Ongoing global warming has resulted in a widespread retreat of glaciers since the end of the Little Ice Age, having important consequences for the society and the environment. There is a wide debate about the extent humans can be considered as responsible for the glacial retreat we observe nowadays. Over the 20th century the anthropogenic influence on the climate system has increased and according to a few global studies this signal has become a prevalent explanation for the observed decrease in glacier mass since the 1980s. These studies have however mainly investigated historical glacier changes with a focus on changes in glacier mass balance solely, whereas several studies have indicated that a relation between glacier dynamics and thinning rates exist. For this reason, the coupling between mass balance models and ice flow models with a sufficient representation of glacier dynamics is crucial.
Observed (OBS) and simulated (SIM) mean surface elevation change (A,B,E,F) and velocities (C,D,G,H) for the Langtang (A–D) and Hintereisferner (E–H) glaciers. Line 6 indicates the location of stone line 6 (Span et al., 1997). Source of the observed mean surface elevation change grids are Ragettli et al. (2016) for the Langtang Glacier and Klug et al. (2018) for the Hintereisferner.
A new study published (open access) in Frontiers in Earth Sciences led by René assesses the response of glaciers to natural and anthropogenic climate change from the end of the Little Ice Age (1850) to the present-day (2016). A coupled glacier mass balance and dynamical ice flow model was developed and applied to two glaciers with contrasting surface characteristics: the debris-covered Langtang Glacier (Nepal) and the clean-ice Hintereisferner (Austria). The model was forced with four climate models from the historical experiment of the CMIP5 archive, which represent region-specific warm-dry, warm-wet, cold-dry, and cold-wet climate conditions. To isolate the effects of anthropogenic climate change on glacier mass balance and dynamics runs are selected from the climate models with and without further anthropogenic forcing after 1970 until 2016.
Simulations showing changes in the geometry of Langtang Glacier and Hintereisferner between 1850 and 2010 under cold-wet and cold-dry anthropogenic climate conditions, respectively (Click for animation).
The findings of this study indicate that both glaciers experience the largest reduction in area and volume under warm climate conditions, and the simultaneously surface velocities generally decrease over time. Without further anthropogenic forcing the findings reveal a 3% (9%) smaller decline in glacier area (volume) for the debris-covered glacier and a 18% (39%) smaller decline in glacier area (volume) for the clean-ice glacier, which indicates that the response of the two glaciers can mainly be attributed to anthropogenic climate change. Here, the debris-covered glacier shows a limited retreat and tends to lose less mass due to insulation of the glacier surface by a layer of supraglacial debris, where the clean-ice glacier responds faster to climate change and shows a larger retreat.
A number of studies in our group have looked at debris-covered glaciers in recent years. What we have not really done yet is ask where the debris covering all that ice is actually coming from. In a new study, published recently in the Journal of Earth Surface Dynamics we are examining the contribution of sediment from the lateral moraines to the glacier surface.
Using repeat DEMs from multiple UAV flights between 2013 and 2018, we show that debris from the moraines can only reach the margins of the glacier surface but locally contributes to a considerable thickening of the cover.
The analysis shows that mass transport results in an elevation change on the lateral moraines with an average rate of +0.31m/year during this period, partly related to sub-moraine ice melt. There is a higher elevation change rate observed in the monsoon (+0.39 m/year) than in the dry season (+0.23 m/year).
The lower debris aprons of the lateral moraines decrease in elevation at a faster rate during both seasons, due to both the melt of ice below and mass wasting processes at the surface. The surface lowering rates of the upper gullied moraine, with no ice core below, translate into an annual increase in debris thickness of 0.08 m/year along a narrow margin of the glacier surface. Here the observed debris thickness is approximately 1 m, reducing melt rates of underlying glacier ice.
We recently published a new paper, led by Maxime Litt, providing guidelines for glacier-ablation modelling in HMA environments.
The conventional Temperature index (TI) models for modelling glacier ablation require few input variables and rely on simple empirical relations. The approach is assumed to be reliable at lower elevations (below 3500 m above sea level, a.s.l) where air temperature relates well to the energy inputs driving melt. Using field meteorological observation in Langtang and Khumbu, we show that temperature relates poorly to a number of important mass-loss drivers in high-altitude, so that temperature indexes have to be handled with care.
