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GPS-SNR-based detection of severe weather events: two case studies of summer 2021 in Switzerland
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  • Matthias Aichinger-Rosenberger,
  • Martin Aregger,
  • Jerome Kopp,
  • Benedikt Soja
Matthias Aichinger-Rosenberger
Institute of Geodesy and Photogrammetry, ETH Zurich

Corresponding Author:[email protected]

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Martin Aregger
University of Bern
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Jerome Kopp
University of Bern
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Benedikt Soja
Institute of Geodesy and Photogrammetry, ETH Zurich
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Abstract

Global Navigation Satellite Systems (GNSS) have become a valuable tool for remote sensing, as signals can be used for monitoring soil and snow properties as well as water vapor in the atmosphere. By using L-band carrier frequencies, GNSS acts as an all-weather-operation system. Nevertheless, severe weather can still have an impact on the strength of signals received at a ground station, as we show in this study. We investigate Signal-to-Noise Ratio (SNR) from the Global Positioning System (GPS) during two thunderstorm events, which produced excessive amounts of rain and hail. We make use of a GPS-SNR-based algorithm, developed for the detection of hail particles from volcanic eruptions. Results indicate that the investigated thunderstorm events are visible in SNR observations. Affected satellites show a significant SNR drop during event periods, which are determined by weather radar observations. Thus, results suggest the possibility of detecting severe weather systems using GNSS-SNR observations.
27 Jun 2023Submitted to ESS Open Archive
08 Jul 2023Published in ESS Open Archive