nisqually glacier response to climate change

In order to investigate the implications of these results for flat glaciers, we performed additional synthetic experiments in order to reproduce this lack of topographical feedback (Fig. Nature 577, 364369 (2020). ISSN 2041-1723 (online). 4). Robinson, C. T., Thompson, C. & Freestone, M. Ecosystem development of streams lengthened by rapid glacial recession. S10). 4e) MB rates. 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. "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. An analysis of the climate signal at the glaciers mean altitude throughout the century reveals that air temperature, particularly in summer, is expected to be the main driver of glacier mass change in the region (Fig. A NASA-led, international study finds Asia's high mountain glaciers are flowing more slowly in response to widespread ice loss, affecting freshwater availability downstream in India, Pakistan and China. Changes in DDFs with respect to air temperature also strongly depend on albedo, with ice presenting a substantially more nonlinear response than snow. A.R. 799904) and from the Fonds de la Recherche Scientifique FNRS (postdoctoral grant charg de recherches). Lett. Despite marked differences among regions, the generalized retreat of glaciers is expected to have major environmental and social impacts2,3. All values correspond to ensemble means under RCP 4.5. A similar behaviour is observed when comparing temperature-index models to more complex models (e.g. All authors provided inputs to the paper and helped to write it. Rackauckas, C. et al. 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. 4e). These conclusions drawn from these synthetic experiments could have large implications given the important sea-level contribution from ice cap-like ice bodies8. When working with spatiotemporal data, it is imperative to respect spatial and temporal data structures during cross-validation in order to correctly assess an accurate model performance48. 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. Dyn. Conversely, the linear MB model appears to be over-sensitive to extreme positive and negative snowfall anomalies. Remote Sens. Front. MB rates only begin to approach equilibrium towards the end of the century under RCP 2.6, for which glaciers could potentially stabilize with the climate in the first decades of the 22nd century depending on their response time (Fig. The smallest best performing architecture was used, in order to find a good balance between predictive power, speed, and extrapolation outside the training data. 1). Annual glacier-wide mass balance (MB) is estimated to remain stable at around 1.2m.w.e. Since 2005, study finds that surface melt off glaciers in the North has risen by 900%. Earth Syst. Vis. 49, 26652683 (2017). We previously demonstrated that this period is long enough to represent the secular trend of glacier dynamics in the region31. Paul, F. et al. P. Kennard, J. Both MB models were trained with exactly the same data, and all other glacier model parameters were unchanged in order to allow isolating the effects of the nonlinearities in the MB. Studies have warned about the use of temperature-index models for snow and ice projections under climate change for decades34,35,36. Huss, M. et al. In the past, shortwave radiation represented a more important fraction in the glacier surface energy budget than the energy fluxes directly related to air temperature (e.g. J. Hydrol. Res. Conf. Secure .gov websites use HTTPS A lock ( ) or https:// means you've safely connected to the .gov website. As previously mentioned, here these differences are computed at regional level for a wide variety of glaciers. 3c). The model output data generated in this study have been deposited in netCDF and CSV format in a Zenodo repository under accession code Creative Commons Attribution 4.0 International. J. Appl. Carlson, B. Ice melt sensitivity to PDDs strongly decreases with increasing summer temperatures, whereas snow melt sensitivity changes at a smaller rate34. GlacierMIP A model intercomparison of global-scale glacier mass-balance models and projections. 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. 2) and RCP 8.5 by the end of the century. The application of a non-linear back-propagation neural network to study the mass balance of Grosse Aletschgletscher, Switzerland. J.B. developed the main glacier model, performed the simulations, analysed the results, and wrote the paper. 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. 51, 313323 (2005). Maussion, F. et al. Rainier, Washington. C.G. Geophys. The mountain has three major peaks: Liberty Cap, Point Success, and Columbia Crest (the latter is the summit, located on the rim of the caldera). Annu. Loss of glaciers contributes to sea-level rise, creates environmental hazards and can alter aquatic habitats. In order to overcome these differences, some adaptations were performed to the GloGEMflow output, accompanied with some hypotheses to ensure a realistic comparison. Glaciers are large-scale, highly sensitive climate instruments which, ideally, should be picked up and weighed once a year. 