Sensitivity analysis of self-consistent polarimetric rain retrieval to C-Band radar observables

Numerical simulations are used to investigate the sensitivity of C-Band rain retrieval to polarimetric radar observables. The simulator is based on a T-matrix solution technique, while the hydrometeor distribution have been characterized with respect to dielectric composition (water, ice, and mixed phase), raindrop size distribution (normalized gamma distribution), shape (ellipsoid with parameterized aspect ratio), and angle orientation. The self-consistent ZPHI approach is here adopted and the sensitivity analysis is performed in order to evaluate the expected errors of this method to radar observables. Since differential phase shift K_DP is affected by the spatial variation of the backscattering differential phase shift δ, a new neural-network estimation technique is applied to remove δ effects on K_DP estimate. The performance of these correction procedures and the effects of an error bias on radar measurements is evaluated by using mono-dimensional Gaussian raincell models.