Mapping High-Resolution Surface Shortwave Net Radiation From Landsat Data

Maps of high-resolution surface shortwave net radiation (SSNR) are important for resolving differences in the surface energy budget at the ecosystem level. The maps can also bridge the gap between existing coarse-resolution SSNR products and point-based field measurements. This study presents a modified hybrid method to estimate both instantaneous and daily SSNR from Landsat data. SSNR values are directly linked to Landsat top-of-atmosphere reflectance by extensive radiative transfer simulation. Regression coefficients are pre-calculated and stored in a look-up table (LUT). Atmospheric water vapor is a key parameter affecting SSNR, and three methods of treating water vapor are evaluated in this study. Comparison between Landsat retrievals and field measurements at six AmeriFlux sites shows that the hybrid method with water vapor as a dimension of LUT can estimate SSNR with a root mean square error of 77.5 W/m(2) (instantaneous) and 36.1 W/m(2) (daily). The method of water vapor correction produces similar results. However, a generic LUT that covers all levels of water vapor results in much larger errors.