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Proceedings Paper

Visualizing uncertainty of river model ensembles
Author(s): John van der Zwaag; Song Zhang; Robert Moorhead; David Welch; Jamie Dyer
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Paper 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.

Paper Details

Date Published: 8 February 2015
PDF: 8 pages
Proc. SPIE 9397, Visualization and Data Analysis 2015, 93970R (8 February 2015); doi: 10.1117/12.2083484
Show Author Affiliations
John van der Zwaag, Mississippi State Univ. (United States)
Song Zhang, Mississippi State Univ. (United States)
Robert Moorhead, Mississippi State Univ. (United States)
David Welch, National Weather Service (United States)
Jamie Dyer, Mississippi State Univ. (United States)

Published in SPIE Proceedings Vol. 9397:
Visualization and Data Analysis 2015
David L. Kao; Ming C. Hao; Mark A. Livingston; Thomas Wischgoll, Editor(s)

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