ALBEDO RETRIEVING FROM DSCOVR/EPIC DATA AND PRELIMINARY VALIDATION
Land surface albedo plays an important role in climate change research. Satellite remote sensing has the characteristic of wide observation range, and it can make repeated observations on the same area. Therefore, using the remote sensing data to retrieve surface albedo becomes a main method to obtain the surface albedo in a wide range or even on a global scale. However, the time resolution of existing albedo products is usually low, which has a great impact on the analysis of rapid changes in surface vegetation and the climate change research. The Deep Space Climate Observatory (DSCOVR) was launched to a sun-earth first Lagrange point (L1) orbit, which is a new and unique vantage point to observe the continuously full, sunlit disk of Earth. DSCOVR can provide observation data with high time resolution, therefore, it is necessary to explore the feasibility of the new sensor DSCOVR/EPIC inversion of the daily albedo product. The relationship between the surface broadband albedo and the surface reflectance was established, and then the surface albedo with high temporal resolution was calculated using the DSCOVR/EPIC data. The Inner Mongolia Autonomous Region and parts of the Sahara Desert were selected to verify the accuracy of DSCOVR albedo compared with MODIS albedo. The results show that the correlation coefficients between DSCOVR albedo and MODIS albedo are greater than 0.7 and RMSE are less than 0.05 both in visible band and shortwave band. It can be seen that this method can be used for the albedo retrieval using DSCOVR/EPIC data.