Budget Amount *help |
¥3,100,000 (Direct Cost: ¥3,100,000)
Fiscal Year 2005: ¥1,000,000 (Direct Cost: ¥1,000,000)
Fiscal Year 2004: ¥1,000,000 (Direct Cost: ¥1,000,000)
Fiscal Year 2003: ¥1,100,000 (Direct Cost: ¥1,100,000)
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Research Abstract |
The purpose of this study is, firstly, to develop the method to statistically express the precipitation characteristics utilizing the satellite remote sensing data. Secondly, we aimed at clarifying the effect of large-scale climatic conditions on the precipitation characteristics, by analyzing the observed relationships between the tropical climatic conditions and characteristics of the precipitation systems. In the first fiscal year (2003), we performed statistic analyses utilizing the Tropical Rainfall Measuring Mission (TRMM)'s Precipitation Radar (PR) data. We successfully developed a method to classify the dominant precipitation systems, such as afternoon shower, organized systems, extratropical frontal systems, from the statistical characteristics of precipitation observed from TRMM PR, for every 3 months and for every 2.5 x 2.5 degrees grid (Katayama and Takayabu). In the second year (2004), we examined the relationship between the sea surface temperature obtained from the TRMM Microwave Imager (TMI) data and the oceanic precipitation characteristics. We also examined the relationship between the tropical cumulus convection and the atmospheric stratification (Takayabu and Yokomori). Furthermore, we processed the TRMM PR and TMI data and produced their match-up data for the study of utilizing TMI data to retrieve the precipitation characteristics suggested from PR statistics. In the last year (2005), we made statistical analyses of the match-up data to find the method to realize the precipitation-type classifications which was developed with PR data in the first year (Katayama and Takayabu method), utilizing the TMI data. As a result, we could find a significant relationship between the precipitation characteristics expressed with TMI data and those with PR data, suggesting a possibility of utilizing TMI data to determine the precipitation characteristics from space.
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