The lunar surface temperature (LST) derived from thermal infrared (TIR) measurements can aid in understanding the physical properties of the lunar surface. The Diviner Lunar Radiometer Experiment (herein, Diviner) sensor provides global lunar surface observation in seven TIR channels. However, its retrieval of LST constantly uses a single emissivity value (i.e., 0.95) by ignoring the spatial variation of lunar surface, thereby reducing the accuracy of temperature and day–night temperature difference. To overcome this problem, this study developed a physical method called temperature–emissivity separation (TES) algorithm to retrieve LST and lunar surface emissivity from the daytime observation in three Christiansen Feature (CF) channels (7.55–8.05, 8.10–8.40, and 8.38–8.60 μm) of the Diviner, and then used the emissivity from daytime observation to inverse LST at nighttime observation. Findings showed that the TES algorithm could retrieve LST and emissivity with an error of less than 0.8 K and 0.008, respectively. However, observation noise significantly affected the retrieval accuracy, particularly for the low‐temperature pixels; moreover, high retrieval accuracy requires a surface temperature higher than 240 K. The new algorithm was applied to obtain the daytime and nighttime LST and emissivity from the Diviner images. Results showed that the LST retrieved from the algorithm differed approximately 3.9 K from that calculated from a single emissivity 0.95. Finally, an example of global surface temperature and emissivity were obtained. Consequently, the CF pixels were found to distribute in the latitude range from −60° to 60°; however, they did not have a large distribution in high‐latitude and near‐polar regions.
