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The term nowcasting reflects the need of timely\udand accurate predictions of risky situations related to the development\udof severe meteorological events. In this work the\udobjective is the very short term prediction of the rainfall field\udfrom geostationary satellite imagery entirely based on neural\udnetwork approach. The very short-time prediction (or nowcasting)\udprocess consists of two steps: first, the infrared radiance\udfield measured from geostationary satellite (Meteosat\ud7) is projected ahead in time (30 min or 1 h); secondly, the\udprojected radiances are used to estimate the rainfall field by\udmeans of a calibrated microwave-based combined algorithm.\udThe methodology is discussed and its accuracy is quantified\udby means of error indicators. An application to a satellite observation\udof a rainfall event over Central Italy is finally shown\udand evaluated

Artificial neural-network technique for precipitation nowcasting from satellite imagery