Improved Joint Phase-Attenuation Estimation With Adaptive and High-Resolution Empirical Coefficient Conditioning for Polarimetric Weather Radars

Due to the independence of the specific differential phase KDP from attenuation and miscalibration, it is often applied in attenuation estimation (i.e., estimation of the specific attenuation A from KDP). However, the measured differential phase 9DP includes the backscattering differential phase δhv and noise, decreasing the accuracy of KDP estimation. Additionally, considering that the coefficient γ of the A-KDP empirical relation is sensitive to temperature and drop size distribution, there is also concern over an a priori fixed value for γ . Especially at higher frequency bands such as X-band, large KDP can amplify the biases caused by inaccurate γ . Adaptive and highresolution (AHR) and ZPHI are methods for estimating phase and attenuation, respectively. Their opposite inputs and outputs create a strong coupling between the two methods, allowing both methods to simultaneously reduce the impact of contaminated 9DP on estimation. Meanwhile, their high resolution (HR) makes it possible to conditioning γ adaptively at a range resolution scale according to different rainfall situations. In this work, a method that combines the individual and common characteristics of AHR and ZPHI is proposed to improve the accuracy of phase and attenuation estimation by adaptively conditioning γ at HR, as well as reducing the biases of δhv and noise. The improved effects of this method are assessed with a typical storm event observed by a polarimetric X-band weather radar in The Netherlands, and its performances are further evaluated with simulations comprehensively. The results show that this method can improve the accuracy of both phase and attenuation estimation significantly, especially at large KDP.