Various techniques exist to model the evolution from glaciers at regional to global scales. Whereas pioneering efforts typically relied on volume-area scaling approximations or parameterizations based on observed glacier changes (retreat parameterization), more recent approaches now also explicitly incorporate ice-dynamical processes. In these latter studies, glaciers are typically represented through central flowlines. Such flowline approaches are particularly suited for mountain glaciers that span over a large elevation range, i.e. valley-glaciers with an elongated shape. However, flowline approaches are not ideal to represent the geometry of ice caps (large glaciers) that generally have a dome-shaped geometry. For ice caps, a model representation that explicitly accounts for the glacier’s 3D geometry and that allows for the glacier to lose and gain mass in all directions, both through mass balance and ice dynamic processes, is needed.

Here we present simulations performed with a coupled surface mass balance – ice flow model that explicitly accounts for the 3D geometry of individual glaciers. The model, written in Python, relies on the shallow ice approximation to describe ice flow, allowing to run large ensembles of simulations. The goal is to simulate the temporal evolution of glaciers with distinct shapes and situated in various climatic regimes, i.e. having a model that allows for an automated intialization and that is suited for regional to global-scale applications.

In this contribution, we present simulations performed with this new large-scale model for regions with mountain glaciers (e.g. European Alps and Scandinavia), as well as regions with large ice caps (e.g. Iceland). Through this, we highlight various challenges that relate to model initialization or the choice of model settings, for instance. We also explore how simulated glacier evolutions compare to those simulated with a retreat parameterzation and through flowline modelling, thereby shedding light on the need for a 3D modelling approach.

How to cite: Zekollari, H., Huss, M., Compagno, L., Pattyn, F., Goelzer, H., Lhermitte, S., Wouters, B., and Farinotti, D.: Modelling the 3-D evolution of glaciers at regional to global scales: challenges and opportunities, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4231, https://doi.org/10.5194/egusphere-egu22-4231, 2022.

The purpose of the research is to assess the influence of the random weather fluctuations on the estimates of the model-based surface mass balance (SMB) components of the mountain glacier. The common approach in the modeling studies is to use meteorological records (measured or modelled) – surface air temperature and precipitation rate – as weather forcing in numerical experiments. The results of the calculations are normally very sensitive to the parameter choice and the model should be carefully calibrated against measured SMB to obtain correct results. What is usually ignored within the frameworks of this approach is that forcing records at e.g. daily resolution contain internal weather variability which after being integrated by the model can yield in a random walk type trend of SMB.   

To evaluate uncertainty in SMB calculations we force an energy balance model of Djankuat glacier in the Central Caucasus with surrogate series of surface air temperature and precipitation rate. The surrogate series of several model decades duration each are produced by a stochastic weather generator WGEN basing on the observed meteorological series at the weather stations located nearby. In WGEN, precipitation events are simulated by a first-order Markov chain, and the intensity of precipitation is represented using independent gamma distribution. Air temperature is calculated by fitting the appropriate distributions and harmonic functions separately for wet and dry days. Seasonality is reproduced by an estimate of individual sets of model parameters for different periods of the year.

Statistical analysis of the generated ensemble of SMB components revealed that relative standard deviation (RSD) of SMB components (accumulation rate, melting, evaporation, melt water retention) vary within the limits 3-6%, but RSD of the specific mass balance is several times higher.

Our approach enables to filter out reaction of the modeled glaciers induced by the weather noise from systematic reply on climate change.

The reported study was funded by the RFBR and RS grant 21-55-10003.

How to cite: Rybak, O. and Rybak, E.: Evaluating uncertainties in modelled surface mass balance components of a mountain glacier, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8893, https://doi.org/10.5194/egusphere-egu22-8893, 2022.

