Use of polarimetric radar data for identification of processes in convective storms

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00020699%3A_____%2F25%3AN0000084" target="_blank" >RIV/00020699:_____/25:N0000084 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Use of polarimetric radar data for identification of processes in convective storms

Original language description

poster on 12th European Conference on Severe Storms, Utrecht, Netherlands – 17.- 21.11. 2025 Since 2015, the Czech weather radar network (CZRAD) has consisted of two dual-pol C-band weather radars. This allows us to use polarimetric radar data for many purposes, including better correction for attenuation, which can provide better precipitation estimation data, improved removal of ground clutter and WLAN interference, and enhanced detection of hailstorms. The use of polarimetric data should also allow us to identify updrafts in convective storm cells based on the detection of so-called ZDR-columns and, more recently, KDP-columns. These are column-like features with positive ZDR and KDP values that can reach altitudes several kilometers above the freezing level. The main reasons for this are the presence of liquid water droplets in the warmer updraft air and their ability to remain in a supercooled state for some time in rapidly rising air parcels. The main goals of this study are to verify the potential of polarimetric data for better nowcasting of storm core behavior based on the detection of ZDR-columns and KDP-columns, and to present the advantages and weaknesses of automated algorithms for identifying warm vs. cold rain processes in convective storms. Such knowledge could significantly help forecasters with severe weather warnings, especially in cases of severe hailstorms or torrential rains. In the present analysis, we focused on case studies of several selected situations that occurred during storm seasons from 2018 to 2024. We studied the ability of various polarimetric data to help predict the severe behavior of convective storms and their accompanying phenomena. DOI: https://doi.org/10.5194/ecss2025-213

Czech name

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Czech description

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Type

O - Miscellaneous

CEP classification

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OECD FORD branch

10509 - Meteorology and atmospheric sciences

Project

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Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů