nisqually glacier response to climate change

Article Hastie, T., Tibshirani, R. & Friedman, J. Hugonnet, R. et al. Geophys. 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. 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. J. Glaciol. Earth Syst. Nonlinear sensitivity of glacier mass balance to future climate change unveiled by deep learning, https://doi.org/10.1038/s41467-022-28033-0. S5 and S6). Farinotti, D. et al. 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. Our results indicate that these uncertainties might be even larger than we previously thought, as linear MB models are introducing additional biases under the extreme climatic conditions of the late 21st and 22nd centuries. Verfaillie, D., Dqu, M., Morin, S. & Lafaysse, M. The method ADAMONT v1.0 for statistical adjustment of climate projections applicable to energy balance land surface models. Thin lines represent each of the 29 individual member runs, while the thick lines represent the average for a given RCP. Thank you for visiting nature.com. As for the MB modelling approach, a detailed explanation on this method can be found in a previous dedicated paper on the methods31. Fr Hydrobiol. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate. S5h, j, l). Several aquatic and terrestrial ecosystems depend on these water resources as well, which ensure a base runoff during the warmest or driest months of the year6. A glacier is a large mass of snow and ice that has accumulated over many years and is present year-round. J.B. was supported by a NWO VIDI grant 016.Vidi.171.063. The application of a non-linear back-propagation neural network to study the mass balance of Grosse Aletschgletscher, Switzerland. GloGEMflow relies on EURO-CORDEX ensembles26, whereas ALPGM uses ADAMONT25, an adjusted version of EURO-CORDEX specifically designed for mountain regions. These results are in agreement with the main known drivers of glacier mass change in the French Alps28. Multiple copies of this dataset were created, and for each individual copy a single predictor (i.e. "The Patagonia Icefields are dominated by so-called 'calving' glaciers," Rignot said. These measurements of surface elevation were begun by personnel of the Tacoma Many studies have investigated the effects of climate change on glacier runoff using observations or modelling, with a recent focus on High Mountain Asia 14,16,17 and the Andes 18,19,20.The degree . Annual glacier-wide mass balance (MB) is estimated to remain stable at around 1.2m.w.e. Canada's glaciers and ice caps are now a major contributor to sea level change, a new UCI study shows. Google Scholar. Glacier surface mass changes are commonly modelled by relying on empirical linear relationships between PDDs and snow, firn or ice melt8,9,10,29. This creates a total of 34 input predictors for each year (7 topographical, 3 seasonal climate, and 24 monthly climate predictors). Vis. 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. This oversensitivity directly results from the fact that temperature-index models rely on linear relationships between PDDs and melt and that these models are calibrated with past MB and climate data. Nonlinear sensitivity of glacier mass balance to future climate change unveiled by deep learning. 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. CAS 2015 IEEE Int. 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. Due to the statistical nature of the Lasso model, the response to snowfall anomalies is also highly influenced by variations in PDDs (Fig. Secure .gov websites use HTTPS A lock ( ) or https:// means you've safely connected to the .gov website. 1a). contributed to the extraction of nonlinear mass balance responses and to the statistical analysis. 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. 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. 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. This type of model uses a calibrated linear relationship between positive degree-days (PDDs) and the melt of ice or snow11. 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. Geophys. This ensures that the model is capable of reproducing MB rates for unseen glaciers and years. Lett. 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 (2015). 10, 42574283 (2017). Previous studies on 21st century large-scale glacier evolution projections have covered the French Alps7,8. This modelling approach was described in detail in a previous publication dedicated to the methods, where the ALpine Parameterized Glacier Model (ALPGM43) was presented31. In this study, we investigate the future evolution of glaciers in the French Alps and their nonlinear response to multiple climate scenarios. On the other hand, for flatter glaciers large differences between deep learning and Lasso are obtained for almost all climate scenarios (Fig. Each one of these cross-validations served to evaluate the model performance for the spatial, temporal and both dimensions, respectively. & Funk, M. A comparison of empirical and physically based glacier surface melt models for long-term simulations of glacier response. Paul, F., Kb, A., Maisch, M., Kellenberger, T. & Haeberli, W. Rapid disintegration of Alpine glaciers observed with satellite data: disintegration of alpine glaciers. 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. Toward mountains without permanent snow and ice: mountains without permanent snow and ice. 