GPS-SNR-based Detection of Severe Weather Events: Two Case Studies of Summer 2021 in Switzerland

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.