A global database of anthropogenic heat emission (AHE) with high spatial resolution was constructed using a top-down approach. Annual average AHE was estimated from four heating components, based on different sectors of energy consumption. A population-adjustment using nighttime light was created to improve estimating AHE spatial variability in urban areas. A sensitivity function of AHE relative to temperature was derived to provide a way to evaluate AHE monthly variability globally.