Adaptive and high-resolution estimation of specific differential phase for polarimetric X-band weather radars

One of the most beneficial polarimetric variables may be the specific differential phase K_DP because of its independence from power attenuation and radar miscalibration. However, conventional K_DP estimation requires a substantial amount of range smoothing as a result of the noisy characteristic of the measured differential phase ψ_DP. In addition, the backscatter differential phase δ_hv component of ψ_DP, significant at C- and X-band frequency, may lead to inaccurate K_DP estimates. In this work, an adaptive approach is proposed to obtain accurate K_DP estimates in rain from noisy ψ_DP, whose δ_hv is of significance, at range resolution scales. This approach uses existing relations between polarimetric variables in rain to filter δ_hv from ψ_DP while maintaining its spatial variability. In addition, the standard deviation of the proposed K_DP estimator is mathematically formulated for quality control. The adaptive approach is assessed using four storm events, associated with light and heavy rain, observed by a polarimetric X-band weather radar in the Netherlands. It is shown that this approach is able to retain the spatial variability of the storms at scales of the range resolution. Moreover, the performance of the proposed approach is compared with two different methods. The results of this comparison show that the proposed approach outperforms the other two methods in terms of the correlation between K_DP and reflectivity, and K_DP standard deviation reduction.