Takemura, H. Tomita, and T. Nakajima(2016), Unrealistically pristine air in the Arctic produced by current global scale models, Scientific Reports, 6, 26561, doi:10.1038/srep26561 Journal page(NPG)

    11. S. Nishizawa, M. Odakta, Y. O. Takahashi, K. Sugiyama, K. Nakajima, M. Ishiwatari, S. Takehiro, H. Yashiro, Y. Sato, H. Tomita, and Y.-Y. Hayashi(2016), Martian dust devil statistics from high-resolution large-eddy simulations, Geophys. Res. Lett., 43, doi:10.1002/2016GL068896 Journal page(AGU)

    12. T. Iguchi, I.-J. Choi, Y. Sato, K. Suzuki, and T. Nakajima(2015), Overview of the development of the Aerosol Loading Interface for Cloud microphysics In Simulation (ALICIS), Prog. Earth Planet. Sci., 2:45, doi:10.1186/s40645-015-0075-0 Journal page(Springer)

    13. Y. Liu, Y. Sato, R. Jia, Y. Xie, J. Huang, and T. Nakajima(2015), Modeling study on the transport of summer dust and anthropogenic aerosols over the Tibetan Plateau, Atmos. Chem. Phys., 15, 12581-12594, doi:10.5194/acp-15-12581-2015 Journal page(Copernicus Publications)

    14. S. Nishizawa, H.Yashiro, Y.Sato, Y.Miyamoto, and H. Tomita(2015), Influence of grid aspect ratio on planetary boundary layer turbulence in large-eddy simulations, Geosci. Model Dev., 8, 3393-3419, doi:10.5194/gmd-8-3393-2015 Journal page(Copernicus Publications)

    15. Y.Sato, S. Nishizawa, H. Yashiro, Y.Miyamoto, Y. Kajikawa,and H. Tomita(2015), Impacts of cloud microphysics on trade wind cumulus: which cloud microphysics processes contribute to the diversity in a large eddy simulation?, Prog. Earth Planet. Sci., 2, 23, doi:10.1186/s40645-015-0053-6 Journal page(Springer)

    16. Y.Sato, Y. Miyamoto, S. Nishizawa, H. Yashiro, Y. Kajikawa, R. Yoshida, T. Yamaura, and H. Tomita(2015), Horizontal Distance of Each Cumulus and Cloud Broadening Distance Determine Cloud Cover, SOLA, 11, 75-79, doi:10.2151/sola.2015-019 Journal page(J-stage)

    17. Y.Sato, S. Nishizawa, H. Yashiro, Y. Miyamoto, and H. Tomita(2014), Potential of Retrieving Shallow-Cloud Life Cycle from Future Generation Satellite Observations through Cloud Evolution Diagrams: A Suggestion from a Large Eddy Simulation, SOLA, 10, 10-14, doi:10.2151/sola.2014-003 Journal page(J-stage)

    18. Y.Sato, T. Y. Nakajima, and T. Nakajima, (2012b), Investigation of the vertical structure of warm cloud microphysical properties using the cloud evolution diagram, CFODD, simulated by three-dimensional spectral bin microphysical model, J. Atmos. Sci., 69, 2012-2030, Journal page(AMS)

    19. Y.Sato, K. Suzuki, T. Iguchi, I.-J. Choi, H. Kadowaki, and T. Nakajima, (2012a), Characteristics of Correlation Statistics between Droplet Radius and Optical Thickness of Warm Clouds Simulated by a Three-Dimensional Regional-Scale Spectral Bin Microphysics Cloud Model, J. Atmos. Sci., 69, 484-502 Journal page(AMS)

    20. Shibata, Y., Y. Murai, Y. Satoh, Y. Fukushima, K. Okajima, M. Ikeuchi, and S. Itoh, 2009, Acceleration of Electron-Transfer-Induced Fluorescence Quenching upon Conversion to the Signaling State in the Blue-Light Receptor, TePixD, from Thermosynechococcus elongatus, J. Phys. Chem. B., 113, 8192-8198 Journal page(Pub Med)

    21. Y. Sato, T. Nakajima, K. Suzuki, and T. Iguchi, 2009, Application of a Monte Carlo integration method to collision and coagulation growth processes of hydrometeors in a bin-type model., J. Geophys. Res., 114, D09215, doi:10.1029/2008JD011247 Journal page(AGU)

    International Conference/Workshop

    Research fund


    1. Grant-in-Aid for JSPS Fellows Investigation of cloud-aerosol interaction using spectral bin microphysical model (PI: 2011 Apr. - 2012 Mar.)
    2. Grants-in-Aid for Scientific Research (B) Development of pioneering cloud microphysical model through the sophistication of Super Droplet method(SDM) for Exa-scale computing (Sub-PI: 2014 Apr. - 2017 Mar.)
    3. Joint Stage research with Hydrospheric Atmospheric Research Center (HyARC), Nagoya University, Suggestion to next-generation satellite observation from the LES simulation with ultra-fine spatial resolution (PI: 2014 Apr. - 2015 Mar.)
    4. Grant-in-Aid for Young Scientists(B) Investigation of regional variability of shallow clouds by using next-generation weather modeling (PI: 2015 Apr. - 2017 Mar.)
    5. Joint Stage research with Hydrospheric Atmospheric Research Center (HyARC), Nagoya University Suggestion of useful usage of next-generation satellite from the combination of high resolution LES, satellite simulator and remote sensing (PI: 2015 Apr. - 2016 Mar.)

    Computational Resources

    1. Initiative on Promotion of Supercomputing for Young Researchers, Supercomputing Division, Information Technology Center, The University of Tokyo Research of cloud-aerosol interaction using spectral bin microphysical model (PI: 2011 Sep. - 2012 Sep.)
    2. Research Project using HPCI computational Resources in 2014 (FY2014: General Use) Integrated environmental modeling of air pollutions in a global scale (Participant: 2014 Apr. - 2015 Mar.)
    3. Research Project using HPCI computational Resources in 2014 (FY2014: General Use) Sophisticated simulation of clouds using Super Droplet Method (SDM) and application for satellite remote sensing (Sub-PI: 2015 Jan. - 2015 Mar.)
    4. Research Project using HPCI computational Resources in 2015 (FY2015: General Use) Development of a next-generation model for atmospheric air pollutants and estimation for their emission inventories (Participant: 2015Apr. - 2016 Mar.)
    5. Research Project using HPCI computational Resources in 2015 (FY2015: General Use) Ice microphysical modeling towards lightening prediction by using the Super Droplet Method (Sub-PI: 2015Apr. - 2016 Mar.)
    6. Research Project using HPCI computational Resources in 2016 (FY2016: General Use) Evaluation of climate and environmental impacts due to atmospheric pollutions using a next-generation material transport model (Participant: 2016 Apr. - 2017 Mar.)
    7. Research Project using HPCI computational Resources in 2016 (FY2016: Junior Researcher Promotion Project) Simulation targeting on cloud aerosol interaction using global scale spectral bin microphysical model (Sub-PI: 2016 Apr. - 2017 Mar.)
    8. Research Project using HPCI computational Resources in 2016 (FY2016: General Use) Massively parallel computation to assess the necessary spatial resolution to simulate convective clouds(Sub-PI: 2016 Oct. - 2017 Mar.)

    © Yousuke Sato

    Made 2007/07/18

    Last modified 2018/11/2