The Southern Andes Daily Snow Depth Dataset (2010–2024): Quality–Controlled Dataset from Chile and Argentina

Abstract. The snowpack is a critical component of the water cycle in the Southern Andes of Chile and Argentina. In this region, quantitative assessments of snow accumulation remain limited by the scarcity, heterogeneity, and inconsistency of in situ observations, leading to large uncertainties in mountain hydrological modeling. To address this gap, we compile and quality–control snow depth observations, which are more spatially extensive and have a higher temporal resolution than snow water equivalent measurements, producing a consistent daily dataset of 81 stations between 21° S and 54° S for the period 2010–2024. Our quality-control procedure was primarily based on an adjustment of the snow depth ground reference level defined as the soil surface during snow-free periods, followed by the removal of anomalous spikes and observations outside physically plausible ranges. This process substantially improved data reliability, increasing the Physical Consistency Index (PCI), a multivariable metric that evaluates whether snow accumulation events are consistent with precipitation occurrence and lower temperatures, from 87 % to 95 % at some stations, while reducing the median data availability across all stations by 23 % (from 1,392 to 1,074 observations). The snow depth data availability increased markedly over time, from only one station in 2010, to 14 stations in 2015, and up to 57 stations in 2024, largely driven by expanded monitoring efforts of the General Directorate of Water, Chile. However, this expansion remains uneven across the Andean zones. The Mediterranean Andes concentrate the highest station density (39) and the largest number of highly complete records, with 17 stations reaching 80–100 % data coverage. In contrast, both the Arid Andes and the Wet Andes have only nine stations each reaching the same level of completeness, highlighting persistent spatial and temporal gaps. Using this newly quality–controlled dataset, we find that snow depth increases with precipitation from the Arid to the Wet Andes, but does not necessarily increase with elevation. The snow depth–elevation relationship is nonlinear in the Arid and Mediterranean Andes, with maximum accumulation at 4,300 m a.s.l. in the Elqui River Basin and 3,300 m a.s.l. in the Maipo River Basin. In contrast, a positive relationship emerges in the Wet Andes (Maule–Itata River Basin). This open–access, quality–controlled snow depth dataset (Medina and Caro, 2026, https://doi.org/10.5281/zenodo.20089265) represents the largest and most complete collection of continuous snow depth data for the Southern Andes, providing a robust basis for hydrological applications, such as model forcing and calibration, empirical analyses, reanalysis evaluation, and improved seasonal streamflow forecasting.