Study on the variations of tropical precipitation characteristics associated with varying climate conditions

本研究的目的是，首先，发展一种利用卫星遥感资料统计表示降水特征的方法。第二，通过分析热带气候条件与降水系统特征之间的观测关系，阐明大尺度气候条件对降水特征的影响，在第一个财政年度（2003年）利用热带降雨测量使命（TRMM）的降水雷达（PR）资料进行了统计分析。我们成功地开发了一种方法，根据TRMM PR每3个月和每2.5 x 2.5度网格的降水统计特征，对主要降水系统进行分类，如午后阵雨、有组织系统、热带外锋系统（片山和高谷）。在第二年（2004年），我们研究了TRMM微波成像仪（TMI）数据获得的海表温度与海洋降水特征之间的关系。我们还研究了热带积云对流和大气层结（高谷和横森）之间的关系。在此基础上，对TRMM PR和TMI资料进行了处理，得到了它们的匹配数据，用于研究利用TMI资料反演PR统计量所反映的降水特征，并在最后一年（2005年）对匹配数据进行了统计分析，探讨了第一年利用PR资料实现降水类型分类的方法（Katayama和Takayabu方法），利用TMI数据。结果表明，TMI资料与PR资料所反映的降水特征之间存在着显著的相关性，这为利用TMI资料从空间上确定降水特征提供了可能。

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.