Wednesday, 25 January 2017: 9:45 AM
611 (Washington State Convention Center )
The advent of cloud computing has enabled an on-demand approach to high-performance computing. Bolt Forecast leverages this power in operations, using Amazon EC2 instances to generate forecast statistics for visualization and delivery using modern web technologies. However, a remaining science challenge lies in the mining and presentation of large weather-forecast data sets (‘big data’), particularly when communicating risk and probability to the consumer.
We first present a methodology for forecast-data generation using Amazon Web Services (‘the cloud’). Next, we investigate emerging application methods, such as machine learning and principle-component analysis, that reduce big data sets into tractable data products ready for delivery to clients. Finally, we investigate cutting-edge web-visualization methods to best interpret output from ensemble forecast systems for use in personal and private sector applications.
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