主办单位:中国气象局沈阳大气环境研究所
国际刊号:ISSN 1673-503X
国内刊号:CN 21-1531/P

Journal of Meteorology and Environment ›› 2018, Vol. 34 ›› Issue (4): 18-25.doi: 10.3969/j.issn.1673-503X.2018.04.003

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Quantitative precipitation inversion algorithm based on the multi-radar mosaic I: dynamic Z-I relationships

JI Yong-ming1  JIANG Da-kai2  CHEN Chuan-lei REN Zhi-jie3  MENG Ying3  CAI Kui-zhi1  HU Peng-yu1  ZHANG Shuo1   

  1. 1. Liaoning Meteorological Disaster Monitoring and Early Warning Center, Shenyang 110166,China; 2. Liaoning Meteorological Administration, Shenyang 110166,China; 3. Liaoning Branch, China Meteorological Administration Training Center, Shenyang 110166,China
  • Received:2017-06-04 Revised:2018-01-22 Online:2018-08-31 Published:2018-09-03

Abstract:

Using the Doppler multi-radar mosaic data and surface precipitation data of encryption automatic stations in Liaoning province, the local dynamic Z-I relationships were established based on the optimization method to get the quantitative precipitation retrieval data with a real-time high spatiotemporal resolution. The method is used to retrieve the precipitation fields produced by typhoon " Meari" in 2011 and "Damrey" in 2012. The results show that the quantitative precipitation retrieval method can reproduce the main spatial distribution characteristics of the precipitation. . However, there is a large bias  in the strong precipitation center. In general, the retrieval  ability of quantitative precipitation for the local dynamic Z-I method is better than the fixed Z-I method. There is still systematic bias in the inversion data, i.e., overestimating the light rain and underestimating the heavy rain. For the heavy precipitation above 20.0 mm•h-1, the average error is greater than -10.0 mm and the average relative error is greater than 70.0%. Further analysis shows that the differences in the proportion of different magnitudes of precipitation and the differences in the regional climate conditions are the two main reasons for the precipitation inversion error. This knowledge provides a way for the improvement of radar quantitative precipitation inversion in the future.

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