1990 Fiscal Year Final Research Report Summary
Physical and Stochastic analyses of heavy rainfall structure and development of short-term prediction system using three-dimensionally scanning radar and satellite
| Project/Area Number |
63850119
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| Research Category |
Grant-in-Aid for Developmental Scientific Research (B).
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| Allocation Type | Single-year Grants |
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| Research Field |
Hydraulic engineering
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| Research Institution | Kyoto University |
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Principal Investigator |
IKEBUCHI S Kyoto. Univ. D. P. R. I. Professor, 防災研究所, 教授 (20026181)
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| Co-Investigator(Kenkyū-buntansha) |
肆矢 雄三 気象庁, 気象衛星センター, 解析技術専門官
阿部 世史之 気象庁, 気象衛星センター, 運輸調査官
NAKAKITA E Kyoto. Univ. D. P. R. I. Associate Professor, 防災研究所, 助教授 (70183506)
SHIIBA M Kyoto. Univ. Engineering Associate Professor, 工業部, 助教授 (90026352)
ABE Y Meteorological Meteorological Engineer of Ministry Satellite
YOTSUYA Y Agency Center of Transport
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| Project Period (FY) |
1988 – 1990
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| Keywords | Radar / Meteorological Satellite / Remote Sensing / Short-term rainfall prediction / Water balance / Stochastic model / Rainfall distribution |
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| Research Abstract |
Firstly, a short-term rainfall prediction method using a three-dimensionally scanning radar is developed based on the analyses of time variations of rainfall distribution. The method is physically based one in the sense that the water balance is taken into consideration.
Secondly, a method of estimating rainfall distribution using geostationary meteorological satellite data is developed with the accuracy of the estimation. One can get rainfall distribution for every an hour in the wide area which includes the area of, for example. Radar network over Japan.
Nextly, a stochastic model of rainfall distribution is proposed based on the statistical analysis using radar and satellite data following to the discussion about how stochastic rainfall distribution models should be used to making planning for disaster prevention.
Finally, two methods of using satellite data into the physical based prediction method. One of then is a method of predicting translation vector of instability field using satellite data. The other is a mth odestimating three-dimensional rainfall distribution using horizontal rainfall distribution. Wing to the development of these two methods, the short-term rainfall prediction system has been completed.
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