A Direct Estimation Method for Daily Mean Albedo With Multiple Observations From FY-4A AGRI and Himawari-8 AHI

Abstract

Surface albedo plays a significant role in Earth’s energy budget and global climate change. The spaceborne remote sensing technique is efficient for deriving and monitoring long-term surface albedo over large regions. Numerous satellite surface albedo products have been established and used for climate change research. However, the surface daily mean albedo is not regularly produced from satellite observations, even though it is more critical than instantaneous albedo for calculating daily shortwave radiation budget. Compared to polar-orbiting satellites, the geostationary satellites offer greater potential for mapping daily albedo with more diurnal observations. This study proposes an innovative multisensor combined direct estimation algorithm, which takes advantage of multiple clear-sky observations from new-generation geostationary satellite sensors FengYun-4 Advanced Geostationary Radiation Imager (AGRI) and Himawari-8 Advanced Himawari Imager (AHI) taken during the same day to improve the surface albedo estimation. Compared to albedo estimates derived from a single sensor, the root mean squared error (RMSE) decreases from 0.030 to 0.022 at OzFlux sites and from 0.040 to 0.031 at Heihe sites. Moreover, an information index of top-of-atmosphere (II_TOA) reflectance is proposed to quantify the amount of information that multiangular TOA observations carry in the surface albedo estimation. As a result, combining observations from two sensors increases such information by 20%, as compared to observations from a single sensor. This study demonstrates the combined multisensor direct estimation method has significant potential for improving surface albedo estimation.