Within the earth system, glaciers serve as important indicators of climate change, being principally governed by temperature and precipitation. Additionally, they provide essential freshwater storage on various scales, ranging from long-term in firn and ice, to short-term storage in snow cover. By preventing precipitation from immediately turning into runoff, glaciers fulfill a buffering role within their basins, providing downstream runoff during melt season. With changes in glacier mass balance in response to changes in climate, a glacier's buffering capacity is altered simultaneously. In order to predict the evolution of runoff on temporal scales relevant to water resource management (5-15 years), it is essential to observe and simulate glacier mass balance on the same scale. The current research presents a global modelling approach using the Open Global Glacier Model (OGGM), forced with a multi-model, multi-member retrospective ensemble of monthly temperature and precipitation re-forecasts (hindcasts) from the Decadal Climate Prediction Project (DCPP), part of the Coupled Model Intercomparison Project, phase 6 (CMIP6). The decadal hindcasts are initialized each year in the period 1960-2010 and are bias corrected for model drift, while retaining the period's warming trend, using a lead-time based correction. The hindcasts are then downscaled to the glacier scale and used to compute the climatic mass balance with OGGM, with fixed glacier geometries. The method is validated using 274 reference glaciers, which have a >5 year observational record. It is then applied globally, to all land-terminating glaciers in the Randolph Glacier Inventory (RGI), outside the Greenland Ice Sheet and Antarctica. The results indicate merit in using decadal re-forecasts to model glacier mass balance, paving the way for reliable decadal scale runoff predictions on regional and global scales.

How to cite: van der Laan, L., Förster, K., Scaife, A., Vlug, A., and Maussion, F.: Assessing skill and use of CMIP6 decadal re-forecasts in global glacier mass balance modelling , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11942, https://doi.org/10.5194/egusphere-egu22-11942, 2022.

The geodetic method has become a popular tool to measure glacier elevation changes over large glacierized regions with high accuracy for multi-annual to decadal time periods. In contrast, the glaciological method provides annually to seasonally resolved information on glacier evolution, but only for a small sample of the world’s glaciers (less than 1%). Various methods have been proposed to bridge the gap on spatio-temporal coverage of glacier change observations and to provide annually-resolved glacier mass balances using the geodetic sample as calibration. Thanks to a new global and near-complete (96% of the world glaciers) dataset of geodetic mass balance observations, this goal has become feasible at the global scale. Inspired by previous methodological frameworks, we developed a new approach to combine the glacier distribution from the globally-complete Randolph Glacier Inventory with the mass balance and elevation change observations from the Fluctuation of Glaciers database of the World Glacier Monitoring Service (WGMS). Our results provide a global assessment of annual glacier mass changes and related uncertainties for every individual glacier during the 2000–2020 period. The glacier-specific time series can then be integrated into an annually-resolved global gridded glacier change product at any user-requested spatial resolution, useful for comparison with gravity-based products, calibration or validation of glacier mass balance models operating at a global scale and to improve calculations of the glacier contribution to regional hydrology and global sea-level rise.

How to cite: Dussaillant, I., Hugonnet, R., Huss, M., Berthier, E., Paul, F., and Zemp, M.: An annual mass balance estimate for each of the world’s glaciers based on observations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6338, https://doi.org/10.5194/egusphere-egu22-6338, 2022.

Crunching satellite imagery or Digital Elevation Models (DEMs) is part of your weekly routine?

You are desperate to calculate glacier volume changes despite gappy observations?

Your head blows up just trying to provide those errors bars for your mass balance estimates?

You think science should be fully reproducible?

Python is one of your favourite programming languages?

If you answered yes to any two of those questions, you should definitely attend this presentation!

Remote sensing is becoming increasingly important in our understanding of global glacier changes. Dozens of studies each year aim at estimating geodetic glacier mass balance from the regional to the global scale, providing factual numbers behind glacier retreat. But how reliable are those numbers? Current approaches raise several problems:

• External data, such as glacier outlines can be updated regularly, as is done e.g. with the RGI outlines, potentially making previous estimates obsolete.
• Data processing techniques, such as DEM coregistration or gap-filling, evolve over time in the community.
• Many results are not reproducible or cannot even be updated, because access to the data or code is not granted.

All these issues make the comparison and validation of older vs newer studies challenging and questions the reliability of glacier change estimates. Why not team-up and create the tools we all dream of?

Here we present xDEM, an open-source, community-built and easy-to-use set of tools for DEMs postprocessing and volume change calculation. The tool is designed as a set of Python modules, built on top of popular libraries (rasterio, geopandas, GDAL). It will ultimately provide all that is needed to turn individual raw DEMs into a geodetic volume change and its uncertainties: coregistration, bias correction, gap-filling, volume change calculation and spatial statistics (e.g. variograms). The concept behind xDEM is:

Ease of use: Python modules developed by glaciologists, (mostly) for glaciologists.

Flexibility and modularity: We offer a set of options, rather than favouring a single method and make it straightforward to combine them.

