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.

SNOWCOP is a Horizon Europe project aimed at developing and evaluating a new high-resolution reanalysis dataset of snow water equivalent (SWE) and glacier ice melt rates for the extra-tropical Andes. The project integrates Copernicus and complementary remote sensing products within a physically based modeling framework to generate daily SWE and ice melt rate maps at 50 m spatial resolution, covering the period from 2002 to the present. These products address a critical observational gap in the region, where ground-based snow and meteorological measurements remain sparse. To support the development and validation of the SNOWCOP workflow, the initial phase of the project focuses on two pilot basins: the Río Maipo (Chile) and the Upper Río Mendoza (Argentina). These basins were selected due to their long term and high-quality instrumental SWE records, making good candidates for method’s evaluation.We present the first results of a retrospective SWE reconstruction that integrates high-resolution daily snow cover maps with snowmelt modeling. The snow cover products are generated by applying a gap-filling and downscaling algorithm to coarse-resolution snow cover fraction data fused with high-resolution multi-source optical observations (Premier et al., 2021). Several snowmelt modeling approaches are evaluated, including a simple temperature-index (TI) model, an enhanced temperature-index (ETI) model (Pellicciotti et al., 2005), and fully physics-based formulations. Model coefficients are derived through calibration against in-situ observations. Meteorological forcings are obtained from ERA5 reanalysis data and dynamically downscaled using MicroMet (Liston & Elder, 2006). The reconstructed SWE is evaluated against ground-based measurements and compared with an existing SWE reanalysis dataset (Cortés & Margulis, 2017). as well as modeling results produced by our team (CHM model - Marsh et al., 2020). References Cortés, G., & Margulis, S. (2017). Impacts of El Niño and La Niña on interannual snow accumulation in the Andes: Results from a high‐resolution 31 year reanalysis. Geophysical Research Letters, 44(13), 6859-6867. Liston, G. E., & Elder, K. (2006). A meteorological distribution system for high-resolution terrestrial modeling (MicroMet). Journal of Hydrometeorology, 7(2), 217-234. Marsh, C. B., Pomeroy, J. W., and Wheater, H. S.: The Canadian Hydrological Model (CHM) v1.0: a multi-scale, multi-extent, variable-complexity hydrological model – design and overview, Geosci. Model Dev., 13, 225–247. Pellicciotti, F., Brock, B., Strasser, U., Burlando, P., Funk, M., & Corripio, J. (2005). An enhanced temperature-index glacier melt model including the shortwave radiation balance: development and testing for Haut Glacier d’Arolla, Switzerland. Journal of glaciology, 51(175), 573-587. Premier, V., Marin, C., Steger, S., Notarnicola, C., & Bruzzone, L. (2021). A novel approach based on a hierarchical multiresolution analysis of optical time series to reconstruct the daily high-resolution snow cover area. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 9223-9240.

The northern slope of the Cerro Solo, located in Southern Patagonian Andes, has a significant instability which could trigger a sudden release of large amounts of water contained in the Torre proglacial lake (Glacial Lake Outburst Flood, GLOF). Such events are highly complex phenomena, with diverse origins and often catastrophic consequences. This paper examines the potential for a rapid increase in the water level caused by a sudden landslide into the Torre Lake, which could lead to an overflow. The subsequent release of water could flood the Fitz Roy River, with the potential to produce damage downstream in El Chalten locality and its surroundings, affecting inhabitants and tourists visiting the area. In this study, various empirical methods for predicting landslide-generated impulse waves are compared. These methods are then applied to model the potential GLOF. The advantages and disadvantages of this procedure are analyzed and discussed. Based on the estimation of peak discharges of lake outflow using empirical formulas, a two-dimensional (2D) hydrodynamic model was implemented to simulate two potential outburst scenarios, with estimated peak discharges of 1166 m3/s and 1769 m3/s. The possible inundation extent and its impact were assessed based on the depth of water and the flow velocity. This study is a preliminary step toward understanding the magnitude of a potential future GLOF event and what elements that could be affected in order to develop an effective response to minimize impact.

