Visual Data Fusion for Decision Support Applications of Numerical Weather Prediction

Non-traditional applications of numerical weather models challenge the typical approaches to the visualization of simulation results. In particular, popular scientific visualization strategies fail when the expertise of the data consumer is not in meteorology and data from the user’s domain must be utilized as well. This problem occurs when predictive weather models are used for a number of weather-sensitive applications. A data fusion approach is adopted for visualization design and can be applied to a diverse set of decision-making efforts such as emergency planning, energy production, airline operations, risk assessment, etc. These applications imply the coupling of weather simulations with other models, analyses and data. To further enable effective assessment and appropriate decisions, focused visualizations must be designed to integrate these distinct data sources, yet still be driven by user goals. Therefore, in many cases, the resultant visualizations do not show forecasts of weather phenomena directly but the derived properties, which are influenced by weather. This work builds upon our past efforts in visualization design that integrates underlying data characteristics, the (human) perception of the visualization and the prerequisite visualization tasks with user goals.