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. The French Alps, located in the westernmost part of the European Alps, experience some of the strongest glacier retreat in the world15,16,17. This behaviour is expected for mountain glaciers, as they are capable of retreating to higher altitudes, thus producing a positive impact on their glacier-wide MB (Fig. Jordi Bolibar. Predicting future glacier evolution is of paramount importance in order to correctly anticipate and mitigate the resulting environmental and social impacts. Nonetheless, since they are both linear, their calibrated parameters establishing the sensitivity of melt and glacier-wide MB to temperature variations remain constant over time. The ice thickness data for two of the largest glaciers in the French Alps were modified in order to improve data quality. Therefore, we were capable of isolating the different behaviours of the nonlinear deep learning model and a linear machine learning model based on the Lasso30. Slider with three articles shown per slide. ICCV (2015) https://doi.org/10.1109/iccv.2015.123. The Nisqually Glacier, Mount Rainier, Washington, 1857-1979: A summary Paul, F. et al. Interestingly, this matches the nonlinear, less sensitive response to summer snowfall in the ablation season of our deep learning model (Fig. For intermediate and pessimistic climate scenarios, no significant differences were found (Fig. Analyses were made of the annual photographs . The authors declare no competing interests. April 17, 2019. However, to further investigate these findings, experiments designed more towards ice caps, and including crucial mechanisms such as ice-ocean interactions and thermodynamics, should be used for this purpose. 1). 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. 4). 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. By monitoring the change in size of glaciers around the world, scientists can learn about global climate change. 15 - Response of glaciers to climate change - Cambridge Core 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). Glaciers - Mount Rainier National Park (U.S. National Park Service) Steiner, D., Walter, A. CoRR abs/1505.00853 (2015). This is not the case for the nonlinear deep learning MB model, which captures the nonlinear response of melt and MB to increasing air temperatures, thus reducing the MB sensitivity to extreme positive and negative air temperature and summer snowfall anomalies (Fig. In our model, we specifically computed this parameterized function for each individual glacier larger than 0.5km2, representing 80% of the total glacierized area in 2015, using two DEMs covering the whole French Alps: a photogrammetric one in 1979 and a SPOT-5 one in 2011. These different behaviours and resulting biases can potentially induce important consequences in long-term glacier evolution projections. With a secondary role, glacier model uncertainty decreases over time, but it represents the greatest source of uncertainty until the middle of the century8. Nonetheless, a better understanding of the underlying processes guiding these nonlinear behaviours at large geographical scales is needed. melt and sublimation of ice, firn and snow; or calving)9; and (2) ice flow dynamics, characterized by the downward movement of ice due to the effects of gravity in the form of deformation of ice and basal sliding. Positive degree-day factors for ablation on the Greenland ice sheet studied by energy-balance modelling. 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. 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. Conversely, the linear MB model appears to be over-sensitive to extreme positive and negative snowfall anomalies. 3). J. Glaciol. 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. Article Bartk, B. et al. 1960). 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. ice cap-like behaviour). 4 ). Alternatively, the Lasso MB model displayed an RMSE of 0.85m.w.e. CPDD, winter snowfall or summer snowfall) was modified for all glaciers and years. Nisqually Glacier - glaciers.pdx.edu Huss, M. & Hock, R. A new model for global glacier change and sea-level rise. Glob. Earth Planet. Nat Commun 13, 409 (2022). Cross-validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure. A knowledge of the areas once occupied by mountain glaciers reveals at least part of the past behavior of these glaciers. deep artificial neural networks) glacier evolution projections by modelling the regional evolution of French alpine glaciers through the 21st century. 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. 3c), which is directly linked to summer air temperatures and has a strong influence on surface albedo. Vertical axes are different for the two analyses. 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. The increase in glacier altitude also causes the solid to liquid precipitation ratio to remain relatively constant. This behaviour is not observed with the nonlinear model, hinting at a positive bias of linear MB models under RCP 2.6. Therefore, their sensitivities to the projected 21st century increase in PDDs are linear. 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. In order to simulate annual glacier-wide MB values, (a) topographical and (b) climate data for those glaciers and years were compiled for each of the 1048 glacier-year values. Glacier response to climate change Jim Salinger, Trevor Chinn, Andrew Willsman, and how fluctuations in New Zealand glaciers reflect regional climate change. GlaciersUnderstanding Climate Drivers | U.S. Geological Survey Swiss Glacier Mass Balance (release 2019). Ice thickness data for Argentire glacier (12.27km2 in 2015) was taken from a combination of field observations (seismic, ground-penetrating radar or hot-water drilling53) and simulations32. 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. B Methodol. longwave radiation budget, turbulent fluxes), in comparison with a future warmer climate. Geosci. Earth Sci. For such cases, we assumed that ice dynamics no longer play an important role, and the mass changes were applied equally throughout the glacier. 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. 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. Climate variations change a glacier's mass balance by affecting ablation and accumulation amounts. In order to improve the comparability between both models, a MB bias correction was applied to GloGEMflows simulated MB, based on the average annual MB difference between both models for the 20032015 period (0.4m.w.e. 31, n/an/a (2004). 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 signal: ice caps and large flatter glaciers are expected to be more influenced by these nonlinear sensitivities than steep mountain glaciers in a warming climate. Park, and S. Beason. J. Glaciol. 