GPS-SNR-based detection of severe weather events: two case studies of
summer 2021 in Switzerland
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.