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. All these glacier models, independently from their approach, need to resolve the two main processes that determine glacier evolution: (1) glacier mass balance, as the difference between the mass gained via accumulation (e.g. 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. In recent years, shrinking glaciers have contributed to about 30% of global sea level rise 1. Glob. 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. Another source of discrepancy between both models comes from the different MB data used to calibrate or train the MB models. a1) over the French Alps. J.B. was supported by a NWO VIDI grant 016.Vidi.171.063. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (2018). 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. By Carol Rasmussen,NASA's Earth Science News Team. Our results serve as a strong reminder that the outcomes of existing large-scale glacier simulations should be interpreted with care, and that newly available techniques (such as the nonlinear deep learning approach presented here) and observations (e.g. Across the globe, glaciers are decreasing in volume and number in response to climate change. The projections without glacier geometry adjustment explore the behaviour of glaciers which cannot retreat to higher elevations (i.e. Our results point out that this lack of topographical feedback leads to an increased frequency of extreme negative MB rates and to more pronounced differences between the nonlinear and linear MB models (Figs. Temperature-index models are known to be over-sensitive to temperature changes, mainly due to important differences in the processes contributing to future warming. MathSciNet However, the use of ANNs remains largely unexplored in glaciology for regression problems, with only a few studies using shallow ANNs for predicting the ice thickness14 or mass balance13 of a single glacier. This parametrization reproduces in an empirical manner the changes in glacier geometry due to the combined effects of ice dynamics and MB. Our analysis suggests that due to this positive impact on the MB signal, only relevant differences are observed between nonlinear and linear MB models for the lowest emission climate scenarios (Fig. 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. Planet. Park, and S. Beason. Google Scholar. CPDD, winter snowfall or summer snowfall) was modified for all glaciers and years. 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. 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 ). The dataset of initial glacier ice thickness, available for the year 2003, determines the starting point of our simulations. "The Patagonia Icefields are dominated by so-called 'calving' glaciers," Rignot said. https://zenodo.org/record/5549758. In the United States, glaciers can be found in the Rocky Mountains, the Sierra Nevada, the Cascades, and throughout Alaska. 2a and S3). 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. I.G. Climate Change 2013: The Physical Science Basis. Cauvy-Frauni, S. & Dangles, O. Glaciers in the European Alps have been monitored for several decades, resulting in the longest observational series in the world23,24. 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. Nisqually Glacier is the lengthiest of any made in North America. Some of these models use a single DDF, while others have separate DDFs for snow and ice, producing a piecewise function composed of two linear sub-functions that can partially account for nonlinear MB dynamics depending on the snowpack. IPCC. In order to avoid overfitting, MB models were thoroughly cross-validated using all data for the 19672015 period in order to ensure a correct out-of-sample performance. These bulges, called kinematic waves, form when higher than normal snowfall builds up in the accumulation area of the glacier (c). "Their numbers have gone from regularly exceeding 50,000 adult salmon in the Nisqually to about 5,000 last year." The Nisqually River near its glacial origins. Huss, M. & Hock, R. A new model for global glacier change and sea-level rise. Geosci. 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. 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. 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. 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. a1 and a r2 of 0.69, explaining 69% of the total MB variance. 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. This approach is known as a cross-validation ensemble49. A small ablation increase may cause . 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. 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. Roe, G. H. Orographic precipitation. A physically-based method for mapping glacial debris-cover thickness from ASTER satellite imagery: development and testing at Miage Glacier, Italian Alps Discovery - the University of Dundee Research Portal The images or other third party material in this article are included in the articles Creative Commons license, unless indicated otherwise in a credit line to the material. J. R. Stat. Our synthetic experiment does not account for glacier surface area shrinking either, which might have an impact on the glacier-wide MB signal. Partitioning the uncertainty of ensemble projections of global glacier mass change. 