Abstract: A new dynamic approach to retrieving snow depth is developed based on integration of passive microwave remote sensing and in situ data.First,the snow-cover confidence index is established by use of both the passive microwave remote sensing and in situ data to identify the snow cover; second,a new dynamic parameterized scheme (the distance weighted method) is developed based on the index.The characteristics of the snow-depth retrieval approach arc as follows:on the one hand, for the difference issue of retrieval coefficients in different spatial-temporal circumstances,a solution is proposed that retrieval coefficients arc able to be adjusted according to real-time observed snow depth,which is the biggest difference from static retricval approaches;on the other hand,the advantage of spatial-temporal continuity of the passive microwave remote sensing da-to has been fully exploited,being able to retrieve the snow depth with relative high resolution and precision in the west China where few stations arc located.The results show that the approach implements the efficient integration of passive microwave remote sensing and observed data, exerts the advantages of different source data, improves obviously the retrieval precision in the western part of China and the south marginal regions of snow cover in eastern China, and solves the question in the old integrating approach that the area of snow cover was always relatively smaller than normal in the west China, amplifying the detectable coverage area of snow depth.In contrast to the static retrieval approach,the dynamic retrieval approach avoids efficiently the question that snow depth was overestimated in mountain regions and underestimated in plain regions.