0.5) than lower values typical from ice34. Alpine glaciers, like this one near Mt. Monitoring the Seasonal hydrology of alpine wetlands in response to snow cover dynamics and summer climate: a novel approach with sentinel-2. The performance of this parametrization was validated in a previous study, indicating a correct agreement with observations31. MATH Projected changes in surface solar radiation in CMIP5 global climate models and in EURO-CORDEX regional climate models for Europe. J. Appl. The record, which was started in 1931, shows the glacier's dramatic responses to about half a century of small but significant climatic variations. Consequently, a simple MB model with a single DDF (e.g. Researchers analyzed almost 2 million satellite images of the glaciers and found that 94 . 21, 229246 (2021). Scand. H.Z. Loss of glaciers contributes to sea-level rise, creates environmental hazards and can alter aquatic habitats. 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. 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. 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 temperature-index model includes up to three different DDFs, for ice, firn and snow, resulting in three parameters. 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. 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. 41, 153160 (1995). On the other hand, ice caps present a different response to future warming, with our results suggesting a negative MB bias by models using linear PDD and accumulation relationships. Gabbi, J., Carenzo, M., Pellicciotti, F., Bauder, A. & Galiez, C. A deep learning reconstruction of mass balance series for all glaciers in the French Alps: 19672015. 'When the Glaciers Disappear, Those Species Will Go Extinct' Geophys. Due to the statistical nature of the Lasso model, the response to snowfall anomalies is also highly influenced by variations in PDDs (Fig. 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. Sign up for the Nature Briefing newsletter what matters in science, free to your inbox daily. 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. 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. (Photograph by Klaus J. Bayr, Keene State College, 1990) One method of measuring glaciers is to send researchers onto the ice with . The smallest best performing architecture was used, in order to find a good balance between predictive power, speed, and extrapolation outside the training data. Models were trained using the SAFRAN reanalysis dataset47, including observations of mountain regions in France for the 19582015 period. The original ice thickness estimates of the methods used by both models are different10,32, and for ALPGM we performed some additional modifications to the two largest glaciers in the French Alps (see Glacier geometry evolution for details). Simulating these processes at a large geographical scale is challenging, with models requiring several parametrizations and simplifications to operate. This means that these flatter ice bodies, under a warming climate, will be subject to higher temperatures than their steeper counterparts. 5). J. Glaciol. 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. Rveillet, M. et al. 3). 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 behaviour is not observed with the nonlinear model, hinting at a positive bias of linear MB models under RCP 2.6. Res. A recent study he did found that 80 percent of the glaciers in Alberta and British Columbia could melt in the next 50 years. Braithwaite, R. J. Ecography 40, 913929 (2017). As Arctic warms, Canada's glaciers playing major role in sea - CBC Marzeion, B. et al. Change 120, 2437 (2014). Years in white in c-e indicate the disappearance of all glaciers in a given massif. Atmospheres 121, 77107728 (2016). Google Scholar. The increase in glacier altitude also causes the solid to liquid precipitation ratio to remain relatively constant. Data 12, 18051821 (2020). 3). A physically-based method for mapping glacial debris-cover thickness PubMedGoogle Scholar. This annual geometry adjustment accounts for the effects of glacier retreat on the climate signal received by glaciers. 14, 815829 (2010). Here, with our newly presented approach, we were able for the first time to quantify the effect that stationary parameters in temperature-index mass balance models have on transient glacier evolution. Earth Syst. 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. Fluctuations of the Nisqually Glacier, Mt. Rainier, Washington, since 44, 13761383 (2017). 3c). Nonlinear sensitivity of glacier mass balance to future climate change unveiled by deep learning, https://doi.org/10.1038/s41467-022-28033-0. 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. Nonetheless, since the main GCM-RCM climate signal is the same, the main large-scale long-term trends are quite similar. Provided by the Springer Nature SharedIt content-sharing initiative. These different behaviours and resulting biases can potentially induce important consequences in long-term glacier evolution projections. Earth Syst. By the end of the century, we predict a glacier volume loss between 75 and 88%. 4 ). J. Geophys. This is well in agreement with the known uncertainties of glacier evolution models, with glacier ice thickness being the second largest uncertainty after the future GCM-RCM-RCP climate members used to force the model29. During the last decade, various global glacier evolution models have been used to provide estimates on the future sea-level contribution from glaciers7,8. Durand, Y. et al. Glaciers are important for agriculture, hydropower, recreation, tourism, and biological communities. However, many glacierized regions in the world present different topographical setups, with flatter glaciers, commonly referred to as ice caps, covering the underlying terrain39. Glaciers and ice caps are experiencing strong mass losses worldwide, challenging water availability, hydropower generation, and ecosystems. 4), as the linear model tends to over-estimate positive MB rates both from air temperature and snowfall (Fig. Nature Geosciences, https://doi.org/10.1038/s41561-021-00885-z (2022). contributed to the climate analyses. Sci. "Seeing the rapid and devastating collapse of this incredible and critical salmon in the Nisqually River is heartbreaking," said Troutt. This means that these differences linked to MB nonlinearities observed in this experiment could be even greater for such ice caps. DDFs are known to vary much less with increasing temperatures for intermediate values of albedo (i.e. As such, these values reflect both the climatic forcing and the changing glacier geometry. S5cf), except for the largest glaciers (e.g. Climatol. Huss, M., Funk, M. & Ohmura, A. Model Dev. 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. 3b). The Open Global Glacier Model (OGGM) 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. 4a, b) and negative (Fig. The nonlinearities present in the simulated annual glacier-wide MB values were assessed by running two different glacier simulations with two different MB models. 2) and RCP 8.5 by the end of the century. ice cap-like behaviour). The Multitrophic Effects of Climate Change and Glacier Retreat - JSTOR Glob. Google Scholar. Correspondence to Nisqually Glacier | glacier, Washington, United States 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. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. These measurements of surface elevation were begun by personnel of the Tacoma 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. 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. longwave radiation budget, turbulent fluxes), in comparison with a future warmer climate. Sci. See how Mount Rainier glaciers have vanished over time, with this eye