Time Lag Estimation between Weather Radar and Disdrometer Based on Correlation Analysis and Falling Velocity

In the field of meteorological remote sensing, radar is often used as a tool to observe the precipitation process. However, due to the difference of radar wavelength and precipitation process, different radars have different attenuation. This paper presents a method for estimating the time lag between disdrometer and radar observation data, and can be used to correct the time lag at higher altitudes. Firstly, the scattering characteristics of precipitation particles are simulated using the T-matrix method (TMM) based on disdrometer data. Subsequently, the time lag of disdrometer is estimated by cross-correlation function method, Pearson operator method and falling velocity method. After correcting the time lag, it can be found that the time consistency between radar observation data and disdrometer data is improved. Finally, the attenuation correction of X and K band radar data during a stratospheric cloud precipitation process is performed, and the impact of time lag correction on the improvement of attenuation correction results is discussed, which demonstrated that after applying time lag correction, the data consistency between X-band radar and K-band radar is significantly improved, with the correlation coefficient increasing from 0.673 to 0.72.