Show simple item record

dc.contributor.authorFriederici, Ankeen_US
dc.contributor.authorFalk, Martinen_US
dc.contributor.authorHotz, Ingriden_US
dc.contributor.editorDutta, Soumya and Feige, Kathrin and Rink, Karsten and Zeckzer, Dirken_US
dc.date.accessioned2021-06-12T11:24:09Z
dc.date.available2021-06-12T11:24:09Z
dc.date.issued2021
dc.identifier.isbn978-3-03868-148-9
dc.identifier.urihttps://doi.org/10.2312/envirvis.20211079
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/envirvis20211079
dc.description.abstractOceanic eddies, which are highly mass-coherent vortices traveling through the earth's waters, are of special interest for their mixing properties. Therefore, large-scale ensemble simulations are performed to approximate their possible evolution. Analyzing their development and transport behavior requires a stable extraction of both their shape and properties of water masses within. We present a framework for extracting the time series of full 3D eddy geometries based on an winding angle criterion. Our analysis tools enables users to explore the results in-depth by linking extracted volumes to extensive statistics collected across several ensemble members. The methods are showcased on an ensemble simulation of the Red Sea. We show that our extraction produces stable and coherent geometries even for highly irregular eddies in the Red Sea. These capabilities are utilized to evaluate the stability of our method with respect to variations of user-defined parameters. Feedback gathered from domain experts was very positive and indicates that our methods will be considered for newly simulated, even larger data sets.en_US
dc.publisherThe Eurographics Associationen_US
dc.subject[Computer Graphics]
dc.subjectHuman
dc.subjectcentered computing
dc.subjectScientific visualization
dc.titleA Winding Angle Framework for Tracking and Exploring Eddy Transport in Oceanic Ensemble Simulationsen_US
dc.description.seriesinformationWorkshop on Visualisation in Environmental Sciences (EnvirVis)
dc.description.sectionheadersProbabilistic and Uncertainty-based Techniques for Environmental Data Visualization
dc.identifier.doi10.2312/envirvis.20211079
dc.identifier.pages17-24


Files in this item

Thumbnail
Thumbnail

This item appears in the following Collection(s)

Show simple item record