Improved snow depth retrieval algorithm in China area using passive microwave remote sensing data

Abstract

Snow depth (SD) is an important input parameter for snow cover hydrologic model and climate model. In China, the snow volume is affected by the plateau climate and different geographical situation, which shows specific rules and characteristics in space and time distribution. Consequently, it is very necessary to dynamically estimate the snow volume of China area. In this paper, we use passive microwave to estimate the snow depth in China, through the analysis on the characteristics of time, space and geographical environment of the snow zone in China, we added the impact of snow cover in pixel, high-frequency (89.0 GHz) on the accuracy of inversion and on the basis Chang's classical algorithm of inversion of snow water equivalent, considered that there were different responses to the microwave in different types of surface, improve the algorithm of inversion of snow water equivalent in China. The results show that new inversion algorithm can improve the precise of the inversion of snow depth in the area of China. However, the low spatial resolution of microwave, complex types of feature in the ground pixel and the changes of the snow status with time and space, which make it difficult to invert snow water equivalent, so need to further study.