2023 Fiscal Year Final Research Report
Development of UAV-mounted disdrometer for enabling traverse measurement of raindrop size distribution and rainfall intensity in the air
Project/Area Number |
22K18834
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Research Category |
Grant-in-Aid for Challenging Research (Exploratory)
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Allocation Type | Multi-year Fund |
Review Section |
Medium-sized Section 22:Civil engineering and related fields
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Research Institution | Tokyo University of Science |
Principal Investigator |
Nakayoshi Makoto 東京理科大学, 創域理工学部社会基盤工学科, 准教授 (90706475)
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Project Period (FY) |
2022-06-30 – 2024-03-31
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Keywords | 雨滴粒径分布 / UAV / Image disdrometer / microphysics |
Outline of Final Research Achievements |
We developed a UAV-mounted device for measuring raindrop size distribution and rainfall intensity, called the Image Disdrometer. By using a Spresense microcontroller to create a custom camera system, we were able to develop a device that is small, lightweight, and low in power consumption. A comparison of the rainfall intensity and raindrop size distribution measurements taken by a ground-installed LPM and the Image Disdrometer confirmed that both sets of data corresponded well. It was also confirmed that the impact of high wind speeds, which are a concern during aerial measurements, and the vibrations caused by flight, have negligible effects on the measurement accuracy of the Image Disdrometer.
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Free Research Field |
都市気象学
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Academic Significance and Societal Importance of the Research Achievements |
雨滴粒径分布は降雨レーダによる雨量測定に不可欠な情報である。日本では全土に偏波レーダが配備されており、偏波レーダによる雨量プロダクトが利用できるが、推定された雨滴粒径分布関数が不正確であれば雨量プロダクトに誤差が生じる。偏波レーダのパラメータ推定は、地上に設置してディスドロメータが用いられているが、降雨レーダが視準している上空の雨滴粒径分布と地上のそれが一致すると言える物理的合理性はない。本研究成果であるUAV搭載型Image Disdrometerはレーダが視準している高度での雨滴粒径分布を測定できる唯一のセンサであり、降雨プロダクトの高精度化、降雨災害の予測精度向上に寄与すると考える。
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