A hybrid stochastic physics-based and polarization-diverse radar reflectivity simulation procedure for rainfall studies is described. The procedure begins with the generation of two-dimensional rainfall intensity fields from a space-time stochastic model with a statistical parametrization of drop-size distribution. The two-dimensional fields are complemented with a vertical structure of hydrometeors by choosing a precipitation cloud type model, which results in size, shape, and phase (mixed or single) distribution at discrete elevations. Given these three-dimensional fields, the sampling volume integration process involved in radar measurements is simulated to give the radar-observed parameters. Effects such as antenna beam pattern, horizontal and vertical gradients, atmospheric gases, and rain attenuation are represented. The radar observables are corrupted with a random measurement error to represent the radar hardware system noise and other sources of uncertainty. The simulated radar reflectivities are qualitatively evaluated using actual radar data. The simulator is a useful tool for engineers and hydrometeorologists in the study of radar-rainfall measurement and estimation errors and their effects.
