Performance of a Radar Mosaic Quantitative Precipitation Estimation Algorithm Based on a New Data Quality Index for the Chinese Polarimetric Radars

• Main Authors: Yang Zhang, Liping Liu, Hao Wen
• Format: Article
• Language: English
• Published: MDPI AG 2020-10-01
• Series: Remote Sensing
• Subjects: polarimetric radar mosaic; quantitative precipitation estimation; bright band correction; radar data quality index
• Online Access: https://www.mdpi.com/2072-4292/12/21/3557

The quality of radar data is crucial for its application. In particular, before radar mosaic and quantitative precipitation estimation (QPE) can be conducted, it is necessary to know the quality of polarimetric parameters. The parameters include the horizontal reflectivity factor, <i>Z_H</i>; the differential reflectivity factor,<i> Z</i>_DR; the specific differential phase,<i> K</i>_DP; and the correlation coefficient, <i>ρ</i>_HV. A novel radar data quality index (<i>RQI</i>) is specifically developed for the Chinese polarimetric radars. Not only the influences of partial beam blockages and bright band upon radar data quality, but also those of bright band correction performance, signal-to-noise ratio, and non-precipitation echoes are considered in the index. <i>RQI </i>can quantitatively describe the quality of various polarimetric parameters. A new radar mosaic QPE algorithm based on <i>RQI</i> is presented in this study, which can be used in different regions with the default values adjusted according to the characteristics of local radar.<i> RQI</i> in this algorithm is widely used for high-quality polarimetric radar data screening and mosaic data merging. Bright band correction is also performed to errors of polarimetric parameters caused by melting ice particles for warm seasons in this algorithm. This algorithm is validated by using nine rainfall events in Guangdong province, China. Major conclusions are as follows. <i>Z_H</i>, <i>Z</i>_DR, and <i>K</i>_DP in bright band become closer to those under bright band after correction than before. However, the influence of <i>K</i>_DP correction upon QPE is not as good as that of <i>Z_H</i> and <i>Z</i>_DRcorrection in bright band. Only <i>Z_H</i> and <i>Z</i>_DR are used to estimate precipitation in the bright band affected area. The new mosaic QPE algorithm can improve QPE performances not only in the beam blocked areas and the bright band affected area, which are far from radars, but also in areas close to the two radars. The sensitivity tests show the new algorithm can perform well and stably for any type of precipitation occurred in warm seasons. This algorithm lays a foundation for regional polarimetric radar mosaic precipitation estimation in China.