A Study of Method for Filtering Copolar Differential Phase of X-Band Dual-Polarimetric Doppler Weather Radar

Measurements of the 714XDP-A X-band dual-polarimetric Doppler radar located at Shunyi of Beijing are used to develop an integrated filter method that can improve the quality of the copolar differential phase Ψ_C measured by X-band dual-polarimetric Doppler radar. Application of the integrated filter method shows that:(1) The integrated wavelet de-noising method is the best and better than the median, integrated mean, integrated Kalman and integrated FIR (Finite Impulse Response) filters. It retains the mean trend of raw Ψ_C range profiles and detailsdeviations are within ±2°, which indicates the results are reliable, although the values may slightly exceed the range in several gates (the numbers of radar range profile). Furthermore, the influence of zero value caused by measurement errors on the filtered results is avoided (the corrected value for zero value in the measurements returns to the level of mean trend with deviations within ±2°, which is regarded as credible). In addition, the fluctuation index of Ψ_C range profiles filtered by integrated wavelet de-noising can be reduced by 94%-97% compared to raw Ψ_C range profiles, and the smoothing effect is remarkable (smoothing the fluctuations exceeding ±1.5° Gate^-1, and retaining the fluctuations inside ±1.5°Gate^-1). (2) The estimated specific differential propagation phase (K_DP) are within the range of ±5° km^-1, and influences caused by zero errors in the measurements and δ and environment noises are avoided. In addition, K_DP can well indicate strong precipitation (for precipitation in stratocumulus clouds, radar reflectivity is usually within 30 dBZ ≤ Z_H < 37 dBZ, and K_DP generally is greater than 0.25° km^-1 with the maximum of 4.3° km^-1; for precipitation in cumulonimbus clouds, radar reflectivity usually is within 30 dBZ ≤ Z_H < 50 dBZ, and K_DP is generally greater than 0.1° km^-1 with the maximum of 1.95° km^-1). This study is beneficial to rainfall estimation and hydrometeors classification, which is important for thunderstorm weather forecast.