High Mountain Asia is an Asian high altitude area with the Tibetan Plateau as the main area and is also an important distribution area of low and middle latitude mountain snow. The dynamic changes of snow in this area have important effects on water, energy balance, and regional climate. As the seasonal snow in the Tibetan Plateau has the characteristics of short storage time and thin snow cover, it is urgent for the understanding of water circulation to monitor the snow cover on day time scales. The dataset is based on MODIS normalized snow index data with the spatial resolution of 500 meters, combing with the terrain data and advantages of a variety of snow cover estimation algorithm under the cloud cover, gradually realizes re-estimation of snow cover under the conditions of cloud cover, meets the need of cloud under 10％ and finally produces “Daily Fractional Snow Cover (FSC) Data set over High Asia (2002–2018)”. Then select binary snow products under cloud-free conditions as a reference to carry out a comparison of cloud distribution and total area time series of two products, the results show that fractional snow cover products accord with binary snow products in both space and time. In the case of the winter of 2013, when the value of fractional snow cover is greater than 50％, the relevance of two products is up to 0.8628. This data set is expected to provide high-temporal-resolution data input for the dynamic monitoring of snow over High Mountain Asia and the research of climate environment, hydrological and energy balance, and disaster assessment.
