Portraying Uncertainty in Battlefield Weather Situational Awareness

Current automated weather forecast models and associated tactical decision aids often produce information that is insufficient or misleading because they do not adequately reveal the accuracy of the forecast. Users of these decision aids need a way tounderstand the reliability of the forecast. Tacticians make decisions semantically, reasoning in terms of qualitative values and the underlying meaning of data. This process can be reinforced through an effective visualization method that reflects theway a user thinks about weather data.This Phase I effort will investigate the feasibility of a method that provides a semantic mapping of data to quantifiable terms. Using this method, Sonalysts will develop and demonstrate an approach for more effective processing and visualization ofweather forecast data. This effort will demonstrate the ability to use weather prediction terms in tactical decision-support applications, while the visualization effort will address the underlying uncertainty of weather forecast data.