Reanalysis of 47 Years of Climate in the French Alps (19582005): Climatology and Trends for Snow Cover. These differences in the received climate signal are explained by the retreat of glaciers to higher altitudes, which keep up with the warming climate in RCP 4.5 but are outpaced by it under RCP 8.5. a Glacier-wide annual MB, b Ice volume, c Glacier area. Global glacier mass changes and their contributions to sea-level rise from 1961 to 2016. is central to a glacier's response: Fig.2ashows 1L.t/for a warming trend of 1 C per century, for three glaciers with dierent (and fixed ). Therefore, linear MB models present more limitations for projections of ice caps, showing a tendency to negative MB biases. In fact, in many cases the surface lowering into warmer air causes this impact on the MB to be negative, further enhancing extreme negative mass balance rates. At present, using complex surface energy balance models for large-scale glacier projections is not feasible yet, mainly due to the lack of input data. A small ablation increase may cause . A dataset of 32 glaciers with direct annual glacier-wide MB observations and remote sensing estimates was used to train the models. Without these cold water resources during the hottest months of the year, many aquatic and terrestrial ecosystems will be impacted due to changes in runoff, water temperature or habitat humidity6,21,22. 3, 16751685 (2019). MathSciNet Glob. In many aspects, it might be too optimistic, as many ice caps will have a negative impact on MB through thinning, bringing their mean surface elevation to lower altitudes, thus further warming their perceived climate. Our results confirm an over-sensitivity of temperature-index models, often used by large-scale studies, to future warming. Summer melt was also above average. H.Z. Hock, R. et al. Partitioning the uncertainty of ensemble projections of global glacier mass change. By monitoring the change in size of glaciers around the world, scientists can learn about global climate change. The estimated ice thickness for Mer de Glace (28.87km2 in 2015) was increased by 25% in order to correct the bias with respect to field observations31. Huss, M. et al. This work was funded by the Labex OSUG@2020 (Investissements davenir, ANR10 LABX56) and the Auvergne-Rhne-Alpes region through the BERGER project. A glacier flows naturally like a river, only much more slowly. Glacier shrinkage in the Alps continues unabated as revealed by a new glacier inventory from Sentinel-2. Hastie, T., Tibshirani, R. & Friedman, J. a deep artificial neural network) or the Lasso (regularized multilinear regression)30. 1a). 12, 909931 (2019). 6 (2018). The linear Lasso MB model suggests a stabilization of glacier evolution, reaching neutral MB rates by the end of the century. "It has been pretty much doing this nonstop since the mid-1800s." The Nisqually Glacier is losing nearly a quarter of a mile in length a year, Kennard added. With a secondary role, glacier model uncertainty decreases over time, but it represents the greatest source of uncertainty until the middle of the century8. Bolibar, J. et al. We argue that such models can be suitable for steep mountain glaciers. To interactively describe to response of glaciers to climate change, a glacier parameterization scheme has been developed and implemented into the regional climate model REMO. 4 ). Temperature-index models are known to be over-sensitive to temperature changes, mainly due to important differences in the processes contributing to future warming. This enables the recalculation of every topographical predictor used for the MB model, thus updating the mean glacier altitude at which climate data for each glacier are retrieved. These trends explored with energy balance models from the literature correspond to the behaviour captured by our deep learning MB model, with a clearly less sensitive response of glacier-wide MB to extreme climate forcings, particularly in summer (Fig. Glaciers are large-scale, highly sensitive climate instruments which, ideally, should be picked up and weighed once a year. J. Glaciol. Additionally, the specific responses of the deep learning and Lasso MB models to air temperature and snowfall were extracted by performing a model sensitivity analysis. The same was done with winter snowfall anomalies, ranging between 1500mm and +1500mm in steps of 100mm, and summer snowfall anomalies, ranging between 1000mm and +1000mm in steps of 100mm. 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. The performance of this parametrization was validated in a previous study, indicating a correct agreement with observations31. Additionally, glacier surface area was found to be a minor predictor in our MB models31. Researchers analyzed almost 2 million satellite images of the glaciers and found that 94 . Marzeion, B. et al. Clarke, G. K. C., Berthier, E., Schoof, C. G. & Jarosch, A. H. Neural networks applied to estimating subglacial topography and glacier volume. 