Ricerc@Sapienza

An analysis to evaluate the impact of multiple radar reflectivity data with a three-dimensional variational (3-D-Var) assimilation system on a heavy precipitation event is presented. The main goal is to build a regionally tuned numerical prediction model and a decision-support system for environmental civil protection services and demonstrate it in the central Italian regions, distinguishing which type of observations, conventional and not (or a combination of them), is more effective in improving the accuracy of the forecasted rainfall.

Rain, snow, and volcanic ash clouds contain particles generated by different physical and chemical processes. When electromagnetic radiation interacts with particle distribution, causing absorption and scattering, the backscattered power enables the retrieval of useful geophysical parameters of particle distribution. This is the measurement principle of microwave weather (meteorological) radar, monostatic remote sensing that can exploit Rayleigh and Mie backscattering to remotely probe atmospheric clouds.