By combining optical remote sensing snow cover products with passive microwave remote sensing snow depth (SD) data, we produced a MODIS (Moderate Resolution Imaging Spectroradiometer) cloudless binary snow cover product and a 500 m snow depth product. The temporal and spatial variations of snow cover from December 2000 to November 2014 in China were analyzed. The results indicate that, over the past 14 years, (1) the mean snow-covered area (SCA) in China was 11.3 % annually and 27 % in the winter season, with the mean SCA decreasing in summer and winter seasons, increasing in spring and fall seasons, and not much change annually; (2) the snow-covered days (SCDs) showed an increase in winter, spring, and fall, and annually, whereas they showed a decrease in summer; (3) the average SD decreased in winter, summer, and fall, while it increased in spring and annually; (4) the spatial distributions of SD and SCD were highly correlated seasonally and annually; and (5) the regional differences in the variation of snow cover in China were significant. Overall, the SCD and SD increased significantly in south and northeast China, and decreased significantly in the north of Xinjiang province. The SCD and SD increased on the southwest edge and in the southeast part of the Tibetan Plateau, whereas it decreased in the north and northwest regions.

The Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra daily snow cover product MOD10A1 was compared with in situ climate station measurements and a snow map generated from Landsat Enhanced Thematic Mapper Plus (ETM+) data. Snow-covered area (SCA) dynamics were assessed using the MODIS 8-day snow cover composite product MOD10A2 for the 2001–2005 snow seasons in northern Xinjiang, China. The results indicate that the snow-mapping agreement between MODIS daily snow maps and surface observations is high at 94.6% over the four snow seasons under clear-sky conditions. The snow classification accuracy in a mountainous area was lower than that in a plain area and caused higher omission errors, probably resulting in an underestimation of the SCA. The omission errors were mainly determined by snow depth, land cover types, the terrain and mixed pixels. The cloud agreement was 95.9%, and approximately 4.1% of cloud was misclassified as snow when the sky view at the climate stations was covered by clouds. An improvement was found in suppressing clouds using the 8-day products, with MOD10A2 reducing about 88.4% of the average cloud cover compared with MOD10A1. SCA in northern Xinjiang retrieved using MOD10A2 shows a clear seasonal trend. The air temperature plays an important role in the fractional SCA, and the spatial distribution of the snow cover differs considerably in the various areas in the northern Xinjiang region.