GPU-based, interactive exploration of large spatiotemporal climate networks

Stefan Buschmann; Peter Hoffmann; Ankit Agarwal; Norbert Marwan; Thomas Nocke

doi:10.1063/5.0131933

GPU-based, interactive exploration of large spatiotemporal climate networks

Chaos. 2023 Apr 1;33(4):043129. doi: 10.1063/5.0131933.

Authors

Stefan Buschmann¹, Peter Hoffmann², Ankit Agarwal³, Norbert Marwan², Thomas Nocke²

Affiliations

¹ Hasso Plattner Institute, University of Potsdam, Prof.-Dr.-Helmert-Str. 2-3, 14482 Potsdam, Germany.
² Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany.
³ Department of Hydrology, Indian Institute of Technology Roorkee, Haridwar Highway, Roorkee, Uttarakhand 247667, India.

PMID: 37097944
DOI: 10.1063/5.0131933

Abstract

This paper introduces the Graphics Processing Unit (GPU)-based tool Geo-Temporal eXplorer (GTX), integrating a set of highly interactive techniques for visual analytics of large geo-referenced complex networks from the climate research domain. The visual exploration of these networks faces a multitude of challenges related to the geo-reference and the size of these networks with up to several million edges and the manifold types of such networks. In this paper, solutions for the interactive visual analysis for several distinct types of large complex networks will be discussed, in particular, time-dependent, multi-scale, and multi-layered ensemble networks. Custom-tailored for climate researchers, the GTX tool supports heterogeneous tasks based on interactive, GPU-based solutions for on-the-fly large network data processing, analysis, and visualization. These solutions are illustrated for two use cases: multi-scale climatic process and climate infection risk networks. This tool helps one to reduce the complexity of the highly interrelated climate information and unveils hidden and temporal links in the climate system, not available using standard and linear tools (such as empirical orthogonal function analysis).