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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
Date of Publication
October 14, 2024
Publication Type
Working Paper
Division/Institute

Institute of Geograph...

Federal Office of Met...

Geographisches Instit...

Oeschger Centre for C...

Oeschger Centre for C...

Author
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
Subject(s)

000 - Computer scienc...

500 - Science::530 - ...

500 - Science

900 - History::910 - ...

Publisher
Cornell University
Language
English
Publisher DOI
10.48550/arXiv.2410.10499
Uncontrolled Keywords

Differential Reflecti...

Hail Sizing

C-Band radar

Crowdsourcing

Convetive Storms

Alpine Topography

Nowcasting

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.
Handle
https://boris-portal.unibe.ch/handle/20.500.12422/210943
Funding(s)
Swiss National Science Foundation, SsClim Project
Dataset(s)
https://github.com/MartinAregger/ZDRC_Calculator_QJ_2024
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File(s)
FileFile TypeFormatSizeLicensePublisher/Copright statementContent
2410.10499v1.pdftextAdobe PDF3.19 MBpublished
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