Due to its capacity of long-time automatic observation, the Vaisala CL51 Ceilometer, which is a simple single wavelength lidar, has great potential to retrieve aerosol vertical profiles. However, the backscattering signals from ceilometers around 910 nm, which are seriously affected by background signals and water vapor absorption, strongly limits the performance of aerosol retrievals. To overcome this issue, a signal correction process would be crucial to reduce errors of backscattering signals of the CL51 ceilometer. Herein, we develop a signal correction method including background signal correction and efficient water vapor correction. Using the profile observed by the collocated Raman lidar as reference data, we demonstrate that the signal correction significantly improves the accuracy of aerosol measurements from the ceilometer, reducing the median relative error between the two instruments from 29.34% to 21.54%. Although the median error remains slightly above the generally acceptable level, the improvement is nonetheless evident and meaningful. We further indicate that the water vapor correction, based on the humidity profiles, has effectively scaled the underestimated ceilometer backscatter profiles, particularly under humid conditions. The water correction method is validated in Leipzig, and the results imply the effectiveness of water vapor correction in different locations. For individual profiles, at around 1.3 km, where the largest profile differences occur, the relative error between the original CL61 and PollyXT decreases from 28.0% to 13.2% after water vapor correction. Our findings underscore the importance of the ceilometer in capturing the vertical distribution of aerosols through refined signal processing, offering a practical approach for observing the atmosphere.