National Aeronautics and Space Administration

Surface incident shortwave radiation (ISR) is a crucial parameter in the land surface radiation budget. Many reanalysis, observation-based, and satellite-derived global radiation products have been developed but often have insufficient accuracy and spatial resolution for many applications. In this paper, we propose a method based on a radiative transfer model for estimating surface ISR from Moderate Resolution Imaging Spectroradiometer (MODIS) Top of Atmosphere (TOA) observations by optimizing the surface and atmospheric variables with a cost function. This approach consisted of two steps: retrieving surface bidirectional reflectance distribution function parameters, aerosol optical depth (AOD), and cloud optical depth (COD); and subsequently calculating surface ISR. Validation against measurements at seven Surface Radiation Budget Network (SURFRAD) sites resulted in an R² of 0.91, a bias of 6.47 Wm², and a root mean square error (RMSE) of 84.17 W/m² (15.12%) for the instantaneous results. Validation at eight high-latitude snow-covered Greenland Climate Network (GC-Net) sites resulted in an R² of 0.86, a bias of 21.40 W/m², and an RMSE of 84.77 W/m² (20.96%). These validation results show that the proposed method is much more accurate than the previous studies (usually with RMSEs of 80-150 W/m²). We further investigated whether incorporating additional satellite products, such as the MODIS surface broadband albedo (MCD43), aerosol (MOD/MYD04), and cloud products (MOD/MYD06), as constraints in the cost function would improve the accuracy. When the AOD and COD estimates were constrained, RMSEs were reduced to 62.19 W/m² (12.12%) and 71.70 W/m² (17.74%) at the SURFRAD and GC-Net sites, respectively. This algorithm could estimate surface ISR with MODIS TOA observations over both snow-free and seasonal/permanent snow-covered surfaces. The algorithm performed well at high-latitude sites, which is very useful for radiation budget research in the polar regions.