Estimation of Snow Water Equivalent in the Tibetan Plateau Using Passive Microwave Remote Sensing Data (SSM/I)
CHE Tao,LI Xin,GAO Feng (Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou Gansu 730000, China)
Snow depth and snow water equivalent are the most import factors in the hydrologic model and climate model. So far, there is not an operational algorithm to estimate the snow water equivalent from passive microwave remote sensing data (SSM/I) in the Tibetan Plateau. In this study the SSM/I brightness temperature data in January 1993 are used to estimate the snow water equivalent SWE in the plateau. The frequencies of SSM/I data used to retrieve snow depth are 19 and 37 GHz in horizontal polarization. The results show that all available algorithms overestimate the snow depth in the Tibetan Plateau. In this paper the reasons of overestimation of snow depth from several aspects are analyzed, such as the water content of snow pack, large water bodies (e.g. lakes), and the abnormal field snow depth data. After eliminating some futile data (including the passive microwave brightness temperature values and snow depth data in the weather stations), an improved algorithm has been established to retrieve the snow depth from the difference of 19 and 37 GHz brightness temperatures in horizontal polarization. Here, snow density is obtained by a time function of fresh snow density. The snow depth and density were converted to the snow water equivalent, and are regarded as the ground truth. In finally, the TB vertically polarized differences of 19 and 37 GHz are regressed with the SWE. Using the statistical method, a simple and practical algorithm is developed to estimate the snow water equivalent from the differences of 19 and 37 GHz in vertical polarization.