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Since today's weather forecasts only cover large regions every few hours, their use in severe weather is limited. In this paper, we present CloudCast, an application that provides short-term weather forecasts depending on users current location. Since severe weather is rare, CloudCast leverages pay-as-you-go cloud platforms to eliminate dedicated computing infrastructure. CloudCast has two components: 1) an architecture linking weather radars to cloud resources, and 2) a Nowcasting algorithm for generating accurate short-term weather forecasts. We study CloudCast's design space, which requires significant data staging to the cloud. Our results indicate that serial transfers achieve tolerable throughput, while parallel transfers represent a bottleneck for real-time mobile Nowcasting. We also analyze forecast accuracy and show high accuracy for ten minutes in the future. Finally, we execute CloudCast live using an on-campus radar, and show that it delivers a 15-minute Nowcast to a mobile client in less than 2 minutes after data sampling started.