Cloud-Free Fractional Snow Cover Estimation from Blended MODIS and FY-2 VISSR Measurements

Abstract

Fractional snow cover from Low-Earth-Orbit (LEO) satellites often encounters data gaps mainly caused by cloud obscuration in one or two observations in a single day. Imagers onboard GEOstationary (GEO) satellites have hourly or more frequent observations, making it possible to reduce cloud obscuration significantly. To map daily cloud-free fractional snow cover, we present a way using blended measurements from Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and FengYun-2 Visible and Infrared Spin Scan Radiometer (FY-2 VISSR). The fractional snow cover from MODIS is estimated using the Multiple End-member Spectral Mixture Analysis (MESMA), while that from FY-2 VISSR is generated using a simple linear interpolation between snow and snow-free end-members. Quickly-moving clouds can be alleviated mainly by the utilization of FY-2 VISSR multi-temporal data. Then spatio-temporally continuous daily fractional snow cover results from the removal of remaining clouds through the interpolation pixel by pixel in time series of snow fraction.