Reproducibility: Version-controlled; releases saved with DOI; test-based development ensures our code always performs as expected.

The progress of the project can be followed at https://github.com/GlacioHack/xdem.

We illustrate the use of xDEM for various test cases and on-going projects to post-process DEMs obtained from ~1930 terrestrial images of the Swiss Alps, American reconnaissance KH-9 satellite images, modern ASTER and Pleiades images or the recent RAGMAC intercomparison experiment.

How to cite: Dehecq, A., Mannerfelt, E., Hugonnet, R., and Tedstone, A.: xDEM - A python library for reproducible DEM analysis and geodetic volume change calculations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5781, https://doi.org/10.5194/egusphere-egu22-5781, 2022.

GLIMS, Global Land Ice Measurements from Space, is an initiative that involves ~250 analysts from 34 countries and has the purpose of mapping all glaciers in the world (excluding the Greenland and Antarctic ice sheets) on a periodic basis.  The GLIMS Glacier Database, which became an official product of the NASA NSIDC DAAC (Distributed Active Archive Center) in 2019, contains time series of glacier outlines from different data sources.  Various parts or facies of glaciers are mapped, including the full glacier extent, debris-covered parts, internal rock outcrops, and glacial lakes.  The Randolph Glacier Inventory (RGI) is a snapshot map of glaciers, with one outline per glacier, as close as possible to a target date.

In the last year, GLIMS and the RGI working group have been working closely together to ingest new data into GLIMS and to improve GLIMS and RGI software tools. The goal is to improve data completeness and quality and to make the creation of the RGI smoother and more transparent (Maussion et al., EGU22-4484).  New data include approximately 60,000 outlines from 14 regions in all parts of the Earth, with times ranging from the Little Ice Age to 2018. Software improvements include more quality-control checks and constraints, such as separating multi-polygons into individual ones. 

The presentation will provide an overview on the latest data additions and software developments in GLIMS and the synergy with RGI production.

How to cite: Raup, B., Maussion, F., Paul, F., Berthier, E., Bolch, T., Kargel, J., and Racoviteanu, A.: More data and increased automation leads to better quality for GLIMS and RGI glacier data sets, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10563, https://doi.org/10.5194/egusphere-egu22-10563, 2022.

We give an overview of the Instructed Glacier Model (IGM) -- a new framework to model the evolution of glaciers at any scale by coupling ice dynamics, surface mass balance, and mass conservation. The key novelty of IGM is that it models the ice flow by a Convolutional Neural Network (CNN), which is trained from physical high-order ice flow mechanical models. Doing so has major advantages in both forward and inverse modelling.

In forward modelling, the most computationally demanding model component (the ice flow) is substituted by a very cheap CNN emulator. Once trained with representative data, IGM permits to model individual mountain glaciers several orders of magnitude faster than high-order ones on CPU with fidelity levels above 90 % in terms of ice flow solutions leading to nearly identical transient thickness evolution. Switching to Graphics Processing Unit (GPU) permits additional significant speed-ups, especially when modelling large-scale glacier networks and/or high spatial resolutions.

In inverse modelling, the substitution by a CNN emulator does not only speed up but facilitates dramatically the data assimilation step, i.e. the search for optimal ice thickness and ice flow parameter spatial distributions that match spatial observations at best (such as ice flow, surface topography or ice thickness profiles) while being consistent with the high-order ice flow mechanics. The reason is that inverting a CNN can take great benefit from the tools used for its training such as automatic differentiation, stochastic gradient methods, and GPU.

IGM is an open-source Python code (https://github.com/jouvetg/igm), which deals with two-dimensional gridded input and output data. Together with a companion library of trained ice flow emulators, IGM permits user-friendly, computationally highly-efficient, easy-to-customize, and mechanically state-of-the-art glacier forward and inverse modelling at any scale. We illustrate its potential by replicating a simulation of the great Aletsch Glacier, Switzerland, from 1880 to 2100, based on a Stokes model. The complete workflow (data assimilation and 220 years long forward modelling) at 100 m of resolution takes about 1-2 min on the GPU of a laptop and can be replicated and adapted easily using an online Colab notebook.

How to cite: Jouvet, G., Cordonnier, G., Kim, B., Luethi, M., Vieli, A., and Aschwanden, A.: IGM, a glacier evolution model accelerated by deep-learning and GPU, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7271, https://doi.org/10.5194/egusphere-egu22-7271, 2022.

