An algorithm for detection and correction of the lunar contamination in the Advanced Microwave Sounding Unit–A (AMSU-A) data is applied to study the observed lunar contamination in the NOAA 18 AMSU-A data. The algorithm is based on a physical model of the lunar surface brightness temperature and the AMSU-A antenna pattern powers to detect the lunar contamination in cold space calibration counts over a large number of scans. The algorithm performs a scan-by-scan detection and correction of the effect of lunar contamination on the AMSU-A data. It is found that the lunar contamination is significant only when the separation angle between the lunar disk and the antenna space viewing is less than 4°, beyond which no significant lunar contamination is detected, as the AMSU-A antenna power drops below 40 dB from its peak. The parameters of the AMSU-A antenna pattern powers are determined from least squares fit to the observed lunar contamination counts extracted from the cold space counts. Using the best fit parameters, we investigated the effect of the lunar contamination on the AMSU-A scene temperatures. It is found that the differences ΔTS between the near-nadir (field of view, FOV 16) scene antenna temperatures calculated with and without correction of lunar contamination vary with channels. It is about 1.5 K over ocean at channels 1 and 2 but only 0.38 K at channel 4. This trend in the ΔTS variation as a function of channels is easily understood by examining the two-point calibration equation. The results presented in this study show that the lunar contamination in the AMSU-A space calibration counts can be accurately detected and that its effect on the measured scene antenna temperatures can be corrected. The algorithm provides a practical approach for scan-by-scan correction of the lunar contamination in AMSU-A data and improves the accuracy of operational calibration of NOAA Level 1B data. An assessment of the postlaunch instrument performance is also presented.