GNSS-derived tropospheric water vapor and precipitation co-variability along continental Chile

Chile's diverse climate spans a remarkable range, from the hyper-arid desert in the north to a Mediterranean climate in the center, temperate humid conditions in the south, and polar tundra in Patagonia. This climatic gradient provides a unique opportunity to study the synchronized variability of tropospheric water vapor (TWV) and precipitation processes. In recent years, GNSS has emerged as a powerful satellite-based tool capable of capturing not only tectonic deformation but also meteorological processes. One of the key parameters derived from GNSS processing is Zenith Total Delay (ZTD), which represents the delay in GNSS signal propagation caused by the troposphere. ZTD is composed of the hydrostatic and wet delays, with the wet delay closely linked to TWV, making it an essential metric for studying atmospheric water vapor dynamics. We use GNSS ZTD observations, spanning between 15 and 28 years, to analyze the intra-seasonal and interannual probability density functions (PDFs) of TWV. Additionally, we examine the co-variability between daily average TWV and accumulated precipitation to establish links between TWV peaks and precipitation events.

Our results reveal significant differences in TWP PDFs across Chile, ranging from log-normal to normal and inverse log-normal distributions. Notably, the relationship between TWV and precipitation is stronger in central, southern, and Patagonian regions, suggesting regional variability in underlying atmospheric processes. Potential mechanisms driving these differences, such as climatic controls and local meteorological dynamics, are discussed in detail.

These findings provide a benchmark for evaluating the representativeness of general circulation models (GCMs) by comparing observed and modeled TWV distributions. Furthermore, they lay the groundwork for future research into the TWV-precipitation relationship at daily and sub-daily timescales, critical for improving weather forecasts and understanding hydrological processes.