Concepts and ideas related to implementation of calving in large-scale ice-sheet models are presented and discussed, and new model verification experiments proposed. For unconfined ice shelves, any calving law where the calving rate increases with cliff height (free board) must lead to an unstable advance or retreat. No other solutions are possible and all calving front positions are always unstable. If in contrast, calving rate is a monotonically decreasing function of cliff height, both stable and unstable positions are possible. An example of such a configuration and simple analytical solution for the transient evolution of the calving front is provided, which can be used for numerical verification purposes. It is argued that cliff-height based calving laws are, at least for the case of buttressed ice shelves, arguably unphysical as they can result in a multi-valued function for the calving rate as a function of local state of stress. Implementation of a new variational form of the level-set method, involving forward-and-backward diffusion, for capturing the evolution of calving fronts is discussed and several applications to Pine Island and Thwaites glacier shown.

How to cite: Gudmundsson, G. H.: Implementation of calving processes in large-scale ice sheet models, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4263, https://doi.org/10.5194/egusphere-egu22-4263, 2022.

Energy budget-based distributed modelling in glacierized catchments is important to examine glaciological-hydrological regimes and compute flow rates in current and projected scenarios. Trends in ablation of snow and glaciers retreat depend upon snow and ice reserves, meteorological parameters and geographical features which vary across sub-basins in Upper Indus Basin. This study attempts to address these issues by employing [1] regional climate models (RCMs) and the Physical based Distributed Snow Land and Ice Model (Ranzi and Rosso 1991; Grossi et al. 2013) in the Naltar catchment (area of 242.41 km2, with 42 km2 glacierized), located in the Hunza river basin (Upper Indus Basin), to project snow and glacier melt and daily streamflow. The calibration and validation of the model were successfully carried out using observed historical meteorological data at hourly time resolution from high altitude meteorological stations (Liaqat et al. 2021). For each of the climate simulations, projections of near future (2040-2059) and far future (2080-2099) under three Representative Concentration Pathways (RCPs) namely RCP2.6, RCP4.5, and RCP8.5 are presented[2]  with respect to corresponding present climate (1991-2010). We used all relevant meteorological variables from an ensemble of 37 simulations in total, which were performed by 3 RCMs driven by 11 different global climate models (GCMs) and were developed under the CORDEX Experiment, (Giorgi et al. 2009)-South Asia initiative. RCMs often present systematic biases and, despite their rather high spatial resolution (here approximately 50km x 50km) they are still too coarse for hydrological impact assessments. In order to produce localized and unbiased climate projections, we scaled the observed climate according to the simulated changes by means of the delta change method as described in Räisänen and Räty (2013) and Räty et al. (2014). Correction factor [3]  in the mean and standard deviation for all for all meteorological variables were obtained for the near and far future periods compared to the historical period (1991-2010) for each simulation. [4] T[5] he joint analysis of climate projections and hydrological modelling, spanning different scenarios and other sources of uncertainty is essential to predict future changes in water resources availability to satisfy mainly irrigation demand in the downstream areas.

References

Giorgi F, Jones C, Asrar GR (2009) Addressing climate information needs at the regional level: the CORDEX framework World Meteorological Organization Bulletin 58:175

Grossi G, Caronna P, Ranzi R (2013) Hydrologic vulnerability to climate change of the Mandrone glacier (Adamello-Presanella group, Italian Alps) Advances in water resources 55:190-203

Liaqat MU, Grossi G, Ansari R, Ranzi R Modeling Hydrological Vulnerability to Climate Change in the Glacierized Naltar Catchment (Pakistan) Using a Distributed Energy Balance Model. In: AGU Fall Meeting 2021, 2021. AGU,

Räisänen J, Räty O (2013) Projections of daily mean temperature variability in the future: cross-validation tests with ENSEMBLES regional climate simulations Climate dynamics 41:1553-1568

Ranzi R, Rosso R (1991) Physically based approach to modelling distributed snowmelt in a small alpine catchment IAHS PUBL, IAHS, WALLINGFORD:141-150

Räty O, Räisänen J, Ylhäisi JS (2014) Evaluation of delta change and bias correction methods for future daily precipitation: intermodel cross-validation using ENSEMBLES simulations Climate dynamics 42:2287-2303

How to cite: Liaqat, M. U., Casanueva, A., Grossi, G., and Ranzi, R.: Future climate and runoff projections in the Naltar Catchment, Upper Indus Basin from CORDEX-South Asia regional climate models and hydrological modelling, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6030, https://doi.org/10.5194/egusphere-egu22-6030, 2022.