In recent decades, glacier retreat has been observed in all the world’s mountain ranges. Over the last 20 years, glaciers in the Andes have lost mass at one of the highest rates on record. Particularly, glaciers in the northern Patagonian Andes show the highest rate of loss of all the Andean regions for the last decade. Detailed records of long-term variations in glacier extent are crucial to put current climate change into context and quantify its impact on mountain areas. In the present study, a reconstruction of the extension (length and area) of the Alerce glacier (41.15° S-71.81° W) for the last 70 years was carried out. By means of historical documents and satellite images (Landsat and Pléiades), detailed maps of glacier fluctuations were generated for the period 1953-2020. Four methodologies were evaluated to measure the front position: i) central flow line; ii) curvilinear box; iii) multiline; and iv) variable box. The magnitude of the front position variations depends on the methodology applied. The method that best addresses glacier front variations over the period analyzed is the variable box method. Between 1953 and 2020, the Alerce glacier lost 35% of its area (1.1±0.1 km2) and 67% of its total length (1.49±0.04 km). It is possible to distinguish periods with different rates of retreat. A stage of slight retreat (-11.3±0.5 ma-1) between 1953 and 1976, followed by a period of stability (-6.7±0.5 ma-1) between 1977 and 1983, then a strong retreat (-58.7±0.5 ma-1) between 1984 and 1999, followed by another period of stability (-5.4±0.5 ma-1) between 2000 and 2009 and, finally, another retreat (-8.7±0.5 ma-1) between 2010 and 2020. The retreat rates for the Alerce glacier mimic those observed in other glaciers in the region, possibly representing a regional climatic signal.

In recent decades, glacier retreat has been observed in all the world's mountain ranges. Over the last 20 years, glaciers in the Andes have lost mass at one of the highest rates on record. Particularly, glaciers in the northern Patagonian Andes show the highest rate of loss of all the Andean regions for the last decade. Detailed records of long-term variations in glacier extent are crucial to put current climate change into context and quantify its impact on mountain areas. In the present study, a reconstruction of the extension (length and area) of the Alerce glacier (41.15 degrees S-71.81 degrees W) for the last 70 years was carried out. By means of historical documents and satellite images (Landsat and Pl & eacute;iades), detailed maps of glacier fluctuations were generated for the period 1953-2020. Four methodologies were evaluated to measure the front position: i) central flow line; ii) curvilinear box; iii) multiline; and iv) variable box. The magnitude of the front position variations depends on the methodology applied. The method that best addresses glacier front variations over the period analyzed is the variable box method. Between 1953 and 2020, the Alerce glacier lost 35% of its area (1.1 +/- 0.1 km 2 ) and 67% of its total length (1.49 +/- 0.04 km). It is possible to distinguish periods with different rates of retreat. A stage of slight retreat (-11.3 +/- 0.5 ma -1 ) between 1953 and 1976, followed by a period of stability (-6.7 +/- 0.5 ma -1 ) between 1977 and 1983, then a strong retreat (-58.7 +/- 0.5 ma -1 ) between 1984 and 1999, followed by another period of stability (-5.4 +/- 0.5 ma -1 ) between 2000 and 2009 and, finally, another retreat (-8.7 +/- 0.5 ma -1 ) between 2010 and 2020. The retreat rates for the Alerce glacier mimic those observed in other glaciers in the region, possibly representing a regional climatic signal.

The hydrometeorological data provided by federal agencies, research groups and private companies tend to be heterogeneous: records are kept in different formats, quality control processes are not standardized and may even vary within a given agency, variables are not always recorded with the same temporal resolution, and there are data gaps and incorrectly recorded values. Once these problems are dealt with, it is useful to have tools to safely store and manipulate the series, providing temporal aggregation, interactive visualization for analysis, static graphics to publish and/or communicate results, techniques to correct and/or modify the series, among others. Here we introduce a package written in the R language using object-oriented programming and designed to accomplish these objectives, giving to the user a general framework for working with any kind of hydrometeorological series. We present the package design, its strengths, limitations and show its application for two real cases.