3). Glacier-wide MB is simulated annually for individual glaciers using deep learning (i.e. Canada's glaciers and ice caps are now a major contributor to sea level change, a new UCI study shows. regularized multilinear regression. Long-term historical interactions between French society and glaciers have developed a dependency of society on them for water resources, agriculture, tourism18particularly the ski business19and hydropower generation. A similar trend is under way. Source: Mount Rainier National Park 47 (2020). This synthetic experiment is an approximation of what might occur in other glacierized regions with ice caps. Soc. Cross-validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure. 3c). Mer de Glace, 29km2 in 2015), which did show important differences under RCP 8.5 (up to 75%), due to their longer response time. The main reason for their success comes from their suitability to large-scale studies with a low density of observations, in some cases displaying an even better performance than more complex models12. Vertical axes are different for the two analyses. Paul, F., Kb, A., Maisch, M., Kellenberger, T. & Haeberli, W. Rapid disintegration of Alpine glaciers observed with satellite data: disintegration of alpine glaciers. The record, which was started in 1931, shows the glacier's dramatic responses to about half a century of small but significant climatic variations. This rapid glacier retreat is already having an environmental impact on natural hazards20, mountain ecosystems21, and biodiversity6. For small perturbations, the response time of a glacier to a perturbation in mass balance can be estimated by dividing the maximum thickness of the glacier by the balance rate at the terminus. Multiple copies of this dataset were created, and for each individual copy a single predictor (i.e. DDFs are known to vary much less with increasing temperatures for intermediate values of albedo (i.e. Several differences are present between ALPGM, the model used in this study, and GloGEMflow (TableS2), which hinder a direct meaningful comparison between both. These measurements of surface elevation were begun by personnel of the Tacoma Planet. Lett. Rveillet, M. et al. Each one of these models was created by training a deep learning model with the full dataset except all data from a random glacier and year, and evaluating the performance on these hidden values. Correspondence to Fundam. Taking into account that for several regions in the world about half of the glacierized volume will be lost during this first half of the 21st century, glacier models play a major role in the correct assessment of future glacier evolution. GloGEMflow10 is a state-of-the-art global glacier evolution model used in a wide range of studies, including the second phase of GlacierMIP7,8. Ser. Maussion, F. et al. A consensus estimate for the ice thickness distribution of all glaciers on Earth. Zemp, M. et al. Strong Alpine glacier melt in the 1940s due to enhanced solar radiation. Alternatively, the comparisons against an independent large-scale glacier evolution model were less straightforward to achieve. The new research suggests that the world's glaciers are disappearing more quickly than scientists previously estimated, and they . Due to the statistical nature of the Lasso model, the response to snowfall anomalies is also highly influenced by variations in PDDs (Fig. 4), as the linear model tends to over-estimate positive MB rates both from air temperature and snowfall (Fig. Park, and S. Beason. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (2018). 4e and 5). Since the neural network used here virtually behaves like a black box, an alternative way is needed to understand the models behaviour. We also use this method to extract glacier borderlines from satellite images across the western Lenglongling mountains. Since the climate and glacier systems are known to be nonlinear13, we investigate the benefits of using a model treating, among others, PDDs in a nonlinear way in order to simulate annual glacier-wide MB at a regional scale. This dataset applies a statistical adjustment specific to French mountain regions based on the SAFRAN dataset, to EURO-CORDEX26 GCM-RCM-RCP members, covering a total of 29 different future climate scenarios for the 20052100 period. S5b). The anomaly in snowfall was evenly distributed for every month in the accumulation (October 1April 31) and ablation seasons, respectively. Farinotti, D., Round, V., Huss, M., Compagno, L. & Zekollari, H. Large hydropower and water-storage potential in future glacier-free basins. 3). This creates an interesting dilemma, with more complex temperature-index MB models generally outperforming simpler models for more climatically homogeneous past periods but introducing important biases for future projections under climate change. 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). Nature 568, 382386 (2019). Our results show that the mean elevation is far more variable than the kinematic ELA ( Fig. Moreover these three aspects of glacier behavior are inextricably interwoven: a high sensitivity to climate change goes hand-in-hand with a large natural variability. In order to investigate the effects of MB nonlinearities on ice caps, we performed the same type of comparison between simulations, but the glacier geometry update module described in the Glacier geometry evolution section was deactivated. The maximum advance of Nisqually Glacier in the last thousand years was located, and retreat from this point is believed to have started about 1840. Finally, there are differences as well in the glacier dynamics of both models, with ALPGM using a glacier-specific parameterized approach and GloGEMflow explicitly reproducing the ice flow dynamics. Previous studies on 21st century large-scale glacier