Prof. Dr. Daniel Farinotti

Glacier retreat presents significant environmental and social challenges. Understanding the local impacts of climatic drivers on glacier evolution is crucial, with mass balance being a central concept. This study introduces miniML-MB, a new minimal machine-learning model designed to estimate annual point surface mass balance (PMB) for very small datasets. Based on an eXtreme Gradient Boosting (XGBoost) architecture, miniML-MB is applied to model PMB at individual sites in the Swiss Alps, emphasising the need for an appropriate training framework and dimensionality reduction techniques. A substantial added value of miniML-MB is its data-driven identification of key climatic drivers of local mass balance. The best PMB prediction performance was achieved with two predictors: mean air temperature (May-August) and total precipitation (October-February). miniML-MB models PMB accurately from 1961 to 2021, with a mean absolute error (MAE) of 0.417 m w.e. across all sites. Notably, miniML-MB demonstrates similar and, in most cases, superior predictive capabilities compared to a simple positive degree-day (PDD) model (MAE of 0.541 m w.e.). Compared to the PDD model, miniML-MB is less effective at reproducing extreme mass balance values (e.g. 2022) that fall outside its training range. As such, miniML-MB shows promise as a gap-filling tool for sites with incomplete PMB measurements as long as the missing year's climate conditions are within the training range. This study underscores potential means for further refinement and broader applications of data-driven approaches in glaciology.

Glaciers are indicators of ongoing anthropogenic climate change¹. Their melting leads to increased local geohazards², and impacts marine³ and terrestrial^4,5 ecosystems, regional freshwater resources⁶, and both global water and energy cycles^7,8. Together with the Greenland and Antarctic ice sheets, glaciers are essential drivers of present^9,10 and future^{11, 12–13} sea-level rise. Previous assessments of global glacier mass changes have been hampered by spatial and temporal limitations and the heterogeneity of existing data series^{14, 15–16}. Here we show in an intercomparison exercise that glaciers worldwide lost 273 ± 16 gigatonnes in mass annually from 2000 to 2023, with an increase of 36 ± 10% from the first (2000–2011) to the second (2012–2023) half of the period. Since 2000, glaciers have lost between 2% and 39% of their ice regionally and about 5% globally. Glacier mass loss is about 18% larger than the loss from the Greenland Ice Sheet and more than twice that from the Antarctic Ice Sheet¹⁷. Our results arise from a scientific community effort to collect, homogenize, combine and analyse glacier mass changes from in situ and remote-sensing observations. Although our estimates are in agreement with findings from previous assessments^{14, 15–16} at a global scale, we found some large regional deviations owing to systematic differences among observation methods. Our results provide a refined baseline for better understanding observational differences and for calibrating model ensembles^12,16,18, which will help to narrow projection uncertainty for the twenty-first century^11,12,18.

Within scenario-based research of social-ecological systems, there has been a growing recognition of the importance of normative scenarios that define positive outcomes for both nature and society. While several frameworks exist to guide the co-creation of normative scenario narratives, examples of operationalizing these narratives in quantitative simulation modelling are still limited. To address this gap, this paper presents an example of how aspects of normative scenarios can be realized within a spatial model of land use and land cover change. This is achieved through a combination of data-driven approaches to encapsulate scenario-specific differences in local and global scale phenomena, as well as iterative expert elicitation to quantify descriptive trends from narratives. This approach is demonstrated with a case study simulating five scenarios of landscape change (three normative and two exploratory) in Switzerland between 2020 and 2060. The resulting maps of future land use and land cover exhibited distinct variations between the scenarios, notably with regard to the prevalence of areas of heterogeneous semi-natural land, such as alpine pastures and grassland, often considered culturally emblematic of Switzerland. While the simulation results were generally consistent with the outcomes expressed in the scenario narratives, following a process of expert feedback, we reflect that there are clear challenges in leveraging such results to elicit further discussions as to the desirability and plausibility of future scenarios. Specifically, the need to summarize spatial simulations in a manner that is easily interpretable and encourages consideration of the broader patterns of change rather than focusing on fine-scale details.

As climate warms, hydrology and geomorphology in glacierized catchments are evolving, changing sediment export from these catchments, thus impacting downstream ecosystems and communities. Currently, much uncertainty persists regarding interactions among geomorphic processes that evacuate sediment from glacierized catchments. Here, we present a catchment-scale numerical model of subglacial and proglacial sediment transport with debris meltout processes. We apply the model in a Monte Carlo framework to suspended sediment data collected over 2014–2020 from the Fieschertal catchment in the Swiss Alps, assessing possible combinations of geomorphic processes responsible for suspended sediment discharge. The ensemble of model outputs quantifies the interaction of different geomorphic processes, including the trade-off between bedrock erosion and sediment previously stored in the catchment. Model runs suggest that, at some periods, up to 20% of the sediment leaving the glacier is deposited in the proglacial area relative to the catchment's total sediment discharge. This shows that the model captures the proglacial area change from sediment source to sediment sink in different hydrological and glaciological conditions. Furthermore, the findings highlight the impact of glacier retreat on the catchment's sediment dynamics, which both reduces the proglacial area's slope and introduces additional sediment to the proglacial area through debris meltout. The model outputs and the parameters quantify the interaction among geomorphic processes, yielding key insights into the drivers of sediment transport in alpine regions. The implications of these interactions are discussed in the context of interpreting processes responsible for controlling erosion rates from glacierized regions and modeling sediment transport in glacierized catchments.

