Daily snow depth in the Southern Andes (2010–2024): a quality-controlled dataset from Chile and Argentina

Seasonal snow is a critical component of the water cycle in the Southern Andes of Chile and Argentina. Quantitative assessments of snow accumulation remain constrained by the scarcity, heterogeneity, and inconsistency of in situ observations, resulting in substantial uncertainties in mountain hydrological modeling. To address this gap, we compiled and quality-controlled snow depth observations to produce a consistent daily dataset from 81 stations between 21 and 54° S covering 2010–2024. Our quality-control procedure involved data compilation and preprocessing, followed by harmonization of snow depth observations, primarily by correcting the ground reference level relative to the soil surface during snow-free periods and removing anomalous spikes and observations outside physically plausible ranges. This process improved data reliability, increasing the Physical Consistency Index (PCI) from 87 % to 95 % at selected stations in the Maipo River Basin, while reducing the median number of days with data across stations by 23 % (from 1392 to 1074 d). The snow depth data availability increased from one station in 2010 to 57 stations in 2024, largely driven by the expansion of the monitoring network operated by the General Directorate of Water (DGA), Chile. However, this expansion remains spatially uneven across the Andean zones. The Mediterranean Andes have the largest number of stations (39), as well as the largest number of stations with highly complete records with 17 stations reaching 80 %–100 % data coverage, compared with only nine stations each in the Arid and Wet Andes, highlighting persistent spatial and temporal gaps. Using this newly quality-controlled dataset, we find that snow depth generally increases from the Arid to the Wet Andes in association with increasing precipitation, whereas its relationship with elevation is not consistently positive. The snow depth-elevation relationship is nonlinear in the Arid and Mediterranean Andes, with maximum observed snow depths at 4300 m a.s.l. in the Elqui River Basin and 3300 m a.s.l. in the Maipo River Basin. In contrast, the available observations indicate a positive snow depth-elevation relationship in the Wet Andes (Maule–Itata River Basin). However, these relationships should be interpreted in the context of the specific spatial and temporal conditions represented by the available observations. This open-access, quality-controlled snow depth dataset (https://doi.org/10.5281/zenodo.21577171, Medina and Caro, 2026) represents the largest and most complete collection of continuous snow depth observations for the Southern Andes and provides a basis for hydrological applications, reanalysis evaluation, and seasonal streamflow forecasting.

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Journal
Earth system science data
Published
2026-09-28
DOI
https://doi.org/10.5194/essd-18-7097-2026
Primary Topic
Cryospheric studies and observations
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article
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article

Daily snow depth in the Southern Andes (2010–2024): a quality-controlled dataset from Chile and Argentina

James McPhee, David Farías-Barahona, Alexis Caro, Nevenka Bulovic et al.
Earth system science data
Cryospheric studies and observations
article

Daily snow depth in the Southern Andes (2010–2024): a quality-controlled dataset from Chile and Argentina

James McPhee, David Farías-Barahona, Alexis Caro, Nevenka Bulovic, Iñigo Irarrázaval, Jorge Huenante, Pierre Pitte, Mauricio Zambrano‐Bigiarini, Cristián Orrego, Sebastian A. Krogh, Ana Hernández‐Duarte, Freddy Alejandro Saavedra, Fernando Gimeno, Shelley A. MacDonell, Mariano Masiokas, Carlos Romero, Javier Medina
article en

Abstract

Seasonal snow is a critical component of the water cycle in the Southern Andes of Chile and Argentina. Quantitative assessments of snow accumulation remain constrained by the scarcity, heterogeneity, and inconsistency of in situ observations, resulting in substantial uncertainties in mountain hydrological modeling. To address this gap, we compiled and quality-controlled snow depth observations to produce a consistent daily dataset from 81 stations between 21 and 54° S covering 2010–2024. Our quality-control procedure involved data compilation and preprocessing, followed by harmonization of snow depth observations, primarily by correcting the ground reference level relative to the soil surface during snow-free periods and removing anomalous spikes and observations outside physically plausible ranges. This process improved data reliability, increasing the Physical Consistency Index (PCI) from 87 % to 95 % at selected stations in the Maipo River Basin, while reducing the median number of days with data across stations by 23 % (from 1392 to 1074 d). The snow depth data availability increased from one station in 2010 to 57 stations in 2024, largely driven by the expansion of the monitoring network operated by the General Directorate of Water (DGA), Chile. However, this expansion remains spatially uneven across the Andean zones. The Mediterranean Andes have the largest number of stations (39), as well as the largest number of stations with highly complete records with 17 stations reaching 80 %–100 % data coverage, compared with only nine stations each in the Arid and Wet Andes, highlighting persistent spatial and temporal gaps. Using this newly quality-controlled dataset, we find that snow depth generally increases from the Arid to the Wet Andes in association with increasing precipitation, whereas its relationship with elevation is not consistently positive. The snow depth-elevation relationship is nonlinear in the Arid and Mediterranean Andes, with maximum observed snow depths at 4300 m a.s.l. in the Elqui River Basin and 3300 m a.s.l. in the Maipo River Basin. In contrast, the available observations indicate a positive snow depth-elevation relationship in the Wet Andes (Maule–Itata River Basin). However, these relationships should be interpreted in the context of the specific spatial and temporal conditions represented by the available observations. This open-access, quality-controlled snow depth dataset (https://doi.org/10.5281/zenodo.21577171, Medina and Caro, 2026) represents the largest and most complete collection of continuous snow depth observations for the Southern Andes and provides a basis for hydrological applications, reanalysis evaluation, and seasonal streamflow forecasting.

Earth system science dataVol. 18(9)
Universidad de Santiago de Chile (CL), Universidad de La Frontera (CL), The University of Queensland (AU), University of Concepción (CL), University of Canterbury (NZ), Universidad de Playa Ancha de Ciencias de la Educación (CL), Instituto de Estudios Avanzados (VE), Centro de Recursos Educativos Avanzados (CL), Gobierno de Chile (CL), Patagonian Ecosystems Investigation Research Center (CL), Center for Climate and Resilience Research (CL), Centro Científico Tecnológico - Mendoza (AR), Advanced Mining Technology Center (CL), University of Chile (CL), University of La Serena (CL)
Clean water and sanitation
Openalex Percentile: Top 16%
Cryospheric studies and observations
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