scholarly journals Correction: Gharehchahi, S.; James, W.H.M.; Bhardwaj, A.; Jensen, J.L.R.; Sam, L.; Ballinger, T.J.; Butler, D.R. Glacier Ice Thickness Estimation and Future Lake Formation in Swiss Southwestern Alps—The Upper Rhône Catchment: A VOLTA Application. Remote Sens. 2020, 12, 3443

2020 ◽  
Vol 12 (22) ◽  
pp. 3709
Author(s):  
Saeideh Gharehchahi ◽  
William H. M. James ◽  
Anshuman Bhardwaj ◽  
Jennifer L. R. Jensen ◽  
Lydia Sam ◽  
...  
Keyword(s):  
Ice Thickness ◽  
Thickness Estimation ◽  
Lake Formation ◽  
Glacier Ice ◽  
Southwestern Alps

The authors wish to make the following corrections to this paper [...]

scholarly journals Glacier Ice Thickness Estimation and Future Lake Formation in Swiss Southwestern Alps—The Upper Rhône Catchment: A VOLTA Application

2020 ◽  
Vol 12 (20) ◽  
pp. 3443 ◽  
Author(s):  
Saeideh Gharehchahi ◽  
William H. M. James ◽  
Anshuman Bhardwaj ◽  
Jennifer L. R. Jensen ◽  
Lydia Sam ◽  
...  
Keyword(s):  
Swiss Alps ◽  
Population Increase ◽  
Glacial Lake ◽  
Ice Thickness ◽  
High Mountain ◽  
Bed Topography ◽  
Lake Formation ◽  
Morphological Criteria ◽  
The Future ◽  
Glacier Ice

Glacial lake formations are currently being observed in the majority of glacierized mountains in the world. Given the ongoing climate change and population increase, studying glacier ice thickness and bed topography is a necessity for understanding the erosive power of glacier activity in the past and lake formation in the future. This study uses the available information to predict potential sites for future lake formation in the Upper Rhône catchment located in the Southwestern Swiss Alps. The study integrates the latest available glacier outlines and high-quality digital elevation models (DEMs) into the Volume and Topography Automation (VOLTA) model to estimate ice thickness within the extent of the glaciers. Unlike the previous ice thickness models, VOLTA calculates ice thickness distribution based on automatically-derived centerlines, while optimizing the model by including the valley side drag parameter in the force equation. In this study, a total ice volume of 37.17 ± 12.26 km3 (1σ) was estimated for the Upper Rhône catchment. The comparison of VOLTA performance indicates a stronger relationship between measured and predicted bedrock, confirming the less variability in VOLTA’s results (r2 ≈ 0.92) than Glacier Bed Topography (GlabTop) (r2 ≈ 0.82). Overall, the mean percentage of ice thickness error for all measured profiles in the Upper Rhône catchment is around ±22%, of which 28 out of 42 glaciers are underestimated. By incorporating the vertical accuracy of free-ice DEM, we could identify 171 overdeepenings. Among them, 100 sites have a high potential for future lake formation based on four morphological criteria. The visual evaluation of deglaciated areas also supports the robustness of the presented methodology, as 11 water bodies were already formed within the predicted overdeepenings. In the wake of changing global climate, such results highlight the importance of combined datasets and parameters for projecting the future glacial landscapes. The timely information on future glacial lake formation can equip planners with essential knowledge, not only for managing water resources and hazards, but also for understanding glacier dynamics, catchment ecology, and landscape evolution of high-mountain regions.

scholarly journals Neural Networks Applied to Estimating Subglacial Topography and Glacier Volume

2009 ◽  
Vol 22 (8) ◽  
pp. 2146-2160 ◽  
Author(s):  
Garry K. C. Clarke ◽  
Etienne Berthier ◽  
Christian G. Schoof ◽  
Alexander H. Jarosch
Keyword(s):  
Neural Network ◽  
Regional Scale ◽  
Ice Thickness ◽  
Ice Dynamics ◽  
Ice Caps ◽  
Mountain Glaciers ◽  
The Neural Network ◽  
Glacier Ice ◽  
Subglacial Topography ◽  
Artificial Neural Network Ann

