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Alexander Kumpf

Publications
3
Citations
62
Publications by Year
20182022
Co-Authors:
Show All Co-Authors (7)
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Alexander Kumpf

Affiliation

Computer Graphics & Visualization Group
Technical University of Munich (TUM)
München, Germany

Publication Topics

Biography

Alexander Kumpf received the BSc degree in mathematics and the MSc degree in mathematical finance from the Technical University of Munich (TUM), Munich, Germany, in 2012 and 2015, and the PhD degree in computer science from TUM, Munich, Germany, in 2020. His major interests in research are visualization of ensemble simulation data using statistical analysis, machine learning, and neural-network-based data improvement.(Based on document published on 24 February 2021).
Publications
3
Citations
62
Publications by Year
20182022
Co-Authors:
Show All Co-Authors (7)
Author's Published Works

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Visual Analysis of Multi-Parameter Distributions Across Ensembles of 3D Fields

Alexander Kumpf;Josef Stumpfegger;Patrick Fabian Härtl;Rüdiger Westermann

IEEE Transactions on Visualization and Computer Graphics
Year: 2022 | Volume: 28, Issue: 10 | Journal Article |
Cited by: Papers (5)
For an ensemble of 3D multi-parameter fields, we present a visual analytics workflow to analyse whether and which parts of a selected multi-parameter distribution is present in all ensemble members. Supported by a parallel coordinate plot, a multi-parameter brush is applied to all ensemble members to select data points with similar multi-parameter distribution. By a combination of spatial sub-divi...Show More

Visual Analysis of Multi-Parameter Distributions Across Ensembles of 3D Fields

Alexander Kumpf;Josef Stumpfegger;Patrick Fabian Härtl;Rüdiger Westermann

Year: 2022 | Volume: 28, Issue: 10 | Journal Article |

Visual Analysis of the Temporal Evolution of Ensemble Forecast Sensitivities

Alexander Kumpf;Marc Rautenhaus;Michael Riemer;Rüdiger Westermann

IEEE Transactions on Visualization and Computer Graphics
Year: 2019 | Volume: 25, Issue: 1 | Journal Article |
Cited by: Papers (19)
Ensemble sensitivity analysis (ESA) has been established in the atmospheric sciences as a correlation-based approach to determine the sensitivity of a scalar forecast quantity computed by a numerical weather prediction model to changes in another model variable at a different model state. Its applications include determining the origin of forecast errors and placing targeted observations to improv...Show More

Visual Analysis of the Temporal Evolution of Ensemble Forecast Sensitivities

Alexander Kumpf;Marc Rautenhaus;Michael Riemer;Rüdiger Westermann

Year: 2019 | Volume: 25, Issue: 1 | Journal Article |

Visualizing Confidence in Cluster-Based Ensemble Weather Forecast Analyses

Alexander Kumpf;Bianca Tost;Marlene Baumgart;Michael Riemer;Rüdiger Westermann;Marc Rautenhaus

IEEE Transactions on Visualization and Computer Graphics
Year: 2018 | Volume: 24, Issue: 1 | Journal Article |
Cited by: Papers (38)
In meteorology, cluster analysis is frequently used to determine representative trends in ensemble weather predictions in a selected spatio-temporal region, e.g., to reduce a set of ensemble members to simplify and improve their analysis. Identified clusters (i.e., groups of similar members), however, can be very sensitive to small changes of the selected region, so that clustering results can be ...Show More

Visualizing Confidence in Cluster-Based Ensemble Weather Forecast Analyses

Alexander Kumpf;Bianca Tost;Marlene Baumgart;Michael Riemer;Rüdiger Westermann;Marc Rautenhaus

Year: 2018 | Volume: 24, Issue: 1 | Journal Article |

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