Ground-based GNSS network and integrated water vapor mapping during the development of severe storms at the Cuyo region (Argentina)

Abstract

Mendoza is a province of Argentina located between 32° S and 34° S at the leeside of the Andes Foothills. Very intense thunderstorms form between October and March (southern hemisphere summer), which produce large hail and damage in crops and properties. Although some hypotheses and conceptualmodelswere proposed in order to identify key possible mechanisms that contribute to trigger convection, they are still waiting for the validation process. As moisture is the main ingredient for storms formation, the identification of its geographical distribution could be used together with other synoptic and mesoscale forcing features to forecast intense convective events. A novel technique in estimating moisture concentration and its geographical distribution has been introduced in order to observe the influx and variability of humidity at this region, during a 45-day period in midsummer. In doing so, we resort to the information provided by the ground-based Global Navigation Satellite System (GNSS) network.More than 300 active stations constitute the continuously operating GNSS network over Southern and Central America (SIRGAS-CON, Sistema de Referencia Geocéntrico para las Américas de Operación Continua). This network allows to retrieve integrated water vapor (IWV) content, mapping this variable by the use of a digital model of terrain. In the period and region under study, a prevailing influx of humidity<br />from N and NE and a high correlation between the accumulation/depletion of humidity and the hail/no hail precipitation days is observed.We discuss in particular the development of five storms detected by the S-Band radar network belonging to the Province ofMendoza. Although the results strongly suggest that IWVmaps are capable to represent the humidity dynamics in the considered region, it is still important to highlight that the calculated values for IWV are unrealistic at some locations as the consequence of deep atmospheric gradients. These biases may be explained by the fact that the GNSS observations are made over the whole horizon of each given site.