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<p>This thesis investigates the development of an agent-based system to analyze  meteorological model data and generate statistics for comparison purposes. With it, it is  possible to research the value and level of improvement when utilizing different levels of  atmospheric-model resolution for guidance in tactical decision aids. Our agent-based  system automates the comparison of model data at a location in the model field with  environmental data extracted from sensor data obtained from RAOB launches. Statistics  were efficiently generated for the variability of the u and v components of the wind  directions, to aid in the rapid determination of the variability of model data and its effects  on targeting accuracy. By addressing the interoperability and adaptability of agents, this  research demonstrates the usefulness of agents to extract information to rapidly compute  mission-planning accuracy.
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<br>Subjects: Oceanography; Mathematical models; Forecasting</div>
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Rost, Michael C.</div>
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