Glacier modelling and downstream impacts

Abstract/Description

Glaciers are important components of the global water cycle, acting as natural reservoirs that provide water for downstream ecosystems and communities. Understanding how glaciers respond to a warming climate is fundamental for predicting future water resources. Debris-covered glaciers complicate this due to the heterogeneous effects that debris cover has on ice melt. Changes in debris extent and thickness affect melt rates, runoff, and glacier evolution. Despite this, many studies focus on glacier retreat and runoff changes while overlooking the dynamic role of debris cover. The interaction between debris extent and debris thickness evolution, sub-debris melt and long-term runoff remains poorly understood in debris-covered glacier systems. We investigate the long-term hydrology of the ~190 km2 Aletschgletscher catchment in the Swiss Alps by integrating debris-cover extent and thickness evolution into mass balance and runoff modelling, addressing a significant knowledge gap in how debris evolution influences hydrological systems. Using the mechanistic land surface model Tethys-Chloris, we reconstruct mass balance and runoff as far back as the early to mid-20th century. Historical maps from SwissTopo were used to reconstruct yearly glacier and debris extents as well as DEMs derived from contour lines. Fieldwork conducted in 2023 provides a comprehensive characterisation of debris properties, allowing us to estimate past debris thicknesses based on interpolation of present day debris-thickness to past debris free periods. Meteorological data from MeteoSwiss and ERA5-Land serve as inputs for the model. Initial results show how changes in debris cover extent and thickness have influenced glacier mass balance and runoff over time. Our findings show the role debris cover plays in controlling glacier hydrology, highlighting the need to incorporate debris dynamics into future predictions of glacier runoff and water resource management in a warming climate.

Abstract/Description

Crevasses are critical components of the cryo-hydrologic system. The Continuum Damage Mechanics (CDM) framework has emerged as a promising approach for modeling crevasse fields. However, its application relies on poorly constrained parameters, such as the critical stress threshold, and by the lack of consensus on appropriate stress invariants that should be considered for fracture initiation (the so-called damage criterion). Studies based on observations notably face uncertainties in converting observed strain or strain rate into stress estimates. In this study, we use a carefully monitored artificial drainage event of a water-filled cavity on the Tête Rousse Glacier in 2010 to investigate fracture initiation processes, focusing on refining damage criteria and stress thresholds. Using the finite element code Elmer/Ice, we simulate the drainage and subsequent refilling of the cavity over three consecutive years. The simulated stress distributions are compared to a field of circular crevasses that were mapped around the cavity during the summer following the first drainage operation. Our results show that stress patterns derived from a non-linear viscous mechanical response (i.e., Glen’s flow law with n = 3) better match observed crevasse fields than those assuming a linear viscous or a linear elastic mechanical behavior. Furthermore, by evaluating four commonly used damage criteria in glaciology-related applications -maximum principal stress, von Mises, Hayhurst, and Coulomb- we show that the maximum principal stress criterion, paired with a stress threshold of approximately 100 to 130 kPa, provides the best reproduction of the observed crevasse field.

Abstract/Description

Andean glaciers are some of the least understood and least modelled glaciers, despite being a crucial component of Andean water towers. Glaciers across the Andes have lost ~25% of their area since the Little Ice Age, while global-scale ice-models predict ~90% ice loss by 2100 CE under the highest emission scenarios. These global-scale ice-models, however, are limited in their utility for regional projections, due to their use of; i) limited mass-balance observations over Andean glaciers that can provide model-data calibration; ii) downscaled global climate models, which are poor at capturing the climatology over mountains; and iii) simplified ice-flow and mass balance processes.

As part of the Deplete and Retreat: The Future of Andean Water Towers project, we aim to develop a modelling framework which overcomes these challenges. We will combine the use of high-resolution dynamically downscaled climate data and COSIPY, a snowpack and ice surface energy and mass balance model, to produce time varying glacial surface mass balance and temperature fields. These are used to force the Parallel Ice Sheet Model (PISM) to produce high resolution ice-flow simulations of past, present, and future ice mass changes in hydrologically important catchments over the Andes.

Here, we present our initial completion of this modelling framework over the Cordillera Vilcanota region. We present time transgressive model outputs, compared against their LIA and present day ice extents to ensure the model is accurately capturing already observed ice changes. This is then forced into the future with mass balance and temperature fields generated under different emission scenarios to project the status of glacier ice in 2150 CE. Future work will expand our approach to other catchment areas that span the Andes, to project glacier changes in a warming world and understand the future implications for water towers.

Abstract/Description

Worldwide glacier retreat outside the two large ice sheets is increasingly tangible and the associated ice-loss has dominated the cryospheric contribution to sea-level change for many decades. This ice loss has also become symbolic for the effects of rising temperatures. In addition to the anticipated importance for future sea-level rise, continuing glacier mass loss will affect seasonal freshwater availability and might add to water-stress in this century in many regions.

Here, we present a self-consistent, ice-dynamic forecasting framework for glacier evolution. For the first time, each glacier on Earth can be treated as a three-dimension body within its surrounding topography without the severe geometric simplifications typical on regional and global scales. The heart of the framework is the systematic utilisation of the rapidly growing body of information from satellite remote sensing. For this purpose, we passed on to ensemble assimilation techniques that transiently consider measurements as they become available – increasing the total information flow into glacier system models. The 3D modelling framework also allows a direct integration of iceberg calving, which is, on regional scales, an important but often unconsidered ice-loss term. Finally, we refined the representation of the local energy balance at the glacier surface improving the multi-decadal stability in the melt formulation.

The performance of the data assimilation was tested on synthetic glacier geometries. For real-world applications, convincing agreement was found against independent measurements. Meanwhile the approach is automated for regional application, ingests remote sensing observations between 2000-2020 and produces a digital representation of any glacier on this planet. This representation is created together with a distinct and associated uncertainty umbrella. The latter is highly valubale, considering the large spectrum of observational coverage and quality in various mountain regions. In summary, we are convinced that our framework will improve our capabilities to represent glacier systems when pursuing regional to global-scale simulations – especially in regional with limited in-situ measurements.

Abstract/Description

Empirical melt models based on the so-called degree-day method have been used for decades to model snow and ice melt within glacier mass balance models. They are easy to implement, require minimal data inputs, and showing usually good results. As such, these models have been used for climate impact projections on glaciers at the regional to global scale. However, these models rely heavily on calibration against observations, which calls into question their transferability and robustness under future climate conditions. Here we perform a ‘virtual world’ experiment by calibrating different empirical glacier melt models against mass balance simulated by a physically based (energy balance) models on Saskatchewan Glacier, Canada, for the period 1979-2010, and then test the transferability of the models against future mass-balance under different climate change scenarios. All empirical models show good performance during the calibration period, but different behaviour during the future climate periods. We find that all melt models suffer from strong parameter equifinality which hampers the unambiguous identification of model parameters. Calibrating on spatial observations (mass balance stakes) instead of on the mean glacier mass balance seems to reduce model equifinality and improve mass balance simulations under climate change scenarios. Our work highlights the challenges of using degree-day based models to project future glacier melt trajectories.