Improved transient weather reporting using people centric sensing

Improving transient weather reporting accuracy by augmenting automated weather monitoring with people centric sensing is highly desirable since transient weather disambiguation can currently only be accomplished through employing trained expert observers or through using news media reports and data analysis following the weather event. Previous research on this topic has been unable to conclude whether people centric sensing improves weather forecasting. This paper proposes a new, semantic and geospatial analytic cross-disciplinary approach focused on only transient weather conditions, specifically tornado touchdowns, as a means of demonstrating that people centric sensing can provide accurate event reporting even before data from official agencies becomes available. In this way, it is shown that people centric sensing can be used to improve the accuracy of, and potentially confirm, the validity of data collected through traditional sensor sources.