Development of an Algorithm for Precipitation over Land by Using Space-based Precipitation Radar and Microwave Radiometer

利用天基降水雷达和微波辐射计开发陆地降水算法

• 批准号: 12450196
• 负责人: KOIKE Toshio
• 金额: $ 7.04万
• 依托单位: The University of Tokyo
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (B)
• 财政年份: 2000
• 资助国家: 日本
• 起止时间: 2000 至 2001
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-12450196/
• 关键词: Remote sensing; Microwave radiometer; Space-based Precipitation Radar; Precipitation; Snowfall; Algorithm

The data from ground based radar and satellite based microwave radiometer acquired on the Tibetan Plateau in summer 1998, enabled us to investigate the microwave radiometric characteristics of land precipitation, and to develop the precipitation estimation algorithm over land area, taking into account of the effects of land surface non-uniformity by inferring rain fall and soil moisture at the same time. And further more we succeeded in assuming the optical thickness on the rainfall layer and the soilmoisture of the land surface, by applying this algorism to the brightness temperature data at 85 GHz and 10 GHz, observed by the TRMM/TMI. In consequence of comparing this assumed optical thickness with precipitation data in meso scale area, it is proved that 10-day average makes it possible to reduce the effects on the precipitation estimation by the satellite-oriented sampling frequency, and to estimate the land surface precipitation from the assumed optical thickness. When compared with … More the vertical profile of rainfall observed by the ground based radar, the thickness difference in the area of snowfall especially above the melting layer affects strongly on the estimation of optical thickness.Next, with the radiometric transmission model covered atmospheric-land surface in a lump, we figured out cloud water density, water vapor, as well as rainfall intensity, soil moisture, and land surface temperature, selected by simulation the combination of the frequency zone with high sensitive to atmospheric variable. Together with this information, we developed the calculation method to! figure out rainfall intensity and cloud water density simultaneously. In this method, firstly we calculate microwave emissivity from the land surface and surface temperature, by algorithm for soil moisture without taking the value of water vapor into consideration. Then using this figure as a boundary condition, we calculate the value of water vapor in the air by the algorithm for rainfall intensity and cloud water density. Next, by inputting this value, we develop the algorithm for soil moisture by using iteration method. As a result, it is clarified to distinguish fine, cloudy, from rainy, but it still needs to identify the effects on the surface roughness of the land for the quantitative estimation of precipitation. Less

利用1998年夏季青藏高原地面雷达和星载微波辐射计资料，研究了陆地降水的微波辐射特征，建立了考虑陆面非均匀性影响的降水估算方法，同时估算了降水量和土壤湿度。利用TRMM/TMI的85 GHz和10 GHz亮温资料，成功地假定了降雨层的光学厚度和地表的土壤湿度。通过与中尺度地区降水资料的比较，证明了采用10天平均可以减小卫星定位采样频率对降水估算的影响，并可以利用光学厚度估算陆面降水。较 ...更多信息 根据地面雷达观测到的降水垂直廓线，降雪区特别是融化层以上的厚度差异对光学厚度的估算有很大的影响.其次，利用覆盖大气-陆地表面的辐射传输模型，计算了云水密度、水汽以及降水强度、土壤湿度和地表温度，通过模拟选择了对大气变量敏感度高的频段组合。结合这些信息，我们开发了计算方法，以！同时计算降雨强度和云水密度。该方法首先根据地表温度和地表温度计算微波发射率，然后根据土壤湿度计算微波发射率，而不考虑水汽的影响。然后以此为边界条件，利用雨强和云水密度的算法计算出大气中的水汽含量。然后，通过输入这个值，我们开发了土壤湿度的算法，使用迭代法。因此，它是明确区分晴，多云，从下雨，但它仍然需要识别的影响，对地面粗糙度的降水量的定量估计。少