Years in white in c-e indicate the disappearance of all glaciers in a given massif. Change 120, 2437 (2014). As Arctic warms, Canada's glaciers playing major role in sea - CBC 5). 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. Therefore, their sensitivities to the projected 21st century increase in PDDs are linear. https://zenodo.org/record/5549758. ArXiv200104385 Cs Math Q-Bio Stat (2020). 3 (2015). (Springer, New York, 2009). 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. Rackauckas, C. et al. Previous studies on 21st century large-scale glacier evolution projections have covered the French Alps7,8. These results are in agreement with the main known drivers of glacier mass change in the French Alps28. 4e). 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. 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. Deep artificial neural networks (ANNs) are nonlinear models that offer an alternative approach to these classic methods. These are among the cascading effects linked to glacier loss which impact ecosystems and . 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. Immerzeel, W. W. et al. PDF Climate Change Glacier response to climate change 4e). Planet. An enhanced temperature-index glacier melt model including the shortwave radiation balance: development and testing for Haut Glacier dArolla, Switzerland. For these 32 glaciers, a total of 1048 annual glacier-wide MB values are available, covering the 19672015 period with gaps. A comparison between the two MB models shows that a nonlinear response to climate forcings is captured by the deep learning MB model, allowing a better representation of glacier mass changes, including significantly reduced biases for extreme values (see Methods). 4a). Glaciers - Mount Rainier National Park (U.S. National Park Service) Therefore, an alternative nonlinear parameterization for the reduction in MB sensitivity under increasing air temperatures would be useful. Farinotti, D. et al. In recent years, shrinking glaciers have contributed to about 30% of global sea level rise 1. By submitting a comment you agree to abide by our Terms and Community Guidelines. Nonlinear sensitivity of glacier mass balance to future climate change unveiled by deep learning. Analysis of a 24-Year photographic record of Nisqually glacier, Mount The Karakoram and the Himalayan mountain range accommodate a large number of glaciers and are the major source of several perennial rivers downstream. The French Alps, located in the westernmost part of the European Alps, experience some of the strongest glacier retreat in the world15,16,17. 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. 65, 453467 (2019). Universal Differential Equations for Scientific Machine Learning. Reanalysis of 47 Years of Climate in the French Alps (19582005): Climatology and Trends for Snow Cover. 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. 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. In the meantime, to ensure continued support, we are displaying the site without styles 14, 815829 (2010). By Carol Rasmussen,NASA's Earth Science News Team. This results in a higher complexity of the Lasso compared to a temperature-index model. Internet Explorer). J. Clim. Hock, R. Temperature index melt modelling in mountain areas. Ice thickness accuracy varied significantly, with an overall correct representation of the ice distribution but with local biases reaching up to 100%. The rest of the story appears to lie primarily in the unique dynamic response of the region's glaciers to climate change. 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. A glacier flows naturally like a river, only much more slowly. Slider with three articles shown per slide. & Galiez, C. A deep learning reconstruction of mass balance series for all glaciers in the French Alps: 19672015. 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. b, c, d and f, g, h annual glacier-wide MB probability distribution functions for all n scenarios in each RCP. Atmospheres 121, 77107728 (2016). 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. ICCV (2015) https://doi.org/10.1109/iccv.2015.123. contributed to the climate analyses. Annual glacier-wide mass balance (MB) is estimated to remain stable at around 1.2m.w.e. "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. Google Scholar. a deep artificial neural network) or the Lasso (regularized multilinear regression)30. 2015 IEEE Int. Glaciers are experiencing important changes throughout the world as a consequence of anthropogenic climate change1. Photographs taken by Simo Rsnen (Bossons glacier, European Alps, CC BY-SA 3.0) and Doug Hardy (Quelccaya ice cap, Andes, CC BY-SA 4.0). This synthetic setup allowed us to reproduce the climatic conditions to be undergone by most ice caps, with their mean surface altitude hardly evolving through time. 4a, b) and negative (Fig. 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. 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 ). We compare model runs using a nonlinear deep learning MB model (the reference approach in our study) against a simplified linear machine learning MB model based on the Lasso30, i.e. 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). 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. Res. 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. a1) over the French Alps. In order to overcome these differences, some adaptations were performed to the GloGEMflow output, accompanied with some hypotheses to ensure a realistic comparison. The increase in glacier altitude also causes the solid to liquid precipitation ratio to remain relatively constant. Overall, this results in linear MB models overestimating both extreme positive (Fig. This translates into a more linear response to air temperature changes compared to the ablation season (Fig. Steiner, D., Walter, A. 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. a Projected mean glacier altitude evolution between 2015 and 2100. Gaining a better understanding of how warming ocean water affects these glaciers will help improve predictions of their fate. 31, n/an/a (2004). 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. Climate predictors consist of: the annual CPDD, winter snowfall, summer snowfall, monthly mean temperature and monthly snowfall. energy balance), with differences increasing when the conditions considerably differ from the calibration period33. Comput. 4a). Differences in projected glacier changes become more pronounced from the second half of the century, when about half of the initial 2015 ice volume has already been lost independent of the considered scenario. 33, 645671 (2005). Such ice caps cannot retreat to higher elevations in a warming climate, which inhibits this positive impact on MB40 (Fig. Nonlinear deep learning response and linear Lasso response to a Cumulative positive degree days (CPDD) anomalies, b winter snowfall, and c summer snowfall.
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