evolution projections have covered the French Alps7,8. Thank you for visiting nature.com. Despite the existence of slightly different trends during the first half of the century, both the Lasso and the temperature-index model react similarly under RCP 4.5 and 8.5 during the second half of the century, compared to the deep learning model. Comput. Share sensitive information only on official, secure websites.. For such cases, we assumed that ice dynamics no longer play an important role, and the mass changes were applied equally throughout the glacier. The two models with linear MB responses to PDDs and accumulation simulate more positive MB rates under RCP 2.6, highlighting their over-sensitivity to negative air temperature anomalies and positive snowfall anomalies (Fig. The high spatial resolution enables a detailed representation of mountain weather patterns, which are often undermined by coarser resolution climate datasets. The glacier ice volume in the French Alps at the beginning of the 21st century is unevenly distributed, with the Mont-Blanc massif accounting for about 60% of the total ice volume in the year 2015 (7.06 out of 11.64km3, Fig. 1). Ten . J. Hosp. Both DEMs were resampled and aligned at a common spatial resolution of 25m. For each glacier, an individual parameterized function was computed representing the differences in glacier surface elevation with respect to the glaciers altitude within the 19792011 period. Steiner, D., Walter, A. This results in a higher complexity of the Lasso compared to a temperature-index model. Glacier ice thickness observations are available for four different glaciers in the regions, which were compared to the estimates used in this model. Nat. In the meantime, to ensure continued support, we are displaying the site without styles 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. Analyses were made of the annual photographs . However, many glacierized regions in the world present different topographical setups, with flatter glaciers, commonly referred to as ice caps, covering the underlying terrain39. Grenoble Alpes, CNRS, IRD, G-INP, Institut des Gosciences de lEnvironnement, Grenoble, France, INRAE, UR RiverLy, Lyon-Villeurbanne, France, Institute for Marine and Atmospheric research Utrecht, Utrecht University, Utrecht, Netherlands, Univ. Consequently, a simple MB model with a single DDF (e.g. 3b). Sci. Despite these differences, the average altitude difference of the glaciers between both models is never greater than 50m (Fig. This translates into more frequent extreme negative MB rates, and therefore greater differences due to nonlinearities for the vast majority of future climate scenarios (Fig. S5h, j, l). Our results suggest that, except for the lowest emissions climate scenarios and for large glaciers with long response times, MB models with linear relationships for PDDs and precipitation are suitable for mountain glaciers with a marked topographical feedback. Ecol. Common climatic signal from glaciers in the European Alps over the last 50 years: Common Climatic Signal in the Alps. 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 ). 31, n/an/a (2004). With this cross-validation we determined a deep learning MB model spatiotemporal (LSYGO) RMSE of 0.59m.w.e. April 17, 2019. 5). 36, L23501 (2009). The source code of the glacier model can be freely accessed in the following repository: https://github.com/JordiBolibar/ALPGM. 4). Atmospheres 121, 77107728 (2016). However, both the climate and glacier systems are known to react non-linearly, even to pre-processed forcings like PDDs13, implying that these models can only offer a linearized approximation of climate-glacier relationships. Simulations for projections in this study were made by generating an ensemble of 60 cross-validated models based on LSYGO. With this study, we provide new predictions of glacier evolution in a highly populated mountain region, while investigating the role of nonlinearities in the response of glaciers to multiple future climate forcings. This experiment enabled the exploration of the response to specific climate forcings of a wide range of glaciers of different topographical characteristics in a wide range of different climatic setups, determined by all meteorological conditions from the years 19672015 (Fig. The rest of the story appears to lie primarily in the unique dynamic response of the region's glaciers to climate change. A knowledge of the areas once occupied by mountain glaciers reveals at least part of the past behavior of these glaciers. Rackauckas, C. et al. Rainier, Washington. The main uncertainties in future glacier estimates stem from future climate projections and levels of greenhouse gas emissions (differences between RCPs, GCMs, and RCMs), whose relative importance progressively increases throughout the 21st century. Our synthetic experiment does not account for glacier surface area shrinking either, which might have an impact on the glacier-wide MB signal. Despite the existence of a wide variety of different approaches to simulate glacier dynamics, all glacier models in GlacierMIP rely on MB models with linear relationships between PDDs and melt, and precipitation and accumulation. 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. 