Jian Shang, Peng Zhang, Lei CAO, Qiong Wu, Xiaopeng Wang, Xiaowen ZHANG, Bosen JIANG, Honggang YIN, Mei YUAN, Da LIU, Yubao Chen, Songyan Gu. 2025: The Comparison of Precipitation Measurement Radar onboard FY-3G Meteorological Satellite with the Ground-based Radars in China. Adv. Atmos. Sci., https://doi.org/10.1007/s00376-025-5149-3
Citation: Jian Shang, Peng Zhang, Lei CAO, Qiong Wu, Xiaopeng Wang, Xiaowen ZHANG, Bosen JIANG, Honggang YIN, Mei YUAN, Da LIU, Yubao Chen, Songyan Gu. 2025: The Comparison of Precipitation Measurement Radar onboard FY-3G Meteorological Satellite with the Ground-based Radars in China. Adv. Atmos. Sci., https://doi.org/10.1007/s00376-025-5149-3

The Comparison of Precipitation Measurement Radar onboard FY-3G Meteorological Satellite with the Ground-based Radars in China

  • China launched its first spaceborne Precipitation Measurement Radar (PMR) on FY-3G satellite in April 2023. To achieve the scientific goal of measuring three-dimensional precipitation structure, evaluating the quantitative measurement ability of the PMR is critical. China operates more than 250 weather radars over the mainland. The consistency of the spaceborne radar with the ground-based radars will enhance precipitation measurement ability especially over oceans and mountains where observations are sparse. Additionally, the spaceborne radar can be used to evaluate the spatial and temporal homogeneity of the ground-based radar network. This paper focuses on comparing the PMR onboard the FY-3G satellite with the S-band Chinese new generation weather radar CINRADs. A comparison algorithm between the PMR and the CINRADs has been developed, incorporating detailed quality control, attenuation correction, data optimization, spatial-temporal matching, non-uniform beam filling constraint, uniformity constraint, and frequency correction. The matched data in typical months of four seasons were selected to carry out the comparison. The data consistency between the PMR and the CINRADs has been analyzed. The correlation coefficient is 0.87, the deviation is 0.89 dB, and the standard deviation is 2.50 dB, based on 98226 matching samples. The results show the radar reflectivity of the PMR is quite comparable to the CINRADs, demonstrating that the PMR data quality is satisfying and can be used to verify and correct data consistency among multiple ground-based radars. This work also paves the way for data fusion and joint application of satellite and ground radars in the future.
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