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. On Mount Rainier, elevation surveys of Nisqually Glacier are regularly made to determine changes in the elevation of the surface. Preliminary results suggest winter accumulation in 2018 was slightly above the 2003-2017 average for the Emmons & Nisqually. Toward mountains without permanent snow and ice: mountains without permanent snow and ice. 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). Both models agree around the average values seen during training (i.e. 12, 1959 (2020). 41, 153160 (1995). S4). Glacier response to climate change Jim Salinger, Trevor Chinn, Andrew Willsman, and how fluctuations in New Zealand glaciers reflect regional climate change. By the end of the century, we predict a glacier volume loss between 75 and 88%. A comprehensive bibliography of scientific publications relating to the glacier is included. Google Scholar. A dataset of 32 glaciers with direct annual glacier-wide MB observations and remote sensing estimates was used to train the models. 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. Atmospheres 121, 77107728 (2016). A recent study he did found that 80 percent of the glaciers in Alberta and British Columbia could melt in the next 50 years. Using this function, the glacier-specific ice thickness and the DEM are updated every year, adjusting the 3D geometry of each glacier. From this behavior, inferences of past climate can be drawn. Evol. 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. Nat Commun 13, 409 (2022). 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). Article 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. We also use this method to extract glacier borderlines from satellite images across the western Lenglongling mountains. Since the neural network used here virtually behaves like a black box, an alternative way is needed to understand the models behaviour. This implies that current global glacier mass loss projections are too low for the lowest emissions climate scenarios and too high for the highest emissions ones, which has direct consequences for related sea-level rise and water resources projections. Vertical axes are different for the two analyses. GloGEMflow has been previously applied in a study over the whole European Alps, and its temperature-index model was mainly calibrated with MB data from the Swiss Alps. This removes the topographical feedback typical from mountain glaciers, and reproduces the more extreme climate conditions that ice caps are likely to endure through the 21st century40. The lower fraction of variance explained by linear models is present under all climate scenarios. ALPGM uses a feed-forward fully connected multilayer perceptron, with an architecture (40-20-10-5-1) with Leaky-ReLu44 activation functions and a single linear function at the output. 3). b, c, d and f, g, h annual glacier-wide MB probability distribution functions for all n scenarios in each RCP. The rest of the story appears to lie primarily in the unique dynamic response of the region's glaciers to climate change. ice cap-like behaviour). 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. Bolibar, J. ALPGM (ALpine Parameterized Glacier Model) v1.1. On the one hand, MB nonlinearities for mountain glaciers appear to be only relevant for climate scenarios with a reduction in greenhouse gases emissions (Fig. Google Scholar. This type of model uses a calibrated linear relationship between positive degree-days (PDDs) and the melt of ice or snow11. 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. With a secondary role, glacier model uncertainty decreases over time, but it represents the greatest source of uncertainty until the middle of the century8. Advances occurred from 1963-68 and from 1974-79. Univ. This synthetic experiment is an approximation of what might occur in other glacierized regions with ice caps. By 2100, under RCP 4.5, these two high-altitude massifs are predicted to retain on average 26% and 13% of their 2015 volume, respectively, with most of the ice concentrated in a few larger glaciers (>1km2, Fig. Alternatively, the Lasso MB model displayed an RMSE of 0.85m.w.e. Hock, R. et al. This is particularly important for the ablation season and for ice DDFs, which need to accommodate the progressively decreasing role that shortwave radiation will play in the future glacier surface energy budget under warmer conditions. 185, 235246 (2014). The nonlinearities present in the simulated annual glacier-wide MB values were assessed by running two different glacier simulations with two different MB models. Common climatic signal from glaciers in the European Alps over the last 50 years: Common Climatic Signal in the Alps. Tests were performed distributing the CPDD anomalies equally among all months of the year with very similar results. 