Phase identification of precipitation particles based on dual linear polarization radar data

Based on Jiangsu X-band dual-line polarization radar data, Z_H (radar horizontal reflectance factor), Z_DR (differential reflectivity factor), K_DP (differential propagation phase shift), pπv(0) (zero lag) are selected using a fuzzy logic algorithm The number of correlations) and other four parameters were used to establish a precipitation particle phase recognition algorithm, and a typical case was used to test and evaluate the effect of the algorithm's phase recognition. Through analysis, the author believes that: (1) The algorithm can basically reflect the phase states of various precipitation particles, indicating that the precipitation particle recognition algorithm established in this paper has strong applicability and the recognition results are credible. (2) This algorithm does not consider the zero-degree layer height and the ambient temperature of each layer, which results in a large recognition error in individual areas. The next step is to use the ambient temperature as an input and use Z_H, Z_DR, K_DP, The construction of membership function with ρ_HV(0) and ambient temperature T should further improve the accuracy of phase identification. (3) The results of the precipitation particle identification are closely related to the parameter settings of the membership functions of the 10 types of water condensate types, and the setting of these parameters is very subjective. A large number of individual statistics are needed to obtain more reliable parameter values.