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Piling and melting of snow cover is a dynamic process which has important effect on the radiation balance, and water circulation over the land surface. Accurate information on snow depth is essential for the study of hydrology and climatology. However, it is almost impossible to obtain any long-term and annual variability characteristics of snow covers by means of conventional field observations. Passive microwave remote sensing has the advantage to penetrate the cloud, and its all-weather capability for snow cover monitoring makes it superior to the optical sensor and near-infrared remote sensing techniques. By means of daily snow cover monitoring data derived from SMMR and SSM/I during the period from 1979 to 2005, snow depth and snow cover days over the northern China were quantitatively analyzed. Spatio-temporal variations of snow covers were evaluated in terms of spatial-temporal distribution and the significant level by the Mann-Kendall rank statistical test. The results suggested that the snow-cover periods became notably shorten and the snow depth turned to decrease obviously with the significant level of alpha<0.01 in the desert of northwest arid region under the significant warming trend. In contrast, the snow depth tended to increase notably with the significant level of alpha<0.001 in the northwest alpine region and Xiaoxing'an Mountain, where the climate tended to be much warm and humid at the same period.