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<p>The uncertainty of weather forecasts contributes to mission risk. Ensemble data can improve combat  capability by incorporating forecast uncertainty into the warfighter decision process. The study transforms raw  ensemble data into optimized decision inputs for upper level turbulence using ORM principles and decision science. It  demonstrates the methodology and importance of incorporating ambiguity, the uncertainty in forecast uncertainty,  into the decision making process using the Taijitu method to estimate ambiguity. Comparing ambiguity and risk  tolerance uncertainty intervals produces a more appropriate decision input compared to currently existing methods.  Significant differences between the current and research derived decision input products demonstrate potential value  added to decision making by incorporating ambiguity information. An effective visualization is devised for varying  levels of risk tolerance and mission thresholds that is educational and practical for users. Research procedures and  results can serve as an example to further education and development of stochastic methods in the Air Force and  Department of Defense.
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<br>Subjects: Weather forecasting; Statistical methods; Evaluation; Turbulent boundary layer; Mathematical models; Decision making; Methodology</div>
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Szczes, Jeanne R.</div>
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