Abstract To predict the rate and consequences of shrinkage of the earth’s mountain glaciers and ice caps, it is necessary to have improved regional-scale models of mountain glaciation and better knowledge of the subglacial topography upon which these models must operate. The problem of estimating glacier ice thickness is addressed by developing an artificial neural network (ANN) approach that uses calculations performed on a digital elevation model (DEM) and on a mask of the present-day ice cover. Because suitable data from real glaciers are lacking, the ANN is trained by substituting the known topography of ice-denuded regions adjacent to the ice-covered regions of interest, and this known topography is hidden by imagining it to be ice-covered. For this training it is assumed that the topography is flooded to various levels by horizontal lake-like glaciers. The validity of this assumption and the estimation skill of the trained ANN is tested by predicting ice thickness for four 50 km × 50 km regions that are currently ice free but that have been partially glaciated using a numerical ice dynamics model. In this manner, predictions of ice thickness based on the neural network can be compared to the modeled ice thickness and the performance of the neural network can be evaluated and improved. From the results, thus far, it is found that ANN depth estimates can yield plausible subglacial topography with a representative rms elevation error of ±70 m and remarkably good estimates of ice volume.

scholarly journals Boundary layer models for calving marine outlet glaciers

2017 ◽  
Vol 11 (5) ◽  
pp. 2283-2303 ◽  
Author(s):  
Christian Schoof ◽  
Andrew D. Davis ◽  
Tiberiu V. Popa
Keyword(s):  
Boundary Layer ◽  
Ice Sheets ◽  
Ice Thickness ◽  
Ice Shelf ◽  
Bedrock Channel ◽  
Extensional Stress ◽  
Grounding Line ◽  
Direct Numerical Solution ◽  
Glacier Ice ◽  
Side Walls

Abstract. We consider the flow of marine-terminating outlet glaciers that are laterally confined in a channel of prescribed width. In that case, the drag exerted by the channel side walls on a floating ice shelf can reduce extensional stress at the grounding line. If ice flux through the grounding line increases with both ice thickness and extensional stress, then a longer shelf can reduce ice flux by decreasing extensional stress. Consequently, calving has an effect on flux through the grounding line by regulating the length of the shelf. In the absence of a shelf, it plays a similar role by controlling the above-flotation height of the calving cliff. Using two calving laws, one due to Nick et al. (2010) based on a model for crevasse propagation due to hydrofracture and the other simply asserting that calving occurs where the glacier ice becomes afloat, we pose and analyse a flowline model for a marine-terminating glacier by two methods: direct numerical solution and matched asymptotic expansions. The latter leads to a boundary layer formulation that predicts flux through the grounding line as a function of depth to bedrock, channel width, basal drag coefficient, and a calving parameter. By contrast with unbuttressed marine ice sheets, we find that flux can decrease with increasing depth to bedrock at the grounding line, reversing the usual stability criterion for steady grounding line location. Stable steady states can then have grounding lines located on retrograde slopes. We show how this anomalous behaviour relates to the strength of lateral versus basal drag on the grounded portion of the glacier and to the specifics of the calving law used.

Integrating and assessing Arctic glacier thickness data into Glacier Thickness Database (GlaThiDa) Version 3.0

2020 ◽  
Author(s):  
Ethan Welty ◽  
Francisco Navarro ◽  
Johannes Fürst ◽  
Isabelle Gärtner-Roer ◽  
Kathrin Naegeli ◽  
...  
Keyword(s):  
International Association ◽  
Surface Elevation ◽  
Survey Method ◽  
Ice Thickness ◽  
Unique Identifier ◽  
Related Information ◽  
Glacier Ice ◽  
Spatial Coordinates ◽  
Data Tables ◽  
Volume Estimates

<p>GlaThiDa is an internationally collected, standardized dataset of glacier thickness from in-situ and remotely sensed observations, based on data submissions, literature review, and airborne data from NASA's Operation IceBridge. GlaThiDa is a contribution to the working group on ‘glacier ice thickness estimation’ formed under the auspices of the International Association of Cryospheric Sciences (IACS). The database is hosted by the World Glacier Monitoring Service (WGMS). GlaThiDa is structured in three data tables of different levels of detail, which are linked together by a unique identifier for each glacier survey. The first table (T) is the overview table containing information on the location and area of the surveyed glacier, interpolated mean and maximum glacier-wide thickness and their reported uncertainties, the survey method and related information, as well as investigator names and source of the data. The second table (TT) includes mean and maximum ice thickness interpolated over surface elevation bands. The third table (TTT) contains the original point measurements, including spatial coordinates, surface elevation, and ice thickness. GlaThiDa was first released in 2014 (version 1.0) and first updated in 2016 (version 2.1). Version 3.0 was released in 2019. In addition to several technical improvements, nearly 3 600 ice-thickness surveys have been added, for a total of 5 181. Most of the new data are for Arctic glaciers, and some of these were collected for the H2020 INTAROS project. Moreover, GlaThiDa was assessed as a core component of the existing Arctic observing system in INTAROS Work Package 2.1 (an assessment of existing Arctic observational capacity and remaining gaps with respect to stakeholders needs). GlaThiDa has great potential as a reference dataset for calibrating and validating regional and global glacier volume estimates.</p>

