Angular-based Edge Bundled Parallel Coordinates Plot for the Visual Analysis of Large Ensemble Simulation Data

TL;DR

This paper introduces an angular-based extension to parallel coordinates plots, called APCP, which reduces visual clutter and improves analysis of large ensemble simulation data, especially in meteorology, by incorporating Bezier curves for better correlation visualization.

Contribution

The paper presents a novel angular-based extension to PCP using Bezier curves, enhancing visualization of large ensemble datasets while preserving correlation information.

Findings

Effective reduction of visual clutter in large datasets

Improved correlation visualization with Bezier curves

Validated system on meteorological ensemble data

Abstract

With the continuous increase in the computational power and resources of modern high-performance computing (HPC) systems, large-scale ensemble simulations have become widely used in various fields of science and engineering, and especially in meteorological and climate science. It is widely known that the simulation outputs are large time-varying, multivariate, and multivalued datasets which pose a particular challenge to the visualization and analysis tasks. In this work, we focused on the widely used Parallel Coordinates Plot (PCP) to analyze the interrelations between different parameters, such as variables, among the members. However, PCP may suffer from visual cluttering and drawing performance with the increase on the data size to be analyzed, that is, the number of polylines. To overcome this problem, we present an extension to the PCP by adding B\'{e}zier curves connecting the angular distribution plots representing the mean and variance of the inclination of the line segments between parallel axes. The proposed Angular-based Parallel Coordinates Plot (APCP) is capable of presenting a simplified overview of the entire ensemble data set while maintaining the correlation information between the adjacent variables. To verify its effectiveness, we developed a visual analytics prototype system and evaluated by using a meteorological ensemble simulation output from the supercomputer Fugaku.