Robust Detection and Visualization of Jet-Stream Core Lines in Atmospheric Flow

Jet-streams, their core lines and their role in atmospheric dynamics have been subject to considerable meteorological research since the first half of the twentieth century. Yet, until today no consistent automated feature detection approach has been proposed to identify jet-stream core lines from 3...

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Veröffentlicht in:IEEE transactions on visualization and computer graphics. - 1996. - 24(2018), 1 vom: 30. Jan., Seite 893-902
1. Verfasser: Kern, Michael (VerfasserIn)
Weitere Verfasser: Hewson, Tim, Sadlo, Filip, Westermann, Rudiger, Rautenhaus, Marc
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2018
Zugriff auf das übergeordnete Werk:IEEE transactions on visualization and computer graphics
Schlagworte:Journal Article Research Support, Non-U.S. Gov't
Beschreibung
Zusammenfassung:Jet-streams, their core lines and their role in atmospheric dynamics have been subject to considerable meteorological research since the first half of the twentieth century. Yet, until today no consistent automated feature detection approach has been proposed to identify jet-stream core lines from 3D wind fields. Such 3D core lines can facilitate meteorological analyses previously not possible. Although jet-stream cores can be manually analyzed by meteorologists in 2D as height ridges in the wind speed field, to the best of our knowledge no automated ridge detection approach has been applied to jet-stream core detection. In this work, we -a team of visualization scientists and meteorologists-propose a method that exploits directional information in the wind field to extract core lines in a robust and numerically less involved manner than traditional 3D ridge detection. For the first time, we apply the extracted 3D core lines to meteorological analysis, considering real-world case studies and demonstrating our method's benefits for weather forecasting and meteorological research
Beschreibung:Date Completed 19.12.2018
Date Revised 19.12.2018
published: Print-Electronic
Citation Status PubMed-not-MEDLINE
ISSN:1941-0506
DOI:10.1109/TVCG.2017.2743989