Bolibar, J. ALPGM (ALpine Parameterized Glacier Model) v1.1. Our previous work31 has shown that linear MB models can be correctly calibrated for data around the mean temperature and precipitation values used during training, giving similar results and performance to deep learning. Glaciers smaller than 0.5km2 often display a high climate imbalance, with their equilibrium line being higher than the glaciers maximum altitude. Glacier-wide MB is simulated annually for individual glaciers using deep learning (i.e. Google Scholar. Data 12, 19731983 (2020). Front. 1). Park, and S. Beason. As the Earth heats up due to climate change, glaciers are melting. Fr Hydrobiol. CPDD, winter snowfall or summer snowfall) was modified for all glaciers and years. The Cryosphere 13, 11251146 (2019). 44, 13761383 (2017). Since these flatter glaciers are more likely to go through extreme negative MB rates, nonlinear responses to future warming play a more important role, producing cumulative MB differences of up to 20% by the end of the century (Fig. This parametrization reproduces in an empirical manner the changes in glacier geometry due to the combined effects of ice dynamics and MB. Geosci. Regarding air temperature forcings, the linear Lasso MB model was found to be slightly under-sensitive to extreme positive cumulative PDD (CPDD) and over-sensitive to extreme negative CPDDs. A.R. Thus, glacier sensitivity to a step change in climate , glacier response to climate trends , and glacier variance driven by stochastic climate fluctuations are all proportional to , making an important number to constrain. 3). Previous studies on 21st century large-scale glacier evolution projections have covered the French Alps7,8. 282, 104115 (2003). The Lasso30, used for the linear mass balance model, is a linear regression analysis method which shrinks model parameters, thus performing both variable selection and regularization. Particularly in Asia, water demand exceeds supply due to rapid population growth, with glacier . Magnin, F., Haeberli, W., Linsbauer, A., Deline, P. & Ravanel, L. Estimating glacier-bed overdeepenings as possible sites of future lakes in the de-glaciating Mont Blanc massif (Western European Alps). a deep artificial neural network) or the Lasso (regularized multilinear regression)30. Nisqually Glacier in Mount Rainier National Park, Wash., covers 2.5 square miles (6.5 square kilometers) (1961) and extends from an altitude of about 14,300 feet (4,400 meters) near the top of Mount Rainier down to 4,700 feet (1,400 meters), in a horizontal distance of 4.1 miles (6.6 kilometers). To obtain 51, 313323 (2005). Planet. All climate anomalies are computed with respect to the 19672015 mean values. We acknowledge the more than 50 years of glaciological monitoring performed by the GLACIOCLIM French National Observatory (https://glacioclim.osug.fr), which provided essential observations for our modelling study. Ice melt sensitivity to PDDs strongly decreases with increasing summer temperatures, whereas snow melt sensitivity changes at a smaller rate34. Years in white in c-e indicate the disappearance of all glaciers in a given massif. the Open Global Glacier Model - OGGM9) is likely to be less affected by an over-sensitivity to future warming than a more complex model with dedicated DDFs for ice, snow, and firn. 47 (2020). S1a). snowfall, avalanches and refreezing) and the mass lost via different processes of ablation (e.g. Such glaciers are often remnants of the Little Ice Age, and mainly lose mass via non-dynamic downwasting51. Ecol. Strong Alpine glacier melt in the 1940s due to enhanced solar radiation. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. 3a). Nature Communications thanks Mohd Anul Haq, Lauren Vargo, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Ecography 40, 913929 (2017). Together with recent findings by another study41 highlighting the increased uncertainties in ice thickness distribution estimates of ice caps compared to mountain glaciers, our results raise further awareness on the important uncertainties in glacier projections for ice caps. Envelopes indicate based on results for all 660 glaciers in the French Alps for the 19672015 period. You are using a browser version with limited support for CSS. Deep artificial neural networks (ANNs) are nonlinear models that offer an alternative approach to these classic methods. Hydrol. New research suggests that climate change-induced melting of the Nisqually Glacier near Seattle, Wash., and other high-elevation glaciers will offset seasonal declines in streamflow until. Earth Syst. 3, 16751685 (2019). glacier length12,14. Ice caps in the Canadian Arctic, the Russian Arctic, Svalbard, and parts of the periphery of Greenland are major reservoirs of ice, as well as some of the biggest expected contributors to sea level rise outside the two polar ice sheets7. 