About 70% of annual precipitation in Beijing area happens in summer season. With more requirements from the municipal government for city management and the public life for this capital city, more accurate quantitative precipitation estimation plays an important role in improving weather forecasting service. By using data collected from Beijing Meteorological Bureau's (BMB) mesoscale weather observation system, including a S-band Doppler radar, a C-band dual-polarization radar, and a dense Automatic Weather Station (AWS) network in Beijing area, several summer rainfall cases are investigated. The rainfall rate R, derived from C-band dual polarization radar, is estimated by using a variety of algorithms based on reflectivity ZH, differential reflectivity ZDR and specific differential phase KDP. For phase wrapping, noise and fluctuation, data quality control is conducted in processing the differential propagation phase PHIDP before using PHIDP to estimate KDP. Besides, ground clutters elimination and attenuation was considered for this C-band system during heavy rainfall. By using R(ZH), R(ZH,ZDR), R(KDP,ZDR), R(KDP) algorithms, different QPE results from C-band dual-polarized radar are compared together with the result from the operational S-band Doppler radar based Z-R relationship. Observations from the AWS network are used to analyze estimation error for the above algorithms. The evaluating results show that rainfall estimation from R(KDP) is superior to the other methods in heavy rainfall cases.
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