Quality Control And Effect Tests Of Doppler Radar Data

Serious quality problems such as ground clutter,velocity ambiguity and distance folding et al.may occur in data detected by Doppler weather radar.The radar data without quality control will have important negative influence on quantitative precipitation estimation and data assimilation.China has built a nationwide weather radar network,and the quality of radar data is a hot topic among experts and scholars at present.At first,based on fuzzy logic,this paper explores the use of three basic variables reflectivity,radial velocity and velocity spectrum width detected by conventional Doppler radar,using the data of Guangzhou SA band radar for different types of features,to identify and eliminate non-precipitation echo,and uses the upper elevation echo data to fill the echo hole after the removing of ground clutter,to improve the effect of the algorithm.On this basis,using C-band dual polarization radar data of Nanjing University of Information Science and Technology,the paper proposed a "mixed"method consisting of fuzzy logic and threshold method,and classified the non-precipitation echo in different types of precipitation echo,as well as the typical clear-air echo alone and zero-centigrade-layer bright band in stratiform cloud processing.The results show that the proposed algorithm based on dual polarization radar can effectively identify non-precipitation echoes in the different type precipitation and completely retained rainfall echo and zero-centigrade-layer bright band.The velocity dealiasing algorithm can also identify velocity ambiguity zone in typhoon cases,and further filling with interpolation and smooth processing to make the typhoon radial velocity field accuracy and continuous.In conclusion,the quality control algorithm of this paper can improve the radar data quality by recognize the zone of non-precipitation and velocity ambiguity,and improve the application of radar products in quantitative precipitation prediction and data assimilation.