4a). https://doi.org/10.1016/B978-0-12-821575-3.00009-8. Other articles where Nisqually Glacier is discussed: Mount Rainier: from the broad summit, including Nisqually Glacier, whose retreat and advance over the last 150 years has helped scientists determine patterns in the Earth's climate. The cumulative positive degree days (CPDD), snowfall and rainfall dl, are at the glaciers annually evolving centroids. provided glacier mass balance data and performed the glaciological analyses. This reanalysis is specifically designed to represent meteorological conditions over complex mountain terrain, being divided by mountain massif, aspect and elevation bands of 300m. Winter climate data are computed between October 1 and March 31, and summer data between April 1 and September 30. Get the most important science stories of the day, free in your inbox. The 29 RCP-GCM-RCM combinations available, hereafter named climate members, are representative of future climate trajectories with different concentration levels of greenhouse gases (TableS1). 3 (2015). Bolibar, J., Rabatel, A., Gouttevin, I. Nisqually Glacier is well known for its kinematic waves ( Meier, 1962 ), but its mass balance has never been measured due to the difficulty of the glacier terrain. For these 32 glaciers, a total of 1048 annual glacier-wide MB values are available, covering the 19672015 period with gaps. Overall, the evolving glaciers are expected to undergo rather stable climate conditions under RCP 4.5, but increasingly higher temperatures and rainfall under RCP 8.5 (Fig. . This allows us to assess the MB models responses at a regional scale to changes in individual predictors (Fig. Hugonnet, R. et al. 4). Both models agree around the average values seen during training (i.e. 22, 21462160 (2009). Loss of glaciers contributes to sea-level rise, creates environmental hazards and can alter aquatic habitats. 3). Farinotti, D. et al. These different behaviours and resulting biases can potentially induce important consequences in long-term glacier evolution projections. Summer climate is computed between April 1st and September 30th and winter climate between October 1st and March 31st. We performed a validation simulation for the 20032015 period by running our model through this period and comparing the simulated glacier surface area of each of the 32 glaciers with MB to observations from the 2015 glacier inventory16,52. Envelopes indicate based on results for all 660 glaciers in the French Alps for the 19672015 period. All authors provided inputs to the paper and helped to write it. During the last decade, various global glacier evolution models have been used to provide estimates on the future sea-level contribution from glaciers7,8. Tour. You are using a browser version with limited support for CSS. Glacier surface mass changes are commonly modelled by relying on empirical linear relationships between PDDs and snow, firn or ice melt8,9,10,29. The climatic forcing comes from high-resolution climate ensemble projections from 29 combinations of global climate models (GCMs) and regional climate models (RCMs) adjusted for mountain regions for three Representative Concentration Pathway (RCP) scenarios: 2.6, 4.5, and 8.525. When comparing our deep learning simulations with those from the Lasso, we found average cumulative MB differences of up to 17% by the end of the century (Fig. Nonetheless, these differences have been shown to be rather small, having a lower impact on results than climate forcings or the initial glacier ice thickness10. The authors declare no competing interests. Years in white in c-e indicate the disappearance of all glaciers in a given massif. Overall, this results in linear MB models overestimating both extreme positive (Fig. 21, 229246 (2021). In order to investigate the effects of MB nonlinearities on flatter glaciers, we conducted a synthetic experiment using the French Alps dataset. 4). Average cumulative MB projections of French Alpine glaciers with a nonlinear deep learning vs. a linear Lasso model for 29 climate scenarios; a with topographical feedback (allowing for glacier retreat) and e without topographical feedback (synthetic experiment with constant mean glacier altitude). In that study, a temperature-index model with a separate degree-day factor (DDF) for snow and ice is used, resulting in piecewise linear functions able to partially reproduce nonlinear MB dynamics. Peer reviewer reports are available. 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. Gardent, M., Rabatel, A., Dedieu, J.-P. & Deline, P. Multitemporal glacier inventory of the French Alps from the late 1960s to the late 2000s. Earth Syst. ADAMONT provides climate data at 300m altitudinal bands and different slope aspects, thus having a significantly higher spatial resolution than the 0.11 from EURO-CORDEX. 4a, b) and negative (Fig. a Projected mean glacier altitude evolution between 2015 and 2100. Vincent, C. et al. 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. Jordi Bolibar. 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. how climate change and glacier retreat are reshaping whole aquatic ecosystems, there is a need to develop an integrated understanding spanning multiple taxonomic groups and trophic levels in glacier-fed rivers (e.g., bacteria, protists, fungi, algae, diatoms, invertebrates, mammals, amphibians, and fish; Clitherow et al. However, the impact of different climate configurations, such as a more continental and drier climate or a more oceanic and humid climate, would certainly have an impact on the results, albeit a much less important one than the lack of topographical feedback explored here. Swiss Glacier Mass Balance (release 2019). (2019) https://doi.org/10.18750/MASSBALANCE.2019.R2019. Glaciers in the European Alps have been monitored for several decades, resulting in the longest observational series in the world23,24. 