Over recent decades, a significant increase in the amount and the size of glacier lakes has been observed. These lakes enhance glacier mass loss but also present societal hazard as they may retain large volumes of water. When large lakes drain, the downstream valleys can severely be impacted by the resulting glacial lake outburst floods (GLOFs), potentially leading to infrastructural damage and ecological impacts. Most studies assessing the future evolution and potential hazards from glacial lakes focus on proglacial lakes, i.e. lakes that are dammed by either moraines or bedrock. Albeit typically more hazardous, ice-dammed lakes including supraglacial lake are generally neglected in such assessments. 

Here, we assess for the first time the formation and development of potential ice-dammed lakes for all glaciers in High Mountain Asia. To do so, we model the geometry of each glacier by linking past digital elevation models to outputs of the combined glacier mass balance, ice flow and debris evolution model GloGEMflow. We identify potential ice-dammed lakes in depressions at the surface and margins of glaciers, and model their geometrical evolution by accounting for the enhanced melt caused by the lakes’ presence. The model is calibrated and evaluated with independent datasets. 

To analyze the ice-dammed lakes’ sensitivity to climate change, we model the evolution of glaciers and their ice-dammed lakes under different Shared Socioeconomic Pathways (SSPs). Our results indicate that the total number of potential ice-dammed lakes will first increase through time, and then diminish as glaciers shrink, reducing confining barriers. Compared to 2000, a moderate warming scenario (SSP126) anticipates approx. 42% more lakes by 2050, whilst in a strong warming scenario (SSP585), the increase is of ~46%. By the end of this century, the number of ice-dammed lakes will diminish compared to the 2050 peak by approx. 16%  (SSP126) and ~42% (SSP585) due to glacier shrinkage. The same pattern is also expected for the lakes’ volume evolution, which is expected to increase compared to 2000 between ~79% (SSP119) and ~87% (SSP585) by 2050, for then diminish by about 8% by the end of the century for SSP585 compared to 2050.  Finally, by investigating the largest ice-dammed lakes, we highlight regions that could be of particular relevance when aiming at anticipating future GLOFs from ice-dammed lakes.

How to cite: Compagno, L., Huss, M., Zekollari, H., Miles, E., and Farinotti, D.: Anticipating future ice-dammed lakes across High Mountain Asia, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-24, https://doi.org/10.5194/egusphere-egu22-24, 2022.

The number and extent of glacial lakes in mountain regions worldwide has increased over recent decades as glaciers have lost mass. These ice-contact lakes modify the dynamic response of glaciers to climate change, presenting a challenge to projecting their future evolution. In High Mountain Asia (HMA) glacial lakes have expanded by more than 45% in the last 30 years. Previous studies have demonstrated the contrasting dynamic evolution of lake- and land-terminating glaciers in the Eastern Himalaya, although it was previously unclear if this was a localised phenomenon. Using existing and manually derived datasets, we observed glacier surface velocity, surface elevation, terminus position and glacial lake area change across HMA’s differing climatic regimes over a twenty-year period (2000–2020) to investigate the dynamic evolution of ~60 lake- and land-terminating glaciers.

Our results show that lake-terminating glaciers in the Himalaya, Karakoram and Pamir experienced faster ice flow in the ablation zone, significant surface thinning and extensive terminus recession in comparison to land-terminating glaciers over the same period. The majority of lake-terminating glacier population experienced a glacier-wide increase in velocity during the twenty-year observation period, including 58% of individual glaciers. In comparison, 62% of land-terminating glaciers experienced a decrease in velocity during the same period. This result suggests that lake-induced dynamic changes are occurring irrespective of the regional climatic regime. Our observations also revealed that lake-terminating debris-covered glaciers experienced a greater magnitude of change in velocity, surface elevation and terminus position, than their clean ice counterparts. These results are important for making projections of future glacier change in HMA where many debris-covered glaciers are pre-disposed to the development of terminal lakes in the next few decades.

How to cite: Scoffield, A., Rowan, A., and Sole, A.: The influence of ice-contact lakes and supraglacial debris on glacier change in High Mountain Asia , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7754, https://doi.org/10.5194/egusphere-egu22-7754, 2022.

