Topology-Based Tracking of Features in Weather/Climate Data
Weather and climate simulations result in big data containing complex physical phenomena, which can be described as features. Commonly, features can be described as critical points in a scalar field, which can be further refined by requiring the critical point to follow a set of rules developed in collaboration with domain scientists. The rules and the tracking are based on concepts from topology such as the merge tree, persistence and the Morse-Smale complex. Currently, the project focuses on improving the visualization of the features, allowing flexible feature definitions and applying our pipeline in an in-situ context.
Contact: Emma Nilsson