Real-Time Rainfall Estimation Using Satellite Signals: Development and Assessment of a New Procedure

This contribution presents a comprehensive methodology for the real-time estimation of the rain intensity from downlink satellite signals. The enhanced system leverages on extremely randomized tree classifiers to automatically perform rainfall detection along earth–satellite links and successively employs an improved procedure to determine the corresponding slant-path rain attenuation. The latter quantity is then exploited to yield real-time rainfall rate estimates with a 1-min time resolution. The accuracy of the proposed methodology is tested using the Ka- and $Q$ -band propagation data, collected in two different sites (Milan and Madrid) and in the framework of the propagation experiments. The results demonstrate the reliability of the automated rain event detector, as well as a satisfactory accuracy in estimating the slant-path rain attenuation and the point rainfall rate. The accuracy is assessed both on a statistical and on an instantaneous basis through the evaluation of different error figures and by inspection of individual time series.