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Spatiotemporal Detection and Uncertainty Visualization of Atmospheric Blocking Events

Li, Mingzhe ; Nowack, Peer ORCID iD icon 1,2; Wang, Bei
1 Institut für Theoretische Informatik (ITI), Karlsruher Institut für Technologie (KIT)
2 Institut für Meteorologie und Klimaforschung Atmosphärische Spurengase und Fernerkundung (IMKASF), Karlsruher Institut für Technologie (KIT)

Abstract:

Atmospheric blocking events are quasi-stationary high-pressure systems that disrupt the typical paths of polar and subtropical air currents, often producing prolonged extreme weather events such as summer heat waves or winter cold spells. Despite their critical role in shaping mid-latitude weather, accurately modeling and analyzing blocking events in long meteorological records remains a significant challenge. To address this challenge, we present anuncertainty visualization framework for detecting and characterizing atmospheric blocking events. First, we introduce a geometry-based detection and tracking method, evaluated on both pre-industrial climate model simulations (UKESM) and reanalysis data (ERA5), which represent historical Earth observations assimilated from satellite and station measurements onto regular numerical grids using weather models. Second, we propose a suite of uncertainty-aware summaries: contour boxplots that capture representative boundaries and their variability, frequency heatmaps that encode occurrences, and 3D temporal stacks that situate these patterns in time. Third, we demonstrate our framework in a case study of the 2003 European heatwave, mapping the spatiotemporal occurrences of blocking events using these summaries. ... mehr


Postprint §
DOI: 10.5445/IR/1000194780
Veröffentlicht am 29.06.2026
Originalveröffentlichung
DOI: 10.1109/TVCG.2026.3694459
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung Atmosphärische Spurengase und Fernerkundung (IMKASF)
Institut für Theoretische Informatik (ITI)
Publikationstyp Zeitschriftenaufsatz
Publikationsdatum 12.06.2026
Sprache Englisch
Identifikator ISSN: 1077-2626, 1941-0506, 2160-9306
KITopen-ID: 1000194780
Erschienen in IEEE Transactions on Visualization and Computer Graphics
Verlag Institute of Electrical and Electronics Engineers (IEEE)
Band 32
Heft 6
Seiten 4742–4752
Vorab online veröffentlicht am 19.05.2026
Schlagwörter Uncertainty visualization, atmospheric blocking events, feature detection, feature tracking, weather, climate science, visualization applications
Nachgewiesen in Scopus
OpenAlex
Relationen in KITopen
Globale Ziele für nachhaltige Entwicklung Ziel 13 – Maßnahmen zum Klimaschutz
KIT – Die Universität in der Helmholtz-Gemeinschaft
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