| Project/Area Number |
17K05664
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Meteorology/Physical oceanography/Hydrology
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| Research Institution | Japan Agency for Marine-Earth Science and Technology |
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Principal Investigator |
SAITO Fuyuki 国立研究開発法人海洋研究開発機構, 地球環境部門(環境変動予測研究センター), 研究員 (60396942)
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| Project Period (FY) |
2017-04-01 – 2023-03-31
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| Project Status |
Completed (Fiscal Year 2022)
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| Budget Amount *help |
¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
Fiscal Year 2019: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2018: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2017: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
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| Keywords | 氷床モデル / 氷床モデリング / 数値モデリング / 保存性輸送数値スキーム / 氷床 / 数値計算 |
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| Outline of Final Research Achievements |
Numerical ice sheet models include equations to solve evolution of ice thickness, temperature and ages, which are represented as either transport equation or advection-diffusion equations. In this study higher-order numerical schemes are implemented for these equations, in order to evaluate their efficiencies and accuracies with comparing the results obtained by classical numerical schemes such as the upwind schemes. In particular, implementation of one of the higher-order semi-Lagrangian scheme (the RCIP scheme) on the computation of ages achieved significant improvement not only the age itself but also annual layer thickness, which is inverse of the age derivative. It is expected that, using this novel technique, much accurate information can be provided for the decision of ice-core drilling site, for example.
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| Academic Significance and Societal Importance of the Research Achievements |
近年、地球温暖化に対する氷床応答によって起こりうる将来の海水準上昇に、世界的な関心が集まっている。このことに関連して数値モデルを用いた氷床応答の定量的評価への要請も高い。また、気候システムのより深い理解のために過去の気候復元とその要因の研究が重要な課題である。氷床数値モデルで得られる氷床変動再現の高精度化、氷年代の高精度化はこのために有用な課題の一つである。本研究で開発改良した氷床モデルにより特に氷年代計算が飛躍的に向上し、古気候復元への重要な手法となった。
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