Abstract The Desert Andes contain >4500 ice masses, but only a handful are currently being monitored. We present the mass changes of the small mountain glacier Agua Negra (1 km2) and of the rest of glaciers in the Jáchal river basin. Remote-sensing data show Agua Negra glacier lost 23% of its area during 1959–2019. Glaciological measurements during 2014–2021 indicate an average annual mass balance of −0.52 m w.e. a−1, with mean winter and summer balances of 0.80 and −1.33 m w.e. a−1, respectively. The Equilibrium Line Altitude (ELA) is estimated to be 5100 ± 100 m a.s.l., which corresponds to an Accumulation Area Ratio (AAR) of 0.28 ± 0.21. Geodetic data from SRTM X and Pléiades show a doubling of the loss rate from −0.32 ± 0.03 m w.e. a−1 in 2000–2013, to −0.66 ± 0.06 m w.e. a−1 in 2013–2019. Comparatively, the ice losses for the entire Jáchal river basin (25 500 km2) derived from ASTER show less negative values, −0.11 ± 16 m w.e. a−1 for 2000–2012 and −0.23 ± 14 m w.e. a−1 for 2012–2018. The regional warming trend since 1979 and a recent decline in snow accumulation are probably driving the observed glacier mass balance.

Over the past 40 years, the HBV (Hydrologiska Byråns Vattenbalansavdelning) hydrological model has been one of the most used worldwide due to its robustness, simplicity, and reliable results.Despite these advantages, the available versions impose some limitations for research studies in mountain watersheds dominated by ice-snow melt runoff (i.e., no glacier module, a limited number of elevation bands, among other constraints).Here we present HBV.IANIGLA, a tool for hydroclimatic studies in regions with steep topography and/or cryospheric processes which provides a modular and extended implementation of the HBV model as an R package.To our knowledge, this is the first modular version of the original HBV model.This feature can be very useful for teaching hydrological modeling, as it offers the possibility to build a customized, open-source model that can be adjusted to different requirements of students and users.

Abstract Glacier ice thickness is crucial to quantifying water resources in mountain regions, and is an essential input for ice-flow models. Using a surface velocity inversion method, we combine ice thickness measurements with detailed surface elevation and velocity data, and derive ice thickness and volume estimates for the Monte Tronador glaciers, North Patagonian Andes. We test the dependence of the inversion model on surface slope by resampling glacier slopes using variable smoothing filter sizes of 16–720 m. While total glacier volumes do not differ considerably, ice thickness estimates show higher variability depending on filter size. Smaller (larger) smoothing scales give thinner (thicker) ice and higher (lower) noise in ice thickness distribution. A filter size of 300 m, equivalent to four times the mean ice thickness, produces a noise-free thickness distribution with an accuracy of 35 m. We estimate the volume of the Monte Tronador glaciers at 4.8 ± 2 km3 with a mean ice thickness of 75 m. Comparison of our results with earlier regional and global assessments shows that the quality of glacier inventories is a significant source of discrepancy. We show that including surface slope as an input parameter increases the accuracy of ice thickness distribution estimates.

Glaciers and the periglacial environment in Argentina have been protected by the Law since 2010. This legislation required the development of the first National Glacier Inventory (NGI), which was officially presented in May 2018 and based on satellite images spanning between 2004 and 2016. Here, we present the methods and results of the NGI, summarize the glaciers' morphological and spatial characteristics, and compare our results to previous regional and global inventories. The NGI reveals an impressive variety of ice masses including rock glaciers, permanent snowfields, mountain and valley glaciers with varying amounts of debris-cover and large outlet glaciers. The Argentinean Andes contain 16 078 ice masses covering an area of 5769 km(2) between 200 and 6900 m a.s.l. Comparison of the combined national inventories of Argentina and Chile (similar to 30 000 glaciers and 28 400 km(2)) with the Randolph Glacier Inventory 6.0 for the Southern Andes (similar to 16 000 glaciers and 29 400 km(2)), shows that there are large differences in extent and number of glaciers in some sub-regions. The NGI represents an improvement for a better understanding of Argentina's freshwater reservoirs and provides detailed information for the preservation and study of ice masses along 4000 km of the Southern Andes.

