Visual analytics of large-scale climate model data
Pak Chung Wong, Han-Wei Shen, Lai-Yung Ruby Leung, Samson Hagos, Teng‐Yok Lee, Xin Tong, Kewei Lü · 2014
This application paper presents a visual analytics tool designed to explore large-scale scientific data modeled after a natural climate phenomenon. The data are modeled on a high-performance computer and exported to a personal computer for interactive visualization. The system is co-designed by visual analytics researchers and domain scientists after a year of rapid prototyping and evaluation of multiple information and scientific visualization techniques using a model dataset that includes both scalar fields and flow fields. Five information-visualization and one scientific-visualization techniques are included in the visual analytics system to balance analytical effectiveness and computation time for large-scale interactive exploration. The paper discusses the system design, explains the design rationale, and shares computation performance and results of different visualization techniques. The primary contribution of this application paper is to show that we can interactively and effectively visualize a large amount of scientific model data on a modest desktop computer. The computation performance results of the individual visualization techniques and the overall system also provide benchmark references for other large-scale visualization development efforts.