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Characterizing hail-prone environments using convection-permitting reanalysis and overshooting top detections over south-central Europe

Giordani, Antonio ; Kunz, Michael ORCID iD icon 1; Bedka, Kristopher M.; Punge, Heinz Jürgen 1; Paccagnella, Tiziana; Pavan, Valentina; Cerenzia, Ines M. L.; Di Sabatino, Silvana
1 Institut für Meteorologie und Klimaforschung (IMK), Karlsruher Institut für Technologie (KIT)

Abstract:

The challenges associated with reliably observing and simulating hazardous hailstorms call for new approaches that combine information from different available sources, such as remote sensing instruments, observations, or numerical modelling, to improve understanding of where and when severe hail most often occurs. In this work, a proxy for hail frequency is developed by combining overshooting cloud top (OT) detections from the Meteosat Second Generation (MSG) weather satellite with convection-
permitting High rEsolution ReAnalysis over Italy (SPHERA) reanalysis predictors describing hail-favourable environmental conditions. Atmospheric properties associated with ground-based reports from the European Severe Weather Database (ESWD) are considered to define specific criteria for data filtering. Five convection-related parameters from reanalysis data quantifying key ingredients for hailstorm occurrence enter the filter: most unstable convective available potential energy (CAPE), K index, surface lifted index, deep-
layer shear, and freezing-level height. A hail frequency estimate over the extended summer season (April–October) in south-central Europe is presented for a test period of 5 years (2016–2020). ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000172932
Veröffentlicht am 31.07.2024
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung Troposphärenforschung (IMKTRO)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2024
Sprache Englisch
Identifikator ISSN: 1561-8633, 1684-9981
KITopen-ID: 1000172932
HGF-Programm 12.11.34 (POF IV, LK 01) Improved predictions from weather to climate scales
Erschienen in Natural Hazards and Earth System Sciences
Verlag European Geosciences Union (EGU)
Band 24
Heft 7
Seiten 2331 – 2357
Vorab online veröffentlicht am 12.07.2024
Nachgewiesen in Dimensions
Web of Science
Scopus
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