The aim of this paper is to provide the community with a comprehensive overview of the studies of glaciers in the tropical Andes conducted in recent decades leading to the current status of the glaciers in the context of climate change. In terms of changes in surface area and length, we show that the glacier retreat in the tropical Andes over the last three decades is unprecedented since the maximum extension of the Little Ice Age (LIA, mid-17th–early 18th century). In terms of changes in mass balance, although there have been some sporadic gains on several glaciers, we show that the trend has been quite negative over the past 50 yr, with a mean mass balance deficit for glaciers in the tropical Andes that is slightly more negative than the one computed on a global scale. A break point in the trend appeared in the late 1970s with mean annual mass balance per year decreasing from −0.2 m w.e. in the period 1964–1975 to −0.76 m w.e. in the period 1976–2010. In addition, even if glaciers are currently retreating everywhere in the tropical Andes, it should be noted that this is much more pronounced on small glaciers at low altitudes that do not have a permanent accumulation zone, and which could disappear in the coming years/decades. Monthly mass balance measurements performed in Bolivia, Ecuador and Colombia show that variability of the surface temperature of the Pacific Ocean is the main factor governing variability of the mass balance at the decadal timescale. Precipitation did not display a significant trend in the tropical Andes in the 20th century, and consequently cannot explain the glacier recession. On the other hand, temperature increased at a significant rate of 0.10 °C decade⁻¹ in the last 70 yr. The higher frequency of El Niño events and changes in its spatial and temporal occurrence since the late 1970s together with a warming troposphere over the tropical Andes may thus explain much of the recent dramatic shrinkage of glaciers in this part of the world.

We present a novel approach to simulate and reconstruct annual glacier-wide surface mass balance (SMB) series based on a deep artificial neural network (ANN; i.e. deep learning). This method has been included as the SMB component of an open-source regional glacier evolution model. While most glacier models tend to incorporate more and more physical processes, here we take an alternative approach by creating a parameterized model based on data science. Annual glacier-wide SMBs can be simulated from topo-climatic predictors using either deep learning or Lasso (least absolute shrinkage and selection operator; regularized multilinear regression), whereas the glacier geometry is updated using a glacier-specific parameterization. We compare and cross-validate our nonlinear deep learning SMB model against other standard linear statistical methods on a dataset of 32 French Alpine glaciers. Deep learning is found to outperform linear methods, with improved explained variance (up to +64 % in space and +108 % in time) and accuracy (up to +47 % in space and +58 % in time), resulting in an estimated r² of 0.77 and a root-mean-square error (RMSE) of 0.51 m w.e. Substantial nonlinear structures are captured by deep learning, with around 35 % of nonlinear behaviour in the temporal dimension. For the glacier geometry evolution, the main uncertainties come from the ice thickness data used to initialize the model. These results should encourage the use of deep learning in glacier modelling as a powerful nonlinear tool, capable of capturing the nonlinearities of the climate and glacier systems, that can serve to reconstruct or simulate SMB time series for individual glaciers in a whole region for past and future climates.

Modern hydrology relies on multiple sources of information combined with climatological, hydrological and glaciological data. These data can be collected through various sources such as private initiatives by companies, research programs, and both national and international organisms. They also vary by types, e.g., in situ measurements, satellite, reanalysis and simulated data. Recently the ANDEX research project, as a GEWEX regional program, was created to understand the processes related to the hydrological cycle and energy fluxes in the Andean region from Colombia to Patagonia. It is quite challenging to carry out this program given the complex orography and diversity of climates from tropical to sub-polar climates. This review article is a compilation of the various databases that are useful for hydrometeorological research in the South American Andes. The National Meteorological and Hydrological Services in Bolivia, Chile, Colombia, Ecuador, Peru, Venezuela and Argentina provide a large amount of data however the high-elevation areas are poorly instrumented and the number of stations varies greatly between the countries. National databases are only partially shared with the international bodies responsible for summarizing the existing data; this causes problems in term of data product assimilation. Across the entire continent, too few radiosondes are being used despite the fact that these data are crucial for validating and identifying problems in the atmospheric models. An increasing number of satellite data are available but it is difficult to assimilate them into the hydroclimatological models suited to the adjusted spatial and temporal resolutions. Specifically, for precipitation, we recommend merged products that account for the high spatial and temporal variability across the Andes. Finally, the international ANDEX program could be an excellent opportunity to increase the knowledge of the hydrological processes in the Andes.

Our paleoprecipitation map of the Altiplano reveals the atmospheric processes underlying a major hydroclimatic change 16 ka ago.

Little is known about the fluctuations of the Pyrenean glaciers. In this study, we reconstructed the evolution of Ossoue Glacier (42°46' N, 0.45 km2), which is located in the central Pyrenees, from the Little Ice Age (LIA) onwards. To do so, length, area, thickness, and mass changes in the glacier were generated from historical data sets, topographical surveys, glaciological measurements (2001–2013), a ground penetrating radar (GPR) survey (2006), and stereoscopic satellite images (2013). The glacier has receded considerably since the end of the LIA, losing 40 % of its length and 60 % of its area. Three periods of marked ice depletion were identified: 1850–1890, 1928–1950, and 1983–2013, as well as two short periods of stabilization: 1890–1894, 1905–1913, and a longer period of slight growth: 1950–1983; these agree with other Pyrenean glacier reconstructions (Maladeta, Coronas, Taillon glaciers). Pyrenean and Alpine glaciers exhibit similar multidecadal variations during the 20th century, with a stable period detected at the end of the 1970s and periods of ice depletion during the 1940s and since the 1980s. Ossoue Glacier fluctuations generally concur with climatic data (air temperature, precipitation, North Atlantic Oscillation, Atlantic Multidecadal Oscillation). Geodetic mass balance over 1983–2013 was −1.04 ± 0.06 w.e.a−1 (−31.3 ± 1.9 m w.e.), whereas glaciological mass balance was −1.45 ± 0.85 m w.e. a−1 (−17.3 ± 2.9 m w.e.) over 2001–2013, resulting in a doubling of the ablation rate in the last decade. In 2013 the maximum ice thickness was 59 ± 10.3 m. Assuming that the current ablation rate remains constant, Ossoue Glacier will disappear midway through the 21st century.