| Project/Area Number |
10450215
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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 |
Architectural environment/equipment
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| Research Institution | Kagoshima University |
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Principal Investigator |
AKASAKA Hiroshi Faculty of Engineering, Kagoshima University, Professor, 工学部, 教授 (20094112)
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| Co-Investigator(Kenkyū-buntansha) |
NIMIYA Hideyo Department of Environmental Design, Nagaoka Institute of Design, Associate Professor, 造形学部, 助教授 (50278058)
TAKEMASA Koji Department of Radiological Science and technology, Hiroshima Prefectural College of Health and Welfare, Associate Professor, 助教授 (30163439)
EMURA Kazuo Faculty of Human Life Science, Osaka City University, Associate Professor, 生活科学部, 助教授 (60138972)
MIKI Nobuhiro Faculty of Engineering, Osaka City University, Professor, 工学部, 教授 (10108665)
MATSUMOTO Shin-ichi Faculty of Systems Science and Technology, Akita Prefectural University, Professor, システム科学技術学部, 教授 (70209633)
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| Project Period (FY) |
1998 – 1999
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| Keywords | Building environment / Weather data / AMeDAS / Standard weather data / Tilted surface radiation / Subterranean temperature / Quality control |
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| Research Abstract |
The weather data for building energy calculation, which are designated as Expanded AMeDAS Weather Data (EA Weather Data), have been developed. EA Weather Data include hourly eight climatic elements for 15 years (1981-1995) at 842 stations throughout Japan. The eight climatic elements are atmospheric temperature, humidity ratio, horizontal global irradiation, atmospheric irradiation, wind direction, wind speed, precipitation, and sunshine duration. The purpose of this research is that it improves quality and value added of EA Weather Data further.
1. AQC and reconfirmation for improving data quality
Japan Meteorological Agency (JMA) has an automated quality control (AQC) procedure to detect abnormal data caused by measuring instruments failure or data transmission error. The AQC procedure by JMA has been applied EA Weather Data. Abnormal values detected by the AQC have been corrected in normal data. Quality improvement for EA Weather Data is checked by the AQC repeatedly.
2. Preparation of standard EA weather data
A demand for typical annual hourly data at each station is anticipated to be high as well as that for long-term real weather data. Thus, the standard EA weather data has been prepared based on EA weather data for 15 years. The standard EA weather data is the annual weather data prepared by selecting a typical month for each month from among 15 years to combine them.
3. Development of operation programs
Operation programs have been developed. One of the programs is called EA DataNavi. Using EA DataNavi, users can invoke EA weather data for a single year at a required station from the CD-ROM of EA weather data for 15 years or that of the standard EA weather data to save it on their respective computers. Furthermore, they can calculate solar irradiation on tilted surfaces facing any direction at any inclination angle and subterranean temperature at a certain depth.
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