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Funded
Project. / 1

Funded
Project.

Sensorsystem zur Vorhersage von extremen Unwettern

Sensorsystem zur Vorhersage von extremen Unwettern

Main application:
Danube University Krems

Scientific management:
Andreas Kainz (Danube University Krems)

Project partners:
Pieter Groenemeijer (ESSL Research and Training Centre)
Tomas Pú?ik (ESSL Research and Training Centre)

Research field:
Geistes-, Sozial- und Kulturwissenschaften Ökosysteme und Ökosystemdienstleistungen Fertigungs- und Automatisierungstechnik

Project-ID: FTI19-019
Project start: 01. March 2021
Runtime: 36 months / ongoing
Funding amount: € 199.183,00

Brief summary

Various recent studies show that the rising global temperature leads to an increase in low-level atmospheric humidity and convective available potential energy that feeds thunderstorms. As a result, the frequency and intensity of thunderstorms will rise, including the number of lightning strikes per storm. Due to the combined effect of global warming on the number of storms and the number of strikes per storm, lightning is expected to be 6% more frequent per degree of global temperature rise, which may lead to an increase in accidents and deaths as well as material and environmental damage. The first detectable phenomenon when a new thunderstorm cell develops is a change of the static electric field at ground level. For that reason, permanent monitoring of the local electrostatic field has been identified as key for thunderstorm warning in the international standards. For effective early warning, multi-station field monitoring is necessary as such measurements improve the reliability and information value. Given the state-of-the-art measurement systems, this is far too expensive to realise and maintain. The unique electric field sensors recently developed at DUK are for the first time reliable and potentially cost-efficient enough to attempt realisation of such large-scale networks. In this project, the sensor will be adapted for outdoor usage and installed at a dedicated monitoring site in Wiener Neustadt. Afterwards, the sensor will collect field data over multiple periods of several days in order to capture the field in different weather conditions (including thunderstorms). This data will be evaluated to explore the potential advantages and warning applications of the sensor in the light of the climate change driven increase in thunderstorm frequency and intensity. Ideally, the field data will help to assess the severity of developing storms at an early stage.

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