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A NASA project spans the gap between research and operations, introducing new composites of satellite imagery to weather forecasters to prepare for the next generation of satellites.

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 Detection of hazardous dust events in nighttime satellite imagery is limited as dust is difficult to distinguish from the cooling ground. A physically-based approach to developing a machine learning model with satellite imagery inputs correctly labels 85% of dust pixels. Application of the machine learning model to a dust event enhances identification of dust, distinguishing the boundaries of the plume.