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FunnelCloud: a cloud-based system for exploring tornado events
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DOI：10.1080/17538947.2017.1279235.png)
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Abstract
En 中文
Recent research has shown an increase in the number of extreme tornado outbreaks per year. The characterization of the spatio-temporal pattern of tornado events is therefore a critical task in the analysis of meteorological data. Currently, there are a large number of available meteorological datasets that can be used for such analysis. However, much of these data are distributed across multiple websites and are not accessible in a central location. This poses a significant challenge for a scientist who is interested in exploring meteorological patterns associated with tornado events. This paper presents a novel system which uses cloud-based technology for integrating, storing, exploring, analyzing, and visualizing meteorological data associated with tornado outbreaks. The system employs a novel NoSQL database schema and web services architecture for data integration and provides a user friendly interface that allows scientists to explore the spatio-temporal pattern of tornado events. Furthermore, scientists can use this interface to analyze the relationship between different meteorological variables and properties of tornado outbreaks using a number of spatio-temporal statistical and data mining methods. The efficacy of the system is demonstrated on a use case centered on the analysis of climatic indicators of large spatio-temporally clustered tornado outbreaks.
Keywords:
tornado data warehouse
cloud-based system
NoSQL
data integration
spatio-temporal clustering
web-mapping
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