Based on the recently released National Glacier Inventory (NGI), we analyzed the characteristics and the mass balance rates of ice masses in the Argentinean Central Andes (ca. 30°–37° S). The NGI provides unprecedented information on area, number and distribution of different ice masses, including debris-covered glaciers and rock glaciers. In the Central Andes, a number of 8,076 ice masses were identified covering a total area of 1767 km 2 . For the period 2000–2018, a general lowering of the ice surface was observed with a region-wide mass balance rate of −0.18 ± 0.19 m w.e. yr −1 . Clear differences depending on the debris coverage of the different ice masses were identified, with mass balance rates ranging from −0.36 ± 0.19 m w.e. yr −1 for partly debris-covered glaciers to −0.02 ± 0.19 m w.e. yr −1 for rock glaciers. Considering different sub-periods, the region-wide mass balance rate was slightly positive (+0.12 ± 0.23 m w. e. yr −1 ) from 2000 to 2009 and negative (−0.21 ± 0.30 m w.e. yr −1 ) from 2009 to 2018. A comparison with the Randolph Glacier Inventory (RGI version 6.0) indicates that the NGI provides more detailed information regarding different type of ice masses whereas region-wide mass balance rates show limited sensitivity to the choice of the inventory. The inclusion of rock glaciers and “debris-covered ice with rock glacier” in the NGI causes mass balance rates to be slightly less negative than when using the RGI. Since the Central Andes are experiencing an unprecedented decade-long drought, our study provides crucial information to estimate current and future hydrological contribution of the different type of ice masses to river discharge in the arid subtropical Andes.

The Andes Cordillera contains the most diverse cryosphere on Earth, including extensive areas covered by seasonal snow, numerous tropical and extratropical glaciers, and many mountain permafrost landforms. Here, we review some recent advances in the study of the main components of the cryosphere in the Andes, and discuss the changes observed in the seasonal snow and permanent ice masses of this region over the past decades. The open access and increasing availability of remote sensing products has produced a substantial improvement in our understanding of the current state and recent changes of the Andean cryosphere, allowing an unprecedented detail in their identification and monitoring at local and regional scales. Analyses of snow cover maps has allowed the identification of seasonal patterns and long term trends in snow accumulation for most of the Andes, with some sectors in central Chile and central-western Argentina showing a clear decline in snowfall and snow persistence since 2010. This recent shortage of mountain snow has caused an extended, severe drought that is unprecedented in the hydrological and climatological records from this region. Together with data from global glacier inventories, detailed inventories at local/regional scales are now also freely available, providing important new information for glaciological, hydrological, and climatological assessments in different sectors of the Andes. Numerous studies largely based on field measurements and/or remote sensing techniques have documented the recent glacier shrinkage throughout the Andes. This observed ice mass loss has put Andean glaciers among the highest contributors to sea level rise per unit area. Other recent studies have focused on rock glaciers, showing that in extensive semi-arid sectors of the Andes these mountain permafrost features contain large reserves of freshwater and may play a crucial role as future climate becomes warmer and drier in this region. Many relevant issues remain to be investigated, however, including an improved estimation of ice volumes at local scales, and detailed assessments of the hydrological significance of the different components of the cryosphere in Andean river basins. The impacts of future climate changes on the Andean cryosphere also need to be studied in more detail, considering the contrasting climatic scenarios projected for each region. The sustained work of various monitoring programs in the different Andean countries is promising and will provide much needed field observations to validate and improve the analyses made from remote sensors and modeling techniques. In this sense, the development of a well-coordinated network of high-elevation hydro-meteorological stations appears as a much needed priority to complement and improve the many glaciological and hydro-climatological assessments that are being conducted across the Andes.

