Quantification of Precipitation Using Polarimetric Radar Measurements during Several Typhoon Events in Southern China - Qiulei Xia; Wenjuan Zhang; Haonan Chen; Wen-Chau Lee; Lei Han; Yu Ma; Xiantong Liu (Remote Sensing, 2020)
Accurate quantitative precipitation estimation (QPE) during typhoon events is critical for flood warning and emergency management. Dual-polarization radar has proven to have better performance for QPE, compared to traditional single-polarization radar. However, polarimetric radar applications have not been extensively investigated in China, especially during extreme events such as typhoons, since the operational dual-polarization system upgrade only happened recently. This paper extends a polarimetric radar rainfall system for local applications during typhoons in southern China and conducts comprehensive studies about QPE and precipitation microphysics. Observations from S-band dual-polarization radar in Guangdong Province during three typhoon events in 2017 are examined to demonstrate the enhanced radar rainfall performance. The microphysical properties of hydrometeors during typhoon events are analyzed through raindrop size distribution (DSD) data and polarimetric radar measurements. The stratiform precipitation in typhoons presents lower mean raindrop diameter and lower raindrop concentration than that of the convection precipitation. The rainfall estimates from the adapted radar rainfall algorithm agree well with rainfall measurements from rain gauges. Using the rain gauge data as references, the maximum normalized mean bias ( <semantics> N M B </semantics> ) of the adapted radar rainfall algorithm is 20.27%; the normalized standard error ( <semantics> N S E </semantics> ) is less than 40%; and the Pearson’s correlation coefficient ( <semantics> C C </semantics> ) is higher than 0.92. For the three typhoon events combined, the <semantics> N S E </semantics> and <semantics> N M B </semantics> are 36.66% and -15.78%, respectively. Compared with several conventional radar rainfall algorithms, the adapted algorithm based on local rainfall microphysics has the best performance in southern China.