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

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.

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Published
2024-10-13
DOI
https://doi.org/10.1109/vis55277.2024.00046
Primary Topic
Simulation Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Michael Böttinger, Gerik Scheuermann, Christian Heine, Tomas Daetz
Simulation Techniques and Applications
article

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

Michael Böttinger, Gerik Scheuermann, Christian Heine, Tomas Daetz
article en

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.

German Climate Computing Centre (DE), Computing Center (RU), Leipzig University (DE)
Deutsche Forschungsgemeinschaft
Reduced inequalities
Openalex Percentile: Top 73%
Simulation Techniques and Applications
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