| Project/Area Number |
11450387
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| Research Category |
Grant-in-Aid for Scientific Research (B).
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
海洋工学
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| Research Institution | The University of Tokyo |
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Principal Investigator |
YAMAGUCHI Hajime Univ.Tokyo, Environmental & Ocean Eng., Prof., 大学院・工学系研究科, 教授 (20166622)
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| Co-Investigator(Kenkyū-buntansha) |
SATO Toru Univ.Tokyo, Environmental & Ocean Eng., Assoc.Prof., 大学院・工学系研究科, 助教授 (30282677)
RHEEM Chang-kyu Univ.Tokyo, Environmental & Ocean Eng., Assoc.Prof., 生産技術研究所・付属海中工学研究センター, 助教授 (70272515)
KATO Hiroharu Univ.Toyo, Mechanical Engineering, Prof., 工学部, 教授 (00010695)
MAEDA Masatsugu Univ.Tokyo, Environmental & Ocean Eng., Assistant, 大学院・工学系研究科, 助手 (60219277)
KOMURA Takashi Univ.Tokyo, Environmental & Ocean Eng., Assistant, 大学院・工学系研究科, 助手 (10010894)
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| Project Period (FY) |
1999 – 2000
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| Project Status |
Completed (Fiscal Year 2000)
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| Budget Amount *help |
¥15,200,000 (Direct Cost: ¥15,200,000)
Fiscal Year 2000: ¥3,200,000 (Direct Cost: ¥3,200,000)
Fiscal Year 1999: ¥12,000,000 (Direct Cost: ¥12,000,000)
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| Keywords | Arctic Ocean / Sea Ice / Geographic Information System / GIS / Numerical Forecast / Polar Environment / Ice Engineering / Drifting Ice |
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| Research Abstract |
1. Meteorological data on the Arctic Ocean were obtained from ECMWF and Japan Meteorological Agency. Sea ice distribution data measured by satellite remote sensing were obtained from NSIDC.These data are of SSM/I sensor, which is installed on the US DMSP satellite.
2. Since sea current data is very limited, we performed fundamental experiments using a rotating tank and also numerical simulation with the same condition, considering to use numerical simulation technique. The experimental current showed the same pattern as the observed surface current in the Arctic Ocean, suggesting that the effect of river run-off along the Siberian and Alaska coasts is significant. The numerical simulation using multi-layer model also showed the same pattern, suggesting that this computer program can be applied to predict the Arctic Ocean current.
3. All of the collected data were transferred into ArcView GIS database format. Because of this, it has become easy to view and analyze the data.
4. The GIS-database system developed in this research was used to analyze the sea ice in the Arctic Ocean. Although the whole ice field changed mainly due to wind and air temperature, some areas showed very complicated sea ice motion. As such, the characteristics of sea ice change can be extracted for each sea area.
5. Several interface programs were developed to connect the GIS and sea ice change prediction programs. As a result, an integrated system of data, GIS and prediction computations was developed. Using this system, we executed sea ice change prediction computations, confirming the effectiveness of this system.
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