Quality Control and Evaluation for Reflectivity Data of Millimeter-Wave Cloud Radar
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Abstract:
This paper describes a quality control (QC) algorithm for reflectivity data of dual-channel millimeter-wave cloud radar (MMCR) in different regions.The data for the research from the 15 MMCR stations which were the first batch of MMCR to be approved for operational use in China.The algorithm provides a method for automatically identifying the QC threshold parameters for reflectivity(Z)and linear depolarization ratio (LDR), combined with filtering check and continuity check, etc., which can effectively eliminate non cloud and non rain echoes.The method is based on the distribution characteristics between the cloud or rain echoes and clutter in the MMCR data. It classifies and labels the cloud or rain echo and 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 reflectivity(Z)and linear depolarization ratio (LDR) for each station can gets rapidly. By comparing the correlation coefficient, average deviation and root mean square error of cloud heights calculated from the MMCR data before and after quality control and radiosonde data at different stations and during different observation periods.The effectiveness of the QC method is discussed.The results show that non-meteorological echoes in the data can be effectively removed after QC,especially low-level suspended clutter. The correlation coefficient with radiosonde-identified cloud base height increases from 0.47 to 0.91, and the correlation coefficient with cloud top height increases from 0.80 to 0.87. That improved that the calculated cloud heights after QC more reasonable. The data after QC can enhances the consistency between the cloud height data of MMCR and radiosonde.