Decoding the signal of extreme weather events in the Azores archipelago using GNSS and atmospheric reanalysis products

The rapidly changing climate is amplifying both the frequency and severity of extreme weather events in the Azores archipelago, Portugal. Understanding the underlying dynamics of these events is essential for effective mitigation. Atmospheric water vapor data derived from the Global Navigation Satellite System (GNSS) data and reanalysis outputs from an atmospheric general circulation model offer valuable tools for studying the behavior of weather fronts around the Atlantic Ocean environment of the Azores. This research aims to conduct a detailed comparison between GNSS-based measurements and atmospheric reanalysis data, such as those available from ERA/MERRA2, focusing on the detection of small-scale atmospheric structures with high temporal resolution. We utilize atmospheric reanalysis products to decode long-term trends in the frequency and severity of extreme weather events in the Azores. We then apply statistical methods to identify consistencies and differences between these two approaches in capturing atmospheric water vapor patterns. By combining water-vapor estimates from both GNSS data and atmospheric reanalysis, we are able to characterize the dynamics of atmospheric turbulence from small (few meters) to large (few tens of kilometers) scales.