A dataset of MODIS-based daily FSC time-series data with one kilo-meter spatial resolution in the Holarctic region (2000–2019)

Abstract

Fractional snow cover (FSC) is a quantitative description of the ratio of snow cover area (SCA) per image element to the spatial extent of the image element. Using the MODIS global surface reflectance product MOD09GA as the source data, this dataset takes advantage of the Google Earth Engine (GEE) platform to establish the Based NDVI Bivariate Linear Regression Model (BV-BLRM) showing the relation between the FSC and the Normalized Difference Snow Index (NDVI), and the Normalized Difference Snow Index (NDSI). Compared with the Root Mean Square Error (RMST) of MOD10A1 V6 data, the RMST of the FSC data prepared by the BV-BLRM has increased by 45%. Based on the model, we obtained a dataset of MODIS-based daily FSC time-series data with one kilo-meter spatial resolution in the Holarctic region (45°N to 90°N). The time series of this dataset is from February 24, 2000 to November 18, 2019, with a temporal resolution of one day and a spatial resolution of one km. The dataset is expected to provide quantitative information of snow distribution for regional climate simulation, hydrological models, etc.