Andean glaciers are among the fastest shrinking and largest contributors to sea level rise on Earth. They also represent crucial water resources in many tropical and semi-arid mountain catchments. Yet the magnitude of the recent ice loss is still debated. Here we present Andean glacier mass changes (from 10° N to 56° S) between 2000 and 2018 using time series of digital elevation models derived from ASTER stereo images. The total mass change over this period was −22.9 ± 5.9 Gt yr−1 (−0.72 ± 0.22 m w.e. yr−1 (m w.e., metres of water equivalent)), with the most negative mass balances in the Patagonian Andes (−0.78 ± 0.25 m w.e. yr−1) and the Tropical Andes (−0.42 ± 0.24 m w.e. yr−1), compared to relatively moderate losses (−0.28 ± 0.18 m w.e. yr−1) in the Dry Andes. Subperiod analysis (2000–2009 versus 2009–2018) revealed a steady mass loss in the tropics and south of 45° S. Conversely, a shift from a slightly positive to a strongly negative mass balance was measured between 26 and 45° S. In the latter region, the drastic glacier loss in recent years coincides with the extremely dry conditions since 2010 and partially helped to mitigate the negative hydrological impacts of this severe and sustained drought. These results provide a comprehensive, high-resolution and multidecadal data set of recent Andes-wide glacier mass changes that constitutes a relevant basis for the calibration and validation of hydrological and glaciological models intended to project future glacier changes and their hydrological impacts. Glaciers in the Andes have lost about 23 Gt of mass per year between 2000 and 2018, with the fastest loss in Patagonia, according to time series of digital elevation models that are based on ASTER stereo images.

The prominent Andes cordillera induces significant differences in climates between its eastern and western slopes. These climatic differences are largely reflected by contrasting vegetation and ice coverages but remain poorly documented. This study quantifies the abrupt changes of precipitation and cloud properties at both sides of the Andes south of 20 degrees S by using surface daily precipitation and satellite (CloudSat and MODIS) data during the 2006-2016 period. Results show that the precipitation changes drastically and precipitating clouds can be of very different nature on each side of the Andes. In the tropical Andes (20-25 degrees S), precipitation normally falls from a sole layer of thick stratiform and convective precipitating clouds during the warm semester, but the annual mean accumulation is about 10-100 times larger on the eastern than on the western slopes. A sole layer of low stratus clouds dominates over the Pacific coast, occasionally producing light rains, whereas high, thin, and non-precipitating clouds dominate most of the time over the continent. In the subtropical Andes (25-35 degrees S), annual mean precipitation is similar on both sides, however, it falls from convective and stratiform precipitating clouds in the warm semester on the eastern slopes, and from stratiform precipitating clouds in the cold semester, mostly as frozen particles, on the western slopes. These different features on both slopes denote a climatic transition between the tropics and extratropics. In the extratropical Andes (south of 35 degrees S), stratiform cloud types produces precipitation on both sides during all the year, but the annual mean precipitation and cloud frequency are enhanced on the western slopes and strongly reduced on the eastern slopes of the Andes. Cloud frequencies are higher than in the subtropics and evenly distributed as single- or multi-layers of low, middle and high clouds. Frozen particles become important in precipitating clouds over the mountains and on the lee side. These findings demonstrate the significant influence of the Andes cordillera on the climate all along southwestern South America, and constitute an excellent example of how the simple dependence of climate on latitude can be substantially altered by the topography.

The rivers originating in the southern Andes (18°–55°S) support numerous ecosystems and a large number of human populations and socio-economic activities in the adjacent lowlands of Chile, Argentina and Bolivia. Here we show that ca. 75% of the total variance in the streamflow records from this extensive region can be explained by only eight spatially coherent patterns of variability. Five (three) of these Andean patterns exhibit extreme dry (wet) conditions in recent years, with strong interannual variations in northern Chile; long-term drying trends between 31° and 41°S; a transitional pattern in the central Patagonian Andes; and increasing trends in northwestern Argentina and southern Bolivia, the Fueguian Andes, and the eastern portion of the South Patagonian Icefield. Multivariate regression analyses show that large-scale indices of ENSO variability can predict 20% to 45% of annual runoff variability between 28° and 46°S. The influence of Antarctic and North Pacific indices becomes more relevant south of 43°S and in northwestern Argentina and southern Bolivia, respectively, but their overall skill as predictors of Andean streamflows is weak. The analyses provide relevant new information to improve understanding of the spatial coherence, the main temporal features, and the ocean-atmospheric forcings of surface runoff across the southern Andes.