12, 168173 (2019). Limnol. Nature 577, 364369 (2020). The effect of glaciers shrinking to smaller extents is not captured by these synthetic experiments, but this effect is less important for flat glaciers that are dominated by thinning (Fig. By the end of the century, we predict a glacier volume loss between 75 and 88%. This will reduce the importance of shortwave radiation for future ablation rates, and it is expected to result in a reduction in values of degree-day factors (DDFs) and therefore a significant change in melt sensitivity to air temperature variations36. Massifs without glaciers by 2100 are marked with a cross, b Glacier ice volume distribution per massif, with its remaining fraction by 2100 (with respect to 2015), c Annual glacier-wide MB per massif, d Annual snowfall per massif, e Annual cumulative positive degree-days (CPDD) per massif. IPCC. The Karakoram and the Himalayan mountain range accommodate a large number of glaciers and are the major source of several perennial rivers downstream. As such, these values reflect both the climatic forcing and the changing glacier geometry. Sci. Consortium, R. G. I. Randolph Glacier Inventory 6.0 (2017) https://doi.org/10.7265/N5-RGI-60. Uncertainties of existing projections of future glacier evolution are particularly large for the second half of the 21st century due to a large uncertainty on future climatic conditions. This translates into a more linear response to air temperature changes compared to the ablation season (Fig. Front. (a) Topographical predictors were computed based on the glaciers annually updated digital elevation model (DEM). The two recent iterations of the Glacier Model Intercomparison Project (GlacierMIP7,8) have proved a remarkable effort to aggregate, compare and understand global glacier evolution estimates and their associated uncertainties. The Cryosphere 13, 13251347 (2019). The machine learning models used in this study are useful to highlight and quantify how nonlinearities in MB affect climate-glacier interactions, but are limited in terms of process understanding. 0.5) than lower values typical from ice34. Data 12, 19731983 (2020). Six, D. & Vincent, C. Sensitivity of mass balance and equilibrium-line altitude to climate change in the French Alps. Activity 13.3 Nisqually Glacier Response to Climate Change Course/Section Date: Name: Nisqually Glacier is a mountain glacier located on the south side of Mt. On Mount Rainier, elevation surveys of Nisqually Glacier are regularly made to determine changes in the elevation of the surface. Deep learning captures a nonlinear response of glaciers to air temperature and precipitation, improving the representation of extreme mass balance rates compared to linear statistical and temperature-index models. The Cryosphere 14, 565584 (2020). The advantage of this method is that by only changing the MB model, we can keep the rest of the model components (glacier dynamics and climate forcing) and parameters the same in order to have a controlled environment for our experiment. S6). This has the strongest impact under RCP 2.6, where positive MB rates are more frequent (Fig. a1) over the French Alps. These synthetic experiments suggest that, for equal climatic conditions, flatter glaciers and ice caps will experience substantially more negative MB rates than steeper mountain glaciers. The training was performed with an RMSprop optimizer, batch normalization46, and we used both dropout and Gaussian noise in order to regularize it. ice cap-like behaviour). 60, 867878 (2014). 3). We ran glacier evolution projections for both the deep learning and Lasso MB models, but we kept the glacier geometry constant, thus preserving the glacier centroid where the climate data is computed constant through time. By performing glacier projections both with mountain glaciers in the French Alps and a synthetic experiment reproducing ice cap-like behaviour, we argue that the limitations identified here for linear models will also have implications for many other glacierized regions in the world. Carlson, B. Rabatel, A., Sanchez, O., Vincent, C. & Six, D. Estimation of glacier thickness from surface mass balance and ice flow velocities: a case study on Argentire Glacier, France. Such ice caps cannot retreat to higher elevations in a warming climate, which inhibits this positive impact on MB40 (Fig. 1gi)26 and glaciers shrinking to higher elevations where precipitation rates are higher as a result of orographic precipitation enhancement27. S7). Annual glacier-wide mass balance (MB) is estimated to remain stable at around 1.2m.w.e. Our projections show a strong glacier mass loss for all 29 climate members, with average ice volume losses by the end of the century of 75%, 80%, and 88% compared to 2015 under RCP 2.6 (9%, n=3), RCP 4.5 (17% +11%, n=13) and RCP 8.5 (15% +11%, n=13), respectively (Fig. The dataset of initial glacier ice thickness, available for the year 2003, determines the starting point of our simulations.
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