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  3. Differential reflectivity columns and hail - linking C-band radar-based estimated column characteristics to crowdsourced hail observation sin Switzerland
 

Differential reflectivity columns and hail - linking C-band radar-based estimated column characteristics to crowdsourced hail observation sin Switzerland

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BORIS DOI
10.48620/88011
Publisher DOI
10.48550/arXiv.2410.10499
Description
Differential reflectivity columns (ZDRC) have been shown to provide information about a storm's updraft intensity and size. The updraft's characteristics, in turn, influence a severe storm's propensity to produce hail and the size of said hail. Consequently, there is the potential to use ZDRC for the detection and sizing of hail. In this observational study, we investigate the characteristics of ZDRC (volume, height, area, maximum ZDR within) automatically detected on an operational C-band radar network in Switzerland and relate them to hail on the ground using 173'000 crowdsourced hail reports collected over a period of 3.5 years.
We implement an adapted version of an established ZDRC detection algorithm on a 3D composite of ZDR data derived from five Swiss weather radars. The composite, in combination with the dense network of radars located on differing altitudes up to 3000 m.a.s.l, helps to counteract the effects of the complex topography of the study region. The alpine region presents visibility and data quality challenges, which are especially crucial for measuring ZDRC. Our analysis finds ZDRC present in most hail-producing storms, with higher frequencies in storms producing severe hail. Further, when looking at lifetime maximum values, we find significant differences in various ZDRC characteristics between hail-producing and non-hail-producing storms. We also attempt to determine thresholds to differentiate between storm types. The temporal evolution of the ZDRC proves challenging to investigate due to their intermittent nature. Nevertheless, the peak values of the ZDRC characteristics are most often measured 5-10 minutes before the first hail reports on the ground, highlighting the potential for ZDRC to be used in warning applications.
Date of Publication
2024-10-14
Publication Type
Working Paper
Subject(s)
000 Computer science, knowledge & systems
500 Science > 530 Physics
500 Science
900 History > 910 Geography & travel
Keyword(s)
Differential Reflectivity Columns
•
Hail Sizing
•
C-Band radar
•
Crowdsourcing
•
Convetive Storms
•
Alpine Topography
•
Nowcasting
Language(s)
en
Contributor(s)
Aregger, Martin
Geographisches Institut (GIUB) - Klimafolgenforschung
Oeschger Centre for Climate Change Research (OCCR)
Martius, Oliviaorcid-logo
Institute of Geography, Climatology
Oeschger Centre for Climate Change Research (OCCR) - MobiLab
Oeschger Centre for Climate Change Research (OCCR)
Germann, Urs
Federal Office of Meteorology and Climatology MeteoSwiss
Hering Alessandro Michele
Federal Office of Meteorology and Climatology MeteoSwiss
Additional Credits
Institute of Geography, Climatology
Federal Office of Meteorology and Climatology MeteoSwiss
Geographisches Institut (GIUB) - Klimafolgenforschung
Oeschger Centre for Climate Change Research (OCCR)
Oeschger Centre for Climate Change Research (OCCR) - MobiLab
Publisher
Cornell University
Related Funding(s)
Swiss National Science Foundation, SsClim Project
Related Dataset(s)
https://github.com/MartinAregger/ZDRC_Calculator_QJ_2024
Access(Rights)
restricted
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