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Vortex Identification across Different Scales

Schielicke, Lisa; Gatzen, Christoph Peter; Ludwig, Patrick ORCID iD icon 1
1 Institut für Meteorologie und Klimaforschung (IMK), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

Vortex identification in atmospheric data remains a challenge. One reason is the general presence of shear throughout the atmosphere that interferes with traditional vortex identification methods based on geopotential height or vorticity. Alternatively, kinematic methods can avoid some of the drawbacks of the traditional methods since they compare the rotational and deformational flow parts. In this work, we apply the kinematic vorticity number method (Wk-method) to atmospheric datasets ranging from the synoptic to the convective scales. The Wk-method is tested for winter storm Kyrill, a high-impact extratropical cyclone that affected Germany in January 2007. This case is especially challenging for vortex identification methods since it produced a complex wind occurrence associated with a derecho along a narrow cold-frontal rain band and an area of high winds close to the low pressure center. The Wk-method is able to identify vortices in differently-resolved datasets and at different height levels in a consistent manner. Additionally, it is able to determine and visualize the storm characteristics. As a result, we discovered that the total positive circulation of the vortices associated with Kyrill remains of similar order across different data sets though the vorticity magnitude of the most intense vortices increases with increasing resolution.


Verlagsausgabe §
DOI: 10.5445/IR/1000098243
Veröffentlicht am 12.09.2019
Originalveröffentlichung
DOI: 10.3390/atmos10090518
Scopus
Zitationen: 2
Web of Science
Zitationen: 2
Dimensions
Zitationen: 2
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung Troposphärenforschung (IMKTRO)
KIT-Zentrum Klima und Umwelt (ZKU)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2019
Sprache Englisch
Identifikator ISSN: 2073-4433
KITopen-ID: 1000098243
HGF-Programm 12.01.02 (POF III, LK 01) Proc.res.f.multisc.predictab.of weather
Erschienen in Atmosphere
Verlag MDPI
Band 10
Heft 9
Seiten 518-543
Vorab online veröffentlicht am 04.09.2019
Nachgewiesen in Web of Science
Dimensions
Scopus
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