Large areas of the Tibetan plateau are only covered by a sparse network of ground snow sampling stations, while the snow cover is highly heterogeneously distributed due to wind, topography etc
. Nevertheless, the snow accumulation and spatial patterns play an important role in the hydrological cycle. It releases moisture during the dry spring period before the onset of the monsoon season. Widely used MODIS snow cover products have been available globally since 2002. The understanding of the temporal and spatial distribution of snow cover in a given region calls for a comprehensive data representation method. In this paper a method to visualize both spatial and temporal aspects of snow cover distribution from MODIS 8-day composite data is presented. It is based on RGB display of the snow cover data which is grouped according to season. The RGB syntheses of snow cover distribution (RSD) were generated for the Nam Co Basin in the central part of the Tibetan Plateau during the years of 2002–2009. An alternating pattern of monsoon and autumn snow cover was identified in the western part of the basin which corresponds to the biennial character of the variations of the Indian monsoon. Monsoon snow cover was found in RSD images for the years 2002, 2004 and 2008 whereas in years 2003 and 2009 the autumn snow cover is dominant. The eastern part of the basin does not follow this general pattern since it is affected by the so called “lake effect”, which is a snow fall induced by the passing of dry and cold westerlies over the lake surface during the winter months. The years 2002, 2006 and 2007 were identified as years with a particularly strong lake effect from the RSD images. Areas with permanent snow cover and areas that were snow free were both found to be relatively stable. Comparison of the lake effect at Nam Co with nearby Siling Co, where the lake effect is smaller or absent, suggests that the presence of an effective barrier on the opposite side of the lake is a prerequisite for the occurrence of the strong lake effect.