IEEE VIS 2024 Content: Visualization of 2D Scalar Field Ensembles Using Volume Visualization of the Empirical Distribution Function

Visualization of 2D Scalar Field Ensembles Using Volume Visualization of the Empirical Distribution Function

Tomas Daetz - Institute of Computer Science, Leipzig University, Leipzig, Germany

Michael Böttinger - German Climate Computing Center (DKRZ), Hamburg, Germany

Gerik Scheuermann - Leipzig University, Leipzig, Germany

Christian Heine - Leipzig University, Leipzig, Germany

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Room: Bayshore VI

2024-10-16T16:36:00ZGMT-0600Change your timezone on the schedule page
2024-10-16T16:36:00Z
Exemplar figure, described by caption below
Precipitation change (%) in 2080-2099 relative to 1986-2005 based on 100 simulation runs of the RCP8.5 scenario within MPI-GE. (a) shows a direct volume rendering of the cumulative height field using a 2D transfer function, mapping cumulative probabilities to opacity and precipitation change to color (blue: increase, red: decrease), and an isosurface of the median. (d) shows an orthographic view from the top. The intersection of the black lines show the point of interest (0°, 170°W). (b) and (c) show the cumulative function graphs along each component of the point of interest. The purple lines depict the zero percent difference.
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Keywords

Scalar field visualization, ensemble visualization, volume rendering, nonparametric statistics.

Abstract

Analyzing uncertainty in spatial data is a vital task in many domains, as for example with climate and weather simulation ensembles. Although many methods support the analysis of uncertain 2D data, such as uncertain isocontours or overlaying of statistical information on plots of the actual data, it is still a challenge to get a more detailed overview of 2D data together with its statistical properties. We present cumulative height fields, a visualization method for 2D scalar field ensembles using the marginal empirical distribution function and show preliminary results using volume rendering and slicing for the Max Planck Institute Grand Ensemble.