| Project/Area Number |
16K12861
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| Research Category |
Grant-in-Aid for Challenging Exploratory Research
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| Allocation Type | Multi-year Fund |
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| Research Field |
Natural disaster / Disaster prevention science
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| Research Institution | National Institute of Information and Communications Technology |
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Principal Investigator |
Yamamoto Masayuki 国立研究開発法人情報通信研究機構, 電磁波研究所リモートセンシング研究室, 主任研究員 (90346073)
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| Research Collaborator |
KAWAMURA Seiji 情報通信研究機構, 電磁波研究所リモートセンシング研究室, 主任研究員 (10435795)
YAMAGUCHI Kosei 京都大学, 防災研究所, 准教授 (90551383)
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| Project Period (FY) |
2016-04-01 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥3,510,000 (Direct Cost: ¥2,700,000、Indirect Cost: ¥810,000)
Fiscal Year 2017: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2016: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Keywords | 大気現象 / ウィンドプロファイラ / 高分解能観測 / 自然現象観測・予測 / リモートセンシング |
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| Outline of Final Research Achievements |
Wind profiler radar (WPR) is an instrument that measures height profiles of wind velocity in the clear air. WPRs have been used not only for researches aiming at clarifying dynamical processes in the atmosphere but also for weather monitoring and prediction by meteorology institutions. Aiming at realizing a breakthrough in measurement resolution of WPR, next-generation WPR has been developed. Clutter mitigation is indispensable for attaining measurement resolution required for next-generation WPR. In this study, a technique that mitigates clutter with retaining measurement resolution was developed. WPRs that have range imaging (RIM), oversampling (OS), and adaptive clutter suppression (ACS) capabilities were used. By experiments using the WPRs, cases in which a combination of RIM plus OS and ACS mitigated clutter and resolved small-scale perturbations of vertical wind at low altitudes were shown.
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| Academic Significance and Societal Importance of the Research Achievements |
次世代WPRは、局地的な気象現象が引き起こす小スケールの風速や乱れを十分に把握できる観測分解能の達成を目指している。次世代WPRが目指す観測性能の達成には、優れた観測分解能の実現に加え、風速・乱流の測定データ品質の向上が必要である。本研究により、OS付きRIMとACSの組み合わせが、観測分解能を確保しつつクラッタによる風速・乱流の測定データ品質の低下を抑える有望な手段であることを示すことができたと考えている。
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