Data Fusion is the use of techniques that combine data from multiple sources and gather that information in order to achieve inferences, which will be more efficient and potentially more accurate than if they were achieved by means of a single source.1 NOAA's Weather Enterprise vision for the production and delivery of services calls for increased use of fused data to most intelligently produce environment information targeted to best meet customer needs for decision support. Information sources for fused products can include satellite and radar data, in situ observations and model analyses and forecasts. The GOES-R Proving Ground and GOES-R Risk Reduction activities provide a near-term opportunity to evaluate this data fusion framework in support of advanced NWS capabilities.

This paper will present some examples of possible proving ground demonstrations to further explore: the pros and cons of data fusion; the best means of presenting fused data information to the forecaster; traceability and data resolution issues (what works and what does not).

1 Definition source: Wikipedia: http://en.wikipedia.org/wiki/Data_fusion