| Project/Area Number |
26286089
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Partial Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Computational science
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| Research Institution | University of Hyogo |
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Principal Investigator |
Shima Shin-ichiro 兵庫県立大学, シミュレーション学研究科, 准教授 (70415983)
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| Co-Investigator(Kenkyū-buntansha) |
佐藤 陽祐 名古屋大学, 工学研究科, 助教 (10633505)
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| Co-Investigator(Renkei-kenkyūsha) |
TOMITA Hirofumi 国立研究開発法人理化学研究所, 計算科学研究センター, チームリーダー (00399578)
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| Research Collaborator |
Arabas Sylwester AETHON, H2020 SME Innovation Associate
Grabowski Wojciech W. NCAR, Senior Scientist
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| Project Period (FY) |
2014-04-01 – 2018-03-31
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| Project Status |
Completed (Fiscal Year 2017)
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| Budget Amount *help |
¥12,610,000 (Direct Cost: ¥9,700,000、Indirect Cost: ¥2,910,000)
Fiscal Year 2016: ¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2015: ¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2014: ¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
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| Keywords | 雲微物理学 / 気象学 / 超水滴法 / 高性能計算(HPC) / 計算科学 / エアロゾル・雲相互作用 / 大気現象 / 雲微物理 / エアロゾロル・雲相互作用 / 高性能計算 (HPC) |
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| Outline of Final Research Achievements |
The super-droplet method (SDM) is a particle-based and probabilistic numerical scheme, which enables the accurate simulation of cloud microphysics with less demand on computation. In the SDM, the time evolution of particles is calculated explicitly by solving the fundamental governing equations. In this project, anticipating the advent of exascale computing era, we extended and advanced the SDM to construct a more sophisticated cloud resolving model. The new model can explicitly predict the time evolution of the diverse morphology of ice particles in deep convection. We also conducted several numerical studies on warm clouds. In particular, we elucidated for the first time that grid resolution less than about 10m is necessary to obtain an accurate numerical solution of trade-wind shallow maritime cumuli field. We also examined the possibility to accelerate the calculation, with some attention to cloud-turbulence interaction.
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