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 training was performed with an RMSprop optimizer, batch normalization46, and we used both dropout and Gaussian noise in order to regularize it. Article He, K., Zhang, X., Ren, S. & Sun, J. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification. 4 vs.S5). 60, 11401154 (2014). Nonetheless, a better understanding of the underlying processes guiding these nonlinear behaviours at large geographical scales is needed. Thin lines represent each of the 29 individual member runs, while the thick lines represent the average for a given RCP. 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. 1d, g). contributed to the climate analyses. Both machine learning MB models were trained with exactly the same data coming from the 1048 annual glacier-wide MB values, and both were cross-validated using LSYGO. 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. For that, a dataset of input predictors covering all the glaciers in the French Alps for the 19672015 period was generated from a past MB reconstruction study15. 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. Farinotti, D. et al. Monitoring the Seasonal hydrology of alpine wetlands in response to snow cover dynamics and summer climate: a novel approach with sentinel-2. Conversely, during the accumulation season, glaciers are mostly covered by snow, with a much higher albedo and a reduced role of shortwave radiation in the MB that will persist even under climate change. Multiple copies of this dataset were created, and for each individual copy a single predictor (i.e. Tom R. Andersson, J. Scott Hosking, Emily Shuckburgh, Shfaqat A. Khan, Anders A. Bjrk, Toni Schenk, Romain Hugonnet, Robert McNabb, Andreas Kb, Atanu Bhattacharya, Tobias Bolch, Tandong Yao, Christian Sommer, Philipp Malz, Matthias H. Braun, Romain Millan, Jrmie Mouginot, Mathieu Morlighem, Matthias H. Braun, Philipp Malz, Thorsten C. Seehaus, Nature Communications In the meantime, to ensure continued support, we are displaying the site without styles Nature Communications (Nat Commun) Seasonal Arctic sea ice forecasting with probabilistic deep learning, Global glacier mass changes and their contributions to sea-level rise from 1961 to 2016, Two decades of glacier mass loss along the Andes, Centennial response of Greenlands three largest outlet glaciers, Accelerated global glacier mass loss in the early twenty-first century, High Mountain Asian glacier response to climate revealed by multi-temporal satellite observations since the 1960s, Rapid glacier retreat and downwasting throughout the European Alps in the early 21st century, Ice velocity and thickness of the worlds glaciers, Constraining glacier elevation and mass changes in South America, https://meetingorganizer.copernicus.org/EGU2020/EGU2020-20908.html, https://doi.org/10.5194/egusphere-egu2020-20908, https://doi.org/10.18750/MASSBALANCE.2019.R2019, https://doi.org/10.1016/B978-0-12-821575-3.00009-8, https://doi.org/10.1038/s41561-021-00885-z, http://creativecommons.org/licenses/by/4.0/, Unabated wastage of the Muz Taw Glacier in the Sawir Mountains during 19592021. A glacier is a large mass of snow and ice that has accumulated over many years and is present year-round. Glacier-wide MB is simulated annually for individual glaciers using deep learning (i.e. 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. Despite their limitations, temperature-index models, owing to their simplicity and parsimonious data requirements, have been widely used for large-scale glacier projections7,8. The position of the front of the wave will be defined as the transverse line across the glacier where the flow of . This ensures that the model is capable of reproducing MB rates for unseen glaciers and years. Jordi Bolibar. 1 and S1). Slider with three articles shown per slide. Years in white in c-e indicate the disappearance of all glaciers in a given massif. The temperature-index model includes up to three different DDFs, for ice, firn and snow, resulting in three parameters. 5). Correspondence to Climate predictors consist of: the annual CPDD, winter snowfall, summer snowfall, monthly mean temperature and monthly snowfall. Hugonnet, R. et al. 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. Predicting future glacier evolution is of paramount importance in order to correctly anticipate and mitigate the resulting environmental and social impacts. The processing chain for extracting glacier outlines from images is composed of four steps: (1) calculation of band ratio, (2) selection of threshold value, (3) creation of binary image and (4) manual digitization. Rveillet, M. et al. Zekollari, H., Huss, M. & Farinotti, D. Modelling the future evolution of glaciers in the European Alps under the EURO-CORDEX RCM ensemble. The Nisqually Glacier is one of the larger glaciers on the southwestern face of Mount Rainier in the U.S. state of Washington.The glacier is one of the most easily viewed on the mountain, and is accessible from the Paradise visitor facilities in Mount Rainier National Park.The glacier has had periods of advance and retreat since 1850 when it was much more extensive.
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