The Use and Potential of Far-Infrared Remote Sensing in Deriving Surface Longwave Downward Radiation under Clear-Sky Conditions

Abstract Surface longwave downward radiation (LWDR) is an essential parameter in Earth’s radiation balance and climate change studies. To date, almost all existing space-based LWDR studies mainly focus on the traditional thermal infrared (TIR) spectrum of 4–15 μ m. The far-infrared (FIR) spectrum (>15 μ m), with its high sensitivity to temperature and water vapor, has the potential to greatly improve the derivation accuracy of LWDR, which is closely related to the above variables. This study proposes a novel attempt to estimate clear-sky LWDR by integrating the traditional TIR bands and newly selected FIR bands. Through comprehensive simulations and analyses, we identify that the FIR bands can serve as an essential complement to existing TIR-based methods, thereby significantly improving the accuracy of LWDR estimation and yielding a 16% overall accuracy improvement. This substantial potential for enhanced accuracy is particularly evident under conditions of low water vapor content or in polar atmospheres, where improvements exceed 23%. This research represents the first incorporation of FIR into longwave radiation estimation fields, highlighting a promising advancement in remote sensing techniques. The findings inspire further exploration of FIR’s potential and lay the groundwork for a deeper understanding of LWDR and the complexities of Earth’s radiation balance, ultimately aiding in more accurate assessments of climate change. Significance Statement Integrating far-infrared into longwave downward radiation estimation marks a significant advancement beyond traditional thermal infrared methods. This study demonstrates that adding FIR data greatly enhances longwave downward radiation (LWDR) accuracy, especially in extreme environments like polar regions and areas with low water vapor, where TIR alone struggles to provide precise estimates. With improving accuracy by up to 23% in polar regions and 16% globally, this approach offers a more reliable understanding of Earth’s radiation budget. These findings are crucial for refining climate models and designing future satellite missions, ultimately supporting better climate predictions and strategies to address climate change.