At the high elevation glaciers in Mountain Asia (HMA), we observed that incoming shortwave radiation is the dominant energy input and the full surface energy balance model relates only partly to daily mean air temperature. During monsoon surface melt dominates ablation processes at lower elevations (between 4950 and 5380 m a.s.l.). As net shortwave radiation is the main energy input at the glacier surface, albedo and cloudiness play key roles while being highly variable in space and time. For these cases only, ablation can be calculated with a TI model. Sublimation and other wind-driven ablation processes are important for mass loss, and remain unresolved with such simple methods. Ablation modeled with a SEB can diverge from the observations, but a suitable value for surface roughness can solve the issue.
Cumulated ablation calculated with the surface lowering measurements (thick blue line), with the surface energy balance for changing z0 values (orange dashed and continuous lines), with the TI (red line) and ETI (clear blue line) with one fixed set of factors. The hourly wind speed is shown upside down (green curve). Periods of surface melt (Ts = 0) are highlighted in orange. Results from Mera Glacier, 5380 m a.s.l in 2014 and 2017 (a) from Yala Glacier, 5350 m a.s.l., in 2014, 2016 (b) and Mera Glacier, 6352 m a.s.l, in 2015 and 2016 (c).
For her master thesis research Kari-Anne studied the sources of light-absorbing particles in the Langtang Valley in Nepal in the Himalaya. The study showed that most light-absorbing particles consisted of local material.
When light-absorbing particles (LAPs) deposit on a glacier surface, they decrease the albedo of ice and snow, resulting in increased melt. Glaciers in high mountain areas in the Himalya are influenced by this effect. Many studies assume that the main source of the LAPs is pollution, like black carbon (BC), from the Indo-Gangetic plain. However, this is uncertain. During this study, field work, microscopic analysis and (large-scale) remote sensing images were used to determine the main source of LAPs in the study area.
The results of the field work and the microscopic analysis showed that most LAPs consisted of natural sources like silicates and aluminosilicates. Only a few black carbon particles were present in the samples. The remote sensing images showed high concentrations of BC at the Indo-Gangetic plain but the concentrations for BC in the field work area were very low. These results make it very unlikely that high concentrations of LAPs at the Indo-Gangetic plain reached the study area during the field work period. Further research is needed to determine if LAP concentrations during other seasons are also dominated by local material.
The recent United Nations Climate Change Conference COP24 held in Katowice, Poland once more demonstrated the world’s climate change concerns. In the Indus, Ganges, and Brahmaputra river basins, a global climate change hotspot and home for about 900 million people, these concerns are pressing, since the river systems provide water resources for the important agricultural, domestic, and industrial sectors that serve these people. Melt water from glaciers and snow feed the headwaters of these rivers and are strongly influenced by rising temperatures. In addition, the monsoon and its dynamics, which determine the regional hydrology, are expected to change. Moreover, strong socio-economic developments and a rapid and continuous population growth will result in tremendous increases in water demand and cause pressure on water resources. It is therefore very likely that a water gap will develop in the future.
A new study published (open access) in Hydrology and Earth System Sciences led by René assesses the combined impacts of climate change and socio-economic developments on the future “blue” water gap in the Indus, Ganges, and Brahmaputra river basins until the end of the 21st century. In this joint effort by FutureWater, Utrecht University, Wageningen Environmental Research and ICIMOD a hydrological model that simulates future changes in the upstream water reserves (SPHY) is coupled with a hydrology and crop production model that simulates future changes in the downstream water balance (LPJmL). The models were forced with the latest climate change projections and socio-economic scenarios.
The findings of this study indicate that the surface water availability will increase, which can mainly be attributed to increases in monsoon precipitation. Besides the increases in surface water availability, water consumption by irrigation will most likely decline due to shorter growing seasons that emerge from temperature increases, and a shift from blue water irrigation to green water/rainfed irrigation due to increases in precipitation. However, this increase in water availability cannot outweigh the strong increases in water demand that are associated with the strong socio-economic development, and will thus likely lead to a substantial increase in the water gap with 7% and 14% in the Indus and Ganges river basins, respectively, during the 21st century. This implies the importance of robust adaptation strategies to cope with future water shortages in the region.
Maps showing the annual groundwater depletion for the reference period (a) and the projected changes in groundwater depletion for RCP4.5 (b), RCP8.5 (c), RCP4.5 – SSP1 (d), and RCP8.5 – SSP3 (e). The projected changes are given for the end of the 21st century. Green indicates less depletion and red indicate more depletion.