Visualizing uncertainty of river model ensembles

John van der Zwaag; Song Zhang; Robert Moorhead; David Welch; Jamie Dyer

doi:10.1117/12.2083484

8 February 2015 Visualizing uncertainty of river model ensembles

John van der Zwaag, Song Zhang, Robert Moorhead, David Welch, Jamie Dyer

Proceedings Volume 9397, Visualization and Data Analysis 2015; 93970R (2015) https://doi.org/10.1117/12.2083484
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States

Abstract

Ensembles are an important tool for researchers to provide accurate forecasts and proper validation of their models. To accurately analyze and understand the ensemble data, it is important that researchers clearly and efficiently visualize the uncertainty of their model output. In this paper, we present two methods for visualizing uncertainty in 1D river model ensembles. We use the strengths of commonly used techniques for analyzing statistical data, and we apply them to the 2D and 3D visualizations of inundation maps. The resulting visualizations give researchers and forecasters an easy method to quickly identify the areas of highest probability of inundation.

Citation Download Citation

John van der Zwaag, Song Zhang, Robert Moorhead, David Welch, and Jamie Dyer "Visualizing uncertainty of river model ensembles", Proc. SPIE 9397, Visualization and Data Analysis 2015, 93970R (8 February 2015); https://doi.org/10.1117/12.2083484

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