A "Real-like" polarimetric weather radar data generation using physical and statistical models

Realistic model of rain radar returns is of interest to improve the performances of rainfull estimation applications and to develop new approximations in case of lack of measured data-bases. In this paper, we propose a method to generate a "Real-like" polarimetric rain radar data based on a dual approach referring to both a physical and a statistical models of rain target. Combining informations from these two models accords us an opportunity to obtain more realistic results than a single model based approach. Theoretical foundation of the actual work was exposed all along the paper. An example of data generation, for a fixed physical configuration, was given so as to illustrate comparison between ideal and realistic rain radar data.