Abstract:This paper describes a quality control (QC) algorithm for reflectivity factor data of dual-channel millimeter-wave cloud radar (MMCR) in different regions. The data used for test sample are from the 15 MMCR stations which are the first batch of MMCR approved for operational use in China. The algorithm provides a method of automatically identifying the QC threshold parameters of reflectivity factor （Z） and linear depolarization ratio (LDR), combined with filtering check and continuity check, etc., and can effectively eliminate non-meteorological echoes. The method is based on the distribution characteristics between the cloud or rain echoes and suspended matter clutter in the MMCR data. It classifies and labels the cloud or rain echoes and suspended matter clutter samples from the 15 stations in 2023. Based on the intersection points of the frequency curves of the two types of echoes, the QC threshold parameters for Z and LDR at each station can be got rapidly. In addition, this paper compares the correlation coefficient, average deviation and root mean square error of cloud heights calculated from the MMCR data before and after QC and radiosonde data at different stations and during different observation periods, and discusses the effectiveness of the QC method. The results show that non-meteorological echoes in the data can be effectively removed after QC, especially the low-level suspended matter clutter. Its correlation coefficient increases from 0.47 to 0.91 with radiosonde-identified cloud base height, and increases from 0.80 to 0.87 with cloud top height. The calculated cloud heights after QC are more reasonable. So, the data after QC can enhance the consistency of the cloud height data between MMCR and radiosonde.