Development of a simulationenvironment for the management and visualization of informationfrom simulation models applied to a regionalscale

Gage, S.H., M. Colunga-Garcia, G.R. Safir, J. Qi, and A.H. Prasla

Presented at the ASM in Seattle (2003-09-18 to 2017-12-05 )

Simulation of physical and biological phenomena at multiple time and space scales is playing a pivotal role in areas that range from genetic studies to global change analysis and assessment. Regional simulation models require the use of large data inputs and are evolving in scope and sophistication. A Modeling Applications System Integrative Framework (MASIF) is presented as a method to facilitate utilization of large amounts of spatial-temporal outputs from regional scale simulations. MASIF incorporates commercial software that provide the model analyst with the ability to rapidly summarize and analyze model results. MASIF enables visualization of model input data, model simulation results, and computation of statistical patterns of information associated with model inputs and outputs. In developing MASIF we have adopted a modular approach that allows the coupling of a model to the analysis and mapping framework using either executable model code or raw computer instructions, and the parameters files. We are currently enabling MASIF to accommodate satellite remotely sensing data as a driver to calibrate model predictions during simulation. For example, we use remote sensing information to adjust simulated biomass or LAI output from daily crop growth.  The MASIF environment provides a powerful and flexible environment that allows model analysts to conduct creative regional experiments with either complex or simple regional models. By providing models with a robust user interface, modelers can optimize their efforts and concentrate on model development. We recognize the value of stand-alone and network-based analytical environments for model assessment and application and thus envision the potential to run, analyze, and visualize web-based simulation models.

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