Analysis of atmospheric variations using GNSS signal as atmospheric sensor (PWV-GNSS) in the extreme rainfall events in Rio Grande do Sul (Brazil) in 2024

Abstract At the end of April and beginning of May 2024, the state of Rio Grande do Sul, Brazil, experienced an unprecedented climatic disaster. A combination of meteorological factors,including extreme accumulated precipitation,and the region’s topography led to a rapid and severe rise in river levels. Therefore, numerous cities were inundated, leaving both people and animals homeless, and resulting in several fatalities. Given the magnitude of these events, this study aims to understand their underlying causes and explore strategies for identifying them both retrospectively and in near-real-time (nowcasting). To this end, we analyzed direct and indirect atmospheric measurements over the most affected areas in Rio Grande do Sul, particularly the cities of Porto Alegre and Santa Maria. Data were obtained from multiple sources, encompassing observations at the surface and throughout the atmospheric column. We mapped precipitable water vapor (PWV), precipitation, and flood extents. The recorded disasters were associated with accumulated rainfall levels that were over three times higher in Porto Alegre (457 mm) and five times higher in Santa Maria (719 mm) compared to previous El Niño events (2015 and 2016). Our findings underscore GNSS-derived PWV as a near-real-time predictor of extreme rainfall with up to 60 min of lead time .