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Spatiotemporal Detection and Uncertainty Visualization of Atmospheric Blocking Events

Li, Mingzhe; Nowack, Peer ORCID iD icon 1; Wang, Bei
1 Institut für Theoretische Informatik (ITI), 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 an uncertainty 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


Volltext §
DOI: 10.5445/IR/1000189347
Veröffentlicht am 07.01.2026
Originalveröffentlichung
DOI: 10.48550/arXiv.2601.00775
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Theoretische Informatik (ITI)
Publikationstyp Forschungsbericht/Preprint
Publikationsjahr 2026
Sprache Englisch
Identifikator KITopen-ID: 1000189347
HGF-Programm 12.11.25 (POF IV, LK 01) Atmospheric composition and circulation changes
Weitere HGF-Programme 12.11.34 (POF IV, LK 01) Improved predictions from weather to climate scales
Verlag arxiv
Serie Computer Science - Graphics
Bemerkung zur Veröffentlichung Accepted for presentation at the OceanViz Conference 2026 in Sydney, Australia, and for journal publication in IEEE Transactions on Visualization and Computer Graphics
Vorab online veröffentlicht am 02.01.2026
Schlagwörter Graphics (cs.GR), Computational Geometry (cs.CG), Atmospheric and Oceanic Physics (physics.ao-ph)
Nachgewiesen in arXiv
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