22, 21462160 (2009). Earth Planet. Earths Future 5, 418435 (2017). The rest of the story appears to lie primarily in the unique dynamic response of the region's glaciers to climate change. By the end of the century, we predict a glacier volume loss between 75 and 88%. However, glacier projections under low-emission scenarios and the behaviour of flatter glaciers and ice caps are likely to be biased by mass balance models with linear sensitivities, introducing long-term biases in sea-level rise and water resources projections. An increase in the thickness of ice in the higher portion of the Nisqually Glacier was first observed by Arthur Johnson Reference Johnson 1 about ten years ago, and the progress of this "wave" of increased ice thickness has been measured by Johnson each year since that time. In this study, we demonstrated the advantages of using deep learning to model glacier MB at regional scales, both in terms of variance and bias. Despite their limitations, temperature-index models, owing to their simplicity and parsimonious data requirements, have been widely used for large-scale glacier projections7,8. Importance and vulnerability of the worlds water towers. Three different types of cross validation were performed: a Leave-One-Glacier-Out (LOGO), a Leave-One-Year-Out (LOYO) and a Leave-Some-Years-and-Glaciers-Out (LSYGO). H.Z. A recent Northern Hemisphere temperature reconstruction indicates an oscillating temperature drop from A.D. 1000-1850 of about 0.2C with a subsequent and still continuing warming of nearly 0.8C ( 3 ). S5 and S6). Swiss glaciers have displayed less negative MB rates than French glaciers during the last decades, thus likely introducing a bias in simulations specific to the French Alps. Greenland's melting glaciers, which plunge into Arctic waters via steep-sided inlets, or fjords, are among the main contributors to global sea level rise in response to climate change. on various mass balance and radiation components) are opening the door for updated and better constrained projections. Canada's glaciers and ice caps are now a major contributor to sea level change, a new UCI study shows. The ice thickness data for two of the largest glaciers in the French Alps were modified in order to improve data quality. Share sensitive information only on official, secure websites.. Geophys. "Such glaciers spawn icebergs into the ocean or lakes and have different dynamics from glaciers that end on land and melt at their front ends. J.B. was supported by a NWO VIDI grant 016.Vidi.171.063. In order to overcome these differences, some adaptations were performed to the GloGEMflow output, accompanied with some hypotheses to ensure a realistic comparison. Alpine glaciers, like this one near Mt. GloGEMflow relies on EURO-CORDEX ensembles26, whereas ALPGM uses ADAMONT25, an adjusted version of EURO-CORDEX specifically designed for mountain regions. Nature 577, 364369 (2020). Glacier surface mass changes are commonly modelled by relying on empirical linear relationships between PDDs and snow, firn or ice melt8,9,10,29. 1a). A comprehensive bibliography of scientific publications relating to the glacier is included. 5). 3). MATH Z. et al. By unravelling nonlinear relationships between climate and glacier MB, we have demonstrated the limitations of linear statistical MB models to represent extreme MB rates in long-term projections. a1), but when conditions deviate from this mean training data centroid, the Lasso can only linearly approximate the extremes based on the linear trend set on the main cluster of average values (Fig. Indeed, the projected 21st century warming will lead to increasing incoming longwave radiation and turbulent fluxes, with no marked future trends in the evolution of shortwave radiation37. Nonlinear sensitivity of glacier mass balance to future climate change unveiled by deep learning. A globally complete, spatially and temporally resolved estimate of glacier mass change: 2000 to 2019. https://meetingorganizer.copernicus.org/EGU2020/EGU2020-20908.html (2020) https://doi.org/10.5194/egusphere-egu2020-20908. Then, we ran multiple simulations for this same period by altering the initial ice thickness by 30% and the glacier geometry update parametrizations by 10%, according to the estimated uncertainties of each of the two methods31. The Cryosphere 12, 13671386 (2018). However, as shown in our previous work and confirmed here, the accuracy of linear models drastically drops as soon as the input climate data diverges from the mean cluster of values used for training. Advances occurred from 1963-68 and from 1974-79. If material is not included in the articles Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. Monitoring the Seasonal hydrology of alpine wetlands in response to snow cover dynamics and summer climate: a novel approach with sentinel-2. 1 and S1). Preliminary results suggest winter accumulation in 2018 was slightly above the 2003-2017 average for the Emmons & Nisqually. Glacier topography is a crucial driver of future glacier projections and is expected to play an important role in determining the magnitude that nonlinearities will have on the mass balance. J. Glaciol. 4e). Nevertheless, we previously demonstrated that glacier surface area is not an important predictor of MB changes in our models29, and ice caps evolve mostly through thinning and not shrinking (Fig. We reduced these differences by running simulations with GloGEMflow using exactly the same 29 climate members used by ALPGM in this study (TableS1). Regarding air temperature, a specific CPDD anomaly ranging from 1500 PDD to +1500 PDD in steps of 100 PDD was prescribed to all glaciers for each dataset copy. Glacier landscapes are expected to see important changes throughout the French Alps, with the average glacier altitude becoming 300m (RCP 4.5) and 400m (RCP 8.5) higher than nowadays (Fig. Swiss Glacier Mass Balance (release 2019). GLAMOS. S5h, j, l). Simulations for projections in this study were made by generating an ensemble of 60 cross-validated models based on LSYGO.

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