Glaciers in the northern Patagonian Andes (35–46° S) have shown a dramatic decline in area in the last decades. However, little is known about glacier mass balance changes in this region. This study presents a geodetic mass balance estimate of Monte Tronador (41.15° S; 71.88° W) glaciers by comparing a Pléiades digital elevation model (DEM) acquired in 2012 with the Shuttle Radar Topography Mission (SRTM) X-band DEM acquired in 2000. We find a slightly negative Monte-Tronador-wide mass budget of −0.17 m w.e. a−1 (ranging from −0.54 to 0.14 m w.e. a−1 for individual glaciers) and a slightly negative trend in glacier extent (−0.16 % a−1) over the 2000–2012 period. With a few exceptions, debris-covered valley glaciers that descend below a bedrock cliff are losing mass at higher rates, while mountain glaciers with termini located above this cliff are closer to mass equilibrium. Climate variations over the last decades show a notable increase in warm season temperatures in the late 1970s but limited warming afterwards. These warmer conditions combined with an overall drying trend may explain the moderate ice mass loss observed at Monte Tronador. The almost balanced mass budget of mountain glaciers suggests that they are probably approaching a dynamic equilibrium with current (post-1977) climate, whereas the valley glaciers tongues will continue to retreat. The slightly negative overall mass budget of Monte Tronador glaciers contrasts with the highly negative mass balance estimates observed in the Patagonian ice fields further south.

Los glaciares constituyen reservas hídricas en estado sólido y son componentes cruciales del sistema hidrológico de montaña. A pesar de su importancia, no existía en Argentina información precisa sobre el número, ubicación y tamaño de estos cuerpos de hielo. En el año 2010, se sanciona la Ley 26639 de “Presupuestos Mínimos para la Preservación de los Glaciares y el Ambiente Periglacial”, que tiene como principales objetivos proteger los glaciares considerados como reservas estratégicas de recursos hídricos y crear el Inventario Nacional de Glaciares (ING), donde se individualicen todos los glaciares y geoformas periglaciales que actúan como reservas hídricas con toda la información necesaria para su adecuada protección, control y monitoreo. El inventario y monitoreo del estado de los glaciares y del ambiente periglacial es llevado a cabo por el Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales (IANIGLA-CONICET) con la coordinación de la autoridad nacional de aplicación de la ley, el Ministerio de Ambiente y Desarrollo Sustentable de Argentina (MAyDS). Este inventario se realiza en tres niveles que varían en complejidad y extensión espacial. En este trabajo se presentan los resultados preliminares obtenidos en el primer nivel, que consiste en el mapeo y caracterización de glaciares (descubiertos, cubiertos, manchones de nieve y de escombros) mediante sensores remotos. Estos datos son luego verificados en el campo en sectores seleccionados. Sobre un total de 70 cuencas y subcuencas delimitadas para el inventario se ha avanzado en 64. Hasta febrero de 2017, se han inventariado 15,482 glaciares que cubren una superficie de 5743 km2

Glaciers are sensitive indicators of climate change. Particularly, glacier surface velocity constitutes a key parameter for estimating ice volume variations as response to global warming and its incidence in sea level rise. Several methodologies based in remotely sensed data have been employed for estimating ice velocity fields. They are mostly based in cross-correlating pairs of images in order to track features displacement between two dates. High ice flux velocity, which can reach more than 1km/year, constitute a challenge for the existing methodologies, in practice limiting to a few days the time span between useful data. In this work we present an extension of the known Pixel Offset – Small Baseline Subsets (PO-SBAS) technique, that profit a set of successive Synthetic Aperture Radar (SAR) scenes for computing displacement time series and ice velocity fields. The algorithm is guided by a preliminary ice velocity model estimated from the data itself, which significantly improves the results reliability and reduces the overall computational cost. Furthermore, it implements a processing scheme that considers the displacement estimations (PO) quality in order to decide which pixels are included in the time-series inversion. The proposed technique is applied to 22 COSMO-Skymed SAR images of Viedma Glacier (Southern Patagonian Icefield, Argentina) spanning roughly a year. The results obtained are robust and make profit of the whole available dataset. Resulting mean velocity field and displacement time series show the algorithm suitability for retrieving and characterizing complex ice motion patterns.