The estimation of snow parameters such as snow extent, snow depth and snow water equivalent are very important. They are parameters in land surface schemes and are very useful in snow disaster assessment. Passive microwave remote sensing has advantages in retrieving these parameters, especially snow depth. However, this technique has not been applied to monitor snow in Tibetan Plateau so far. So since last winter we tried to operationally monitor snow in this area by using SSM/I data, providing daily snow depth maps to the concerning sections of local government. In the meantime, the in-situ measurements of snow depth data in the Tibetan Plateau were collected to validate the retrieval algorithm employed in this study. In the paper, SSM/I images before and after a heavy snowfall were analyzed and compared with MODIS images. The results showed that the snow extent from SSM/I data is consistent with that from MODIS data, and snow depths from SSM/I are helpful for the assessment of snow disaster. However, compared with in-situ observations SSM/I derived snow depths are significantly overestimated. Since passive microwave remote sensing is almost transparently to atmosphere and cloud, it will play an important role in monitoring snow in the Tibetan Plateau, wih the retreival algorithm being improved. This will be more dominant when AMSR data are available.