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

利用1998年夏季青藏高原地面雷达和卫星微波辐射计的资料，研究了陆地降水的微波辐射特征，并通过推算降雨量和土壤湿度，同时考虑了地表不均匀的影响，发展了陆地地区的降水估算算法。将该算法应用于TRMM/TMI观测到的85 GHz和10 GHz亮温数据，成功地假定了降雨层的光学厚度和地表的土壤水分。通过将该假设光学厚度与中尺度区降水资料进行比较，证明了10天平均可以减少卫星采样频率对降水估算的影响，并根据假设光学厚度估算地表降水。与…相比在地面雷达观测到的降水垂直廓线中，降雪区尤其是融化层以上的厚度差异对光学厚度的估计有很大影响。其次，利用覆盖大气-地表的辐射传输模型，通过模拟选取对大气变化高度敏感的频带组合，计算出云水密度、水汽以及降雨强度、土壤湿度和地表温度。结合这些信息，我们开发了计算方法来！同时计算降雨强度和云水密度。在该方法中，首先利用不考虑水汽含量的土壤湿度算法计算地表微波发射率和地表温度。然后以该数值为边界条件，利用降雨强度和云水密度算法计算了大气中的水汽含量。其次，通过输入该值，我们利用迭代方法开发了计算土壤水分的算法。因此，明确了晴天、阴天、雨天的区别，但在定量估算降水时，仍需识别对地表粗糙度的影响。较少

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