A Gaussian mixture method for specific differential phase retrieval at X-band frequency
The specific differential phase Kdp is one of the most important polarimetric radar variables, but the variance σ2(Kdp), regarding the errors in the calculation of the range derivative of the differential phase shift Φdp, is not well characterized due to the lack of a data generation model. This paper presents a probabilistic method based on the Gaussian mixture model for Kdp estimation at X-band frequency. The Gaussian mixture method can not only estimate the expected values of Kdp by differentiating the expected values of Φdp, but also obtain σ2(Kdp) from the product of the square of the first derivative of Kdp and the variance of Φdp. Additionally, the ambiguous phase and backscattering differential phase shift are corrected via the mixture model. The method is qualitatively evaluated with a convective event of a bow echo observed by the X-band dual-polarization radar in the University of Missouri. It is concluded that Kdp estimates are highly consistent with the gradients of Φdp in the leading edge of the bow echo, and large σ2(Kdp) occurs with high variation of Kdp. Furthermore, the performance is quantitatively assessed by 2-year radar–gauge data, and the results are compared to linear regression model. It is clear that Kdp-based rain amounts have good agreement with the rain gauge data, while the Gaussian mixture method gives improvements over the linear regression model, particularly for far ranges.