A common disadvantage of almost all global glacier models is that they ignore the explicit description of the debris cover on the heat exchange of the glacier surfaces with the atmosphere. Debris cover plays a key role in the regulation of melt processes. A debris cover more than a few centimeters reduces melting, since it isolates the underlying ice. In this way, debris covered areas are thought to be less exposed to rising temperatures, thereby reducing glacier retreat and mass loss.        

In the foothills of the North Caucasus, an important agricultural region, the problem of expected changes in mountain glaciation is particularly acute, since fluctuations in the flow regime of local rivers depend on the evolution of glaciers: the contribution of glacial runoff to total discharge is very significant.

Here, we present the assessment of debris cover influence on the glacier evolution of the Northern Caucasus on a regional scale (Terek and Kuban river basins). The aim is to determine how much the characteristics of mountain glaciation (its mass balance, area, volume, position of the glacier fronts) of the Northern Caucasus depend on the debris cover evolution. In order to accomplish this goal, we use the GloGEMflow model and a newly created debris cover dynamic module, which is calibrated using newly mapped debris cover outlines. The debris thickness evolution is simulated with a steady deposit model adapted from Verhaegen et al. (2020) and Anderson & Anderson (2016), where debris input onto the glacier is generated from a fixed point on the flow line.

The results reveal that the debris cover evolution pattern differ significantly for Terek and Kuban glacierized basins. Lower elevated Kuban basin glaciers undergo a rapid retreat and lose the debris covered glacier tongues while the Terek basin glaciers experience supraglacial debris expansion with a six times larger effect of debris cover on glacier volume evolution. From 2000 to 2016 the mass loss in the Terek ice basin reached 47834 Mt with an influence of the debris cover module and 50435 Mt  under debris-free conditions. Therefore, we can expect that by the end of the current century the mass loss of the Terek glaciers will be significantly overestimated in case debris cover influence will be ignored in model calculations. On the contrary, in the Kuban basin, calculated mass loss in 2000-2016 with and without debris cover were 1249 Mt  and 1258 Mt  respectfully. Committed loss experiments (constant mean climate for 1990-2015) show that the glaciers of the Terek basin lose ~35% of ice if debris cover is not taken into account and ~29% if debris cover module is turned on (~2  ice volume difference). For the Kuban basin glaciers, the difference of ice volume is only ~0.1  in debris-free vs. debris-covered modes.

The reported study was funded by the RFBR and RS grant 21-55-10003, the work of T. Postnikova was supported by the RFBR grant 20-35-90042.

How to cite: Postnikova, T., Rybak, O., Zekollari, H., Huss, M., Gubanov, A., and Nosenko, G.: Debris cover effect on the evolution of glaciation in the Northern Caucasus, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7736, https://doi.org/10.5194/egusphere-egu22-7736, 2022.

In the northern Japanese Alps, more than 100 perennial snow patches exist (Higuchi and Iozawa, 1971)．Recently, several groups measured the ice thickness and horizontal flow velocity of seven perennial snow patches in the region, finding them to be active glaciers (e.g., Arie et al., 2019). As they are less than 0.5 km² in area, they are classified as very small glaciers (VSGs). According to Arie et al. (2021), who observed the mass balance using geodetic methods from 2015 to 2019, 1) the fluctuation of the annual mass balance of Japanese VSGs was highly dependent on yearly fluctuation in accumulation depth, 2) the mass balance amplitude was the largest of all glaciers in the world recorded by WGMS, 3) VSGs can be formed only in terrains where avalanches and snowdrifts can acquire more than double the snowfall. However, for avalanches and snowdrifts in 3), the specific topographic conditions that indicate the magnitude of these contributions are not clear. Hughes (2009) found that the contribution of avalanches to the glacier is large where the "avalanche ratio," which is the ratio of total avalanche discharge area to total glacier area, is high.
 
In this study, we compared the avalanche ratio, distribution altitude, and slope direction of the seven confirmed VSGs, seven large perennial snow patches (over 10,000 m²), and three small perennial snow patches (under 1000 m²) to show the topographic conditions for the formation of glaciers and perennial snow patches in the northern Japanese Alps. As a result, there was a positive correlation between the average snow depth of VSGs calculated by the geodetic method from 2015 to 2021 and the avalanche ratio. A negative correlation was seen between the avalanche ratio and distribution altitude in the VSGs, and the lower the altitude, the higher the avalanche ratio. In addition, the relationship between avalanche ratio and distribution altitude showed that the avalanche ratio of VSGs and large perennial snow patches were larger than that of small perennial snow patches at the same altitude. The avalanche ratio of Ikenotan Glacier, which is the only glacier on the windward slope with no snowdrift, was more than twice as large as that of VSGs at the same altitude. These results suggest that the magnitude of the contribution of avalanche and snowdrift deposition and the distribution altitude determine the size of glaciers and perennial snow patches.
 
