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A hybrid method of combining linear programming (LP) and physical constraints is developed to estimate specific differential phase (K DP ) and to improve rain estimation. The hybrid K DP estimator and the existing estimators of LP, least squares fitting, and a self-consistent relation of polarimetric radar variables are evaluated and compared using simulated data. Simulation results indicate the new estimator's superiority, particularly in regions where backscattering phase (δ hv ) dominates. Furthermore, a quantitative comparison between auto-weather-station rain-gauge observations and K DP -based radar rain estimates for a Meiyu event also demonstrate the superiority of the hybrid K DP estimator over existing methods.
Huang et al. (Wed,) studied this question.