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WANG Jin, YUE Zhiguo, HE Wenbin, DAI Changming, PAN Liujie, LIU Hui, ZHANG Lei. 2020: Research on the Z-R relationship of mixed convective-stratiform clouds in Xi'an area. Torrential Rain and Disasters, 39(4): 409-417. DOI: 10.3969/j.issn.1004-9045.2020.04.011
Citation: WANG Jin, YUE Zhiguo, HE Wenbin, DAI Changming, PAN Liujie, LIU Hui, ZHANG Lei. 2020: Research on the Z-R relationship of mixed convective-stratiform clouds in Xi'an area. Torrential Rain and Disasters, 39(4): 409-417. DOI: 10.3969/j.issn.1004-9045.2020.04.011

Research on the Z-R relationship of mixed convective-stratiform clouds in Xi'an area

  • Based on the raindrop spectrum data observed in Xi'an, Shaanxi Province from 2013 to 2014, and combined with the observation data of the weather radar, the mean raindrop distribution, the microphysical characteristic quantity and Z-R relationship of 43 precipitation events of the mixed convective-stratiform clouds were statistically analyzed. The results show that the mean raindrop spectrum of the precipitation display a single peak, and the fitting of the Gamma distribution to the large precipitation particles is obviously better than that of the M-P distribution. The drop size corresponding to the peak value of raindrop number concentration and having the greatest contribution to rainfall intensity appeared at less than 1 mm in diameter in the raindrop spectrum. A Z-R relationship Z=168R1.43 has been established by the least square method for the mixed convective-stratiform clouds in Xi'an area. When the echo intensity calculated from raindrop spectrum data is less than (greater than) 30 dBz, the radar observation can overestimate the echo intensity. With echo intensity decreasing, the radar echo intensity is obviously overestimated (underestimated). A 5-grade revised scheme for the radar echo is proposed. The Z-R relationship Z=168R1.43 was used to estimate the rainfall during the precipitation events of the mixed convective-stratiform clouds in Xi'an area. The estimated amount of precipitation is closer to the actually measured rainfall. The relative error of the estimated rainfall was reduced from 51.3% to 25.4%.
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