Arie, K., Narama, C., Fukui, K., Iida, H. and Takahashi, K.: Ice thickness and flow of the Karamatsuzawa perennial snow patch in the northern Japanese Alps, Journal of the Japanese Society of Snow and Ice, 81(6), 283–295, doi:10.5331/seppyo.81.6_283, 2019.
Arie, K., Narama, C., Yamamoto, R., Fukui, K. and Iida, H.: Characteristics of mountain glaciers in the northern Japanese Alps, cryosphere, 1–28, doi:10.5194/tc-2021-182, 2021.
Higuchi, K. and Iozawa, T.: Atlas of perennial snow patches in central Japan, Water Research Laboratory. Faculty of Science, Nagoya University., 1971.
Hughes, P. D.: Twenty-first Century Glaciers and Climate in the Prokletije Mountains, Albania, Arct. Antarct. Alp. Res., 41(4), 455–459, 2009.

How to cite: Arie, K. and Narama, C.: Topographic conditions for the formation of glaciers and perennial snow patches in the northern Japanese Alps, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-131, https://doi.org/10.5194/egusphere-egu22-131, 2022.

The evolution of glaciers and ice sheets depends sensitively on the processes occurring at their boundaries such as, e.g., the ice-bedrock interface or shear margins. These boundary regions share as common characteristics the transition from flow to no flow over a relatively short distance, resulting in a complex and fundamentally non-hydrostatic stress field. The localised intense shearing may further induce weakening of the ice owing to thermomechanical interactions, ultimately accelerating and potentially destabilising the bulk of the ice. Better understanding the sensitivity of these near-boundary processes is vital and challenging as it requires non-linear and coupled full Stokes models that can afford very high resolution in three-dimensions.

We present recent development of a thermomechanical coupled numerical model that leverages graphical processing units (GPUs) acceleration to resolve the instantaneous stress and velocity fields within ice flow over complex topography in three dimensions. We apply the model to various glaciers of the Swiss Alps resolving the complex flow field in three dimensions and at very high spatial resolution. We further use the model to assess the competition between basal sliding and internal sliding, the latter referring to the formation of a near-basal internal shear zone within the ice owing to thermomechanical feedback. We finally provide some insights in GPU-based high-performance computing model development using the Julia language and the ongoing development of efficient implicit iterative solvers based on the accelerated pseudo-transient method.

How to cite: Räss, L., Utkin, I., and Omlin, S.: Resolving thermomechanical ice flow on Alpine topography, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12741, https://doi.org/10.5194/egusphere-egu22-12741, 2022.

Ice flow models include processes which cannot be determined from observational data, but must be represented mathematically in order to simulate the physical system. One such process is the interaction between the ice and the bedrock, basal sliding, which enters models in the form of a sliding law describing the relationship between basal drag and velocity. Basal sliding is a major factor in ice flow, and therefore how it is represented is one of the most important modelling decisions.

Several sliding laws have been proposed and used in ice flow models, representing different types of bed. In general, these comprise some combination of a Weertman-style power law and Coulomb friction. The equations for sliding laws contain parameters which are usually given constant, uniform values. The responses to perturbations in the ice flow system differ depending on the sliding law used, and on the parameter choices made.

In this study, we use the ice flow model Úa to run experiments for a range of different sliding laws, and different values for parameters within these laws. In each case, we test the response of the model to perturbations in the ice shelf melt rate. We investigate the differences between our model outputs, and assess the relationships between sliding law parameter choices and the resulting changes in ice flow.

Our model domain covers the Amundsen Sea Embayment, which we break down into separate catchment areas during our analysis in order to capture localised variation in our results.

How to cite: Barnes, J. and Gudmundsson, H.: The effects of parameter choices in basal sliding laws on a modelled ice flow response to perturbations in forcing, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8658, https://doi.org/10.5194/egusphere-egu22-8658, 2022.