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). MATH Google Scholar. Landscape response to climate change and its role in infrastructure Advances occurred from 1963-68 and from 1974-79. At the Edge: Monitoring Glaciers to Watch Global Warming - NASA Six, D. & Vincent, C. Sensitivity of mass balance and equilibrium-line altitude to climate change in the French Alps. This behaviour has already been observed for the European Alps, with a reduction in DDFs for snow during the ablation season of 7% per decade34. 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. ArXiv200104385 Cs Math Q-Bio Stat (2020). Our results also highlight the important role played by glacier geometry adjustment under changing climatic conditions, which is typical of mountain glaciers38. A global synthesis of biodiversity responses to glacier retreat. 36, L23501 (2009). 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 ). The lower fraction of variance explained by linear models is present under all climate scenarios. This behaviour is particularly clear for summer snowfall, for which the differences are the largest (Fig. 2) and RCP 8.5 by the end of the century. Analysis of a 24-Year photographic record of Nisqually glacier, Mount Map-based methods for estimating glacier equilibrium-line altitudes Here, we compare our results with those from a recent study that focused on the European Alps10. 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. The Cryosphere 14, 565584 (2020). "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. As climate changes, so do glaciers | PNAS Our analyses suggest that these limitations can also be translated to temperature-index MB models, as they share linear relationships between PDDs and melt, as well as precipitation and accumulation. Overall, this results in linear MB models overestimating both extreme positive (Fig. 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. Glacier shrinkage in the Alps continues unabated as revealed by a new glacier inventory from Sentinel-2. 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. Water resources provided by glaciers sustain around 10% of the worlds population living near mountains and the contiguous plains4, depending on them for agriculture, hydropower generation5, industry or domestic use. S6). Peer reviewer reports are available. Anyone you share the following link with will be able to read this content: Sorry, a shareable link is not currently available for this article. The performance of this parametrization was validated in a previous study, indicating a correct agreement with observations31. An accurate prediction of future glacier evolution will be crucial to successfully adapt socioeconomic models and preserve biodiversity. A well-established parametrization based on empirical functions50 was used in order to redistribute the annually simulated glacier-wide mass changes over each glacier. 'When the Glaciers Disappear, Those Species Will Go Extinct' 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. S1a). Envelopes indicate based on results for all 660 glaciers in the French Alps for the 19672015 period. A small ablation increase may cause . Warming Seas Are Accelerating Greenland's Glacier Retreat Alpine glaciers, like this one near Mt. Zekollari, H., Huss, M. & Farinotti, D. Modelling the future evolution of glaciers in the European Alps under the EURO-CORDEX RCM ensemble. 51, 313323 (2005). The Cryosphere 13, 11251146 (2019). 3). 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). Hydrol. GlacierMIP A model intercomparison of global-scale glacier mass-balance models and projections. 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. On the one hand, this improves our confidence in long-term MB projections for steep glaciers made by most GlacierMIP models for intermediate and high emissions climate scenarios. A physically-based method for mapping glacial debris-cover thickness The nonlinearities present in the simulated annual glacier-wide MB values were assessed by running two different glacier simulations with two different MB models. Salim, E., Ravanel, L., Deline, P. & Gauchon, C. A review of melting ice adaptation strategies in the glacier tourism context. J. Glaciol. Res. Loss of glaciers contributes to sea-level rise, creates environmental hazards and can alter aquatic habitats. 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. 33, 645671 (2005). Additionally, glacier surface area was found to be a minor predictor in our MB models31. Change 120, 2437 (2014). Data 12, 19731983 (2020). Cauvy-Frauni, S. & Dangles, O. Our results confirm an over-sensitivity of temperature-index models, often used by large-scale studies, to future warming. The Elements of Statistical Learning. Use the Previous and Next buttons to navigate the slides or the slide controller buttons at the end to navigate through each slide. Meteorol. Marzeion, B. et al. (Zenodo, 2020). 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. Contrasting glacier responses to recent climate change in high-mountain J. Hosp. 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. Res. Deep learning applied to glacier evolution modelling. Ioffe, S. & Szegedy, C. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (2015). 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. I.G. Article Our synthetic experiment does not account for glacier surface area shrinking either, which might have an impact on the glacier-wide MB signal. ice caps) that are found in other glacierized regions such as the Arctic, where the largest volumes of glacier ice (other than the ice sheets) are stored32, cannot retreat to higher elevations. This implies that specific climatic differences between massifs can be better captured by ALPGM than GloGEMflow. J. Hydrol. Glaciers with the greatest degree of seasonality in their flow behavior, such as Nisqually and Shoestring glaciers, responded most rapidly. For these 32 glaciers, a total of 1048 annual glacier-wide MB values are available, covering the 19672015 period with gaps. Huss, M., Funk, M. & Ohmura, A. 4a, b) and negative (Fig. 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.

What Is An Option Contract When Buying A Car, Wichita Falls, Tx News Shooting, Marvin Ellison Family, Tupac Hologram Concert Tickets, Liberty Safe Washington Series, Articles N