Weather Prediction Uncertainty Management And Representation (PUMAR)

Strategic weather centers run numerical weather prediction (NWP) models, but military operators do not often have the time or capability to analyze the NWP information -- warfighters must rely on decision aids to succinctly translate the NWP informationinto battlefield intelligence. Since NWP models are not perfect, methods are needed to determine and display the meta-information (e.g., uncertainty, resolution, timeliness) about a forecast to assess mission impact. To help address this need, we proposea Phase I SBIR program to prototype and demonstrate a system for weather Prediction Uncertainty Management And Representation (PUMAR). Four core components characterize our approach. First, we will perform a cognitive task analysis of aweather-influenced decision-making scenario, followed by a principled categorization of the types and sources of uncertainty influencing the decision-maker. Second, we will identify and develop methods to manage the key types of uncertainty in NWPforecasts (e.g., ensemble forecasting, Bayesian hierarchical methods). Third, we will prototype several meta-information visualization techniques and user interfaces in the context of a decision aid that uses weather information to determine weaponcapabilities. Fourth, we will integrate these concepts and methods into a computerized system designed to interface with existing DoD meteorological systems.