Ice thickness, volume and subglacial relief of Ashuu-Tor, Bordu, Kara-Batkak and Golubina glaciers (Central-Asia) derived from GPR measurements and different approaching methods

2020 ◽  
Author(s):  
Lander Van Tricht ◽  
Philippe Huybrechts ◽  
Jonas Van Breedam ◽  
Johannes Fuerst ◽  
Oleg Rybak ◽  
...  
Keyword(s):  
Central Asia ◽  
Thickness Distribution ◽  
Mass Conservation ◽  
Tien Shan ◽  
Ice Age ◽  
Ice Thickness ◽  
Mountain Range ◽  
Lake Formation ◽  
Ground Penetrating ◽  
Thickness Measurements

<p>Glaciers in the Tien Shan (Central-Asia) mountains contribute a considerable part of the freshwater used for irrigation and households in the dry lowland areas of Kyrgyzstan and its neighbouring countries. Since the Little Ice Age, the total ice mass in this mountain range has been decreasing significantly. However, accurate measurements of the current ice volume and ice thickness distribution in the Tien Shan remain scarce, and accurate data is largely lacking at the local scale. In 2016, 2017 and 2019, we organized 1-month field campaigns in Central-Asia to sound the ice thickness of four different glaciers in the Tien Shan using a Narod ground penetrating radar (GPR) system.</p><p>Here, we present and discuss our in-situ ice thickness measurements of the four glaciers. We performed in total more than 1000 GPR soundings. We found a maximum ice thickness of 200 meters in the central part of the southern facing Ashuu-Tor glacier. On both Bordu and Golubina, we measured ice thicknesses up to 140 meters. Kara-Batkak was found to have the thinnest ice which is in agreement to the large average slope of this glacier. We extended all the ice thickness measurements to the entire glacier surfaces using three different methods based on the assumption of plastic flow (method 1) and the principle of mass conservation (method 2 & 3) and assessed their differences.</p><p>In this research, we show a detailed ice thickness distribution of Ashuu-Tor, Bordu, Golubina and Kara-Batkak glaciers. This can be used for glaciological modelling and assessing ice and water storage. We also point out the locations of potential lake formation in bedrock overdeepenings as a succession of glacier retreat.</p>

scholarly journals Impact of frontal ablation on the ice thickness estimation of marine-terminating glaciers in Alaska

2019 ◽  
Vol 13 (10) ◽  
pp. 2657-2672 ◽  
Author(s):  
Beatriz Recinos ◽  
Fabien Maussion ◽  
Timo Rothenpieler ◽  
Ben Marzeion
Keyword(s):  
Sea Level ◽  
Thickness Distribution ◽  
Regional Scale ◽  
Ice Thickness ◽  
Potential Contribution ◽  
Volume Estimate ◽  
Tidewater Glaciers ◽  
Thickness Estimation ◽  
The Impact ◽  
Frontal Ablation

Abstract. Frontal ablation is a major component of the mass budget of calving glaciers, strongly affecting their dynamics. Most global-scale ice volume estimates to date still suffer from considerable uncertainties related to (i) the implemented frontal ablation parameterization or (ii) not accounting for frontal ablation at all in the glacier model. To improve estimates of the ice thickness distribution of glaciers, it is thus important to identify and test low-cost and robust parameterizations of this process. By implementing such parameterization into the ice thickness estimation module of the Open Global Glacier Model (OGGM v1.1.2), we conduct a first assessment of the impact of accounting for frontal ablation on the estimate of ice stored in glaciers in Alaska. We find that inversion methods based on mass conservation systematically underestimate the mass turnover and, therefore, the thickness of tidewater glaciers when neglecting frontal ablation. This underestimation can amount to up to 19 % on a regional scale and up to 30 % for individual glaciers. The effect is independent of the size of the glacier. Additionally, we perform different sensitivity experiments to study the influence of (i) a constant of proportionality (k) used in the frontal ablation parameterization, (ii) Glen's temperature-dependent creep parameter (A) and (iii) a sliding velocity parameter (fs) on the regional dynamics of Alaska tidewater glaciers. OGGM is able to reproduce previous regional frontal ablation estimates, applying a number of combinations of values for k, Glen's A and fs. Our sensitivity studies also show that differences in thickness between accounting for and not accounting for frontal ablation occur mainly at the lower parts of the glacier, both above and below sea level. This indicates that not accounting for frontal ablation will have an impact on the estimate of the glaciers' potential contribution to sea-level rise. Introducing frontal ablation increases the volume estimate of Alaska marine-terminating glaciers from 9.18±0.62 to 10.61±0.75 mm s.l.e, of which 1.52±0.31 mm s.l.e (0.59±0.08 mm s.l.e when ignoring frontal ablation) are found to be below sea level.

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