Abstract
Land surface emissivity (LSE) in the infrared (IR) window region (8–12 μm) governs the thermal emissions from the Earth's surface. Many LSE databases, retrieved from various satellite instruments, are available for studying climate, Earth‐atmosphere interaction, weather, and the environment. The precision (standard deviation) and accuracy (bias) of these databases remain unclear. In this study, we introduce an objective and efficient method for quantitatively evaluating the LSE precision using satellite radiance observations. The LSE brightness temperature (Tb) deviations, defined as the standard deviations of Tb differences between satellite observations and radiative transfer calculations, can be estimated by minimizing the impacts from land surface temperature (LST) and atmospheric profiles. This is followed by the estimation of LSE precision. This method does not need the true LSE measurements. It only needs ancillary information such as atmospheric profiles and LST, both of which do not require high accuracy and thus can be obtained from a numerical weather prediction forecast or analysis. The method is applied to six different monthly LSE databases from August 2006 and 2007, and the results are presented. The error sources affecting the method are identified and the sensitivity to these errors is studied.
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