This study addresses the effect that the interaction between anomalous radar beam propagation (AP) and wind turbines that are located far from the radar has on radar-rainfall estimates. The interference of wind turbines in radar observations may lead to significant errors in rainfall estimates since wind turbines are often clustered to form wind farms. In this study, we propose a novel approach - based on the polarimetric capability recently added to the WSR-88D NEXRAD radars - that identifies and eliminates wind turbine clutter along with common ground clutter AP effects. Our primary objective is to devise a physically meaningful and fully automated dual-polarimetric method that effectively handles clutter features, which are hard to detect using single-channel reflectivity data alone. To address this issue, we explore the feasibility of using polarimetric variables such as differential reflectivity (ZDR), copolar correlation (RHO), and differential phase (PHIDP). Accordingly, we developed three new approaches using polarimetric variables, which are combined with the AP detection algorithm that uses a three-dimensional structure of reflectivity. We evaluate the new algorithms in terms of both eliminating non-meteorological radar returns and preserving returns from actual rain. The proposed algorithm, which uses RHO conditioned on horizontal reflectivity values while also accounting for the variation of ZDR or PHIDP, shows good performance for the presented cases.