Mountain permafrost, constituting 30% of the global permafrost area, is sensitive to climate change and strongly impacts mountain ecosystems and communities. This study examines 21st century permafrost warming in European mountains using decadal ground temperature data from sixty-four boreholes in the Alps, Scandinavia, Iceland, Sierra Nevada and Svalbard. During 2013–2022, warming rates at 10 metres depth exceed 1 °C dec⁻¹ in cases, generally surpassing previous estimates because of accelerated warming and the use of a comprehensive data set. Substantial permafrost warming occurred at cold and ice-poor bedrock sites at high elevations and latitudes, at rates comparable to surface air temperature increase. In contrast, latent heat effects in ice-rich ground near 0 °C reduce warming rates and mask important changes of mountain permafrost substrates. The warming patterns observed are consistent across all sites, depths and time periods. For the coming decades, the propagation of permafrost warming to greater depths is largely predetermined already.

More than 60% of meteorite finds on Earth originate from Antarctica. Using a data-driven analysis that identifies meteorite-rich sites in Antarctica, we show climate warming causes many extraterrestrial rocks to be lost from the surface by melting into the ice sheet. At present, approximately 5,000 meteorites become inaccessible per year (versus ~1,000 finds per year) and, independent of the emissions scenario, ~24% will be lost by 2050, potentially rising to ∼76% by 2100 under a high-emissions scenario.

Projecting the global evolution of glaciers is crucial to quantify future sea-level rise and changes in glacierfed rivers. Recent intercomparison efforts have shown that a large part of the uncertainties in the projected glacier evolution is driven by the glacier model itself and by the data used for initial conditions and calibration. Here, we quantify the effect that mass balance observations, one of the most crucial data sources used in glacier modelling, have on glacier projections. For this, we model the 21st century global glacier evolution under Coupled Model Intercomparison Phase 6 project (CMIP6) climate scenarios with the Global Glacier Evolution Model (GloGEM) calibrated to match glacierspecific mass balance observations, as opposed to relying on regional mass balance observations. We find that the differences in modelled 21st century glacier changes can be large at the scale of individual glaciers (up to several tens of percent), but tend to average out at regional to global scales (a few percent at most). Our study thus indicates that the added value of relying on glacier-specific observations is at the subregional and local scale, which will increasingly allow projecting the glacier-specific evolution and local impacts for every individual glacier on Earth. To increase the ensemble of models that project global glacier evolution under CMIP6 scenarios, simulations are also performed with the Open Global Glacier Model (OGGM). We project the 2015- 2100 global glacier loss to vary between 25_15% (Glo- GEM) and 29_14%(OGGM) under SSP1-2.6 to 46_26% and 54_29% under SSP5-8.5 (ensemble median, with 95% confidence interval; calibration with glacier-specific observations). Despite some differences at the regional scale and a slightly more pronounced sensitivity to changing climatic conditions, our results agree well with the recent projections by Rounce et al. (2023), thereby projecting, for any emission scenario, a higher 21st century mass loss than the current community estimate from the second phase of the Glacier Model Intercomparison Project (GlacierMIP2)..

Developing renewable energy is crucial for achieving China's carbon neutrality target by 2060. Xizang has a large renewable energy potential, especially hydropower potential, and it could become an important source of clean energy. Meanwhile, climate change has been affecting and will significantly alter hydropower resources in Xizang. This study estimates the development of Xizang's power system and its role in the national power supply under China's carbon neutrality target. In particular, it considers the changes in theoretically available hydropower potential from glacial retreat and transmission-supporting policies. The results show that considering the hydropower potential changes from glacier retreat under climate change, an additional 5.7–6.8 GW of hydropower capacity could be developed in Xizang by 2060, concentrated in Linzhi and Naqu areas. This additional hydropower capacity could increase to 15.9–17.7 GW if transmission subsidies are provided. Under such a scenario, Xizang could export renewable electricity to other provinces for up to about 3 % of the national electricity demand by 2060. The results indicate the importance of considering the impacts of climate change in power system planning and implementing transmission-supporting policies, which could facilitate Xizang to become a renewable energy base for China.

The mountain cryosphere and groundwater play pivotal roles in shaping the hydrological cycle, yet their connectivity remains incompletely understood. Current knowledge on meltwater recharge and consequent groundwater discharge processes is better developed for snow–groundwater connectivity than for glacier–groundwater connectivity. Estimates of meltwater recharge vary considerably, which is probably a function of not only inherent catchment characteristics but also of the different spatio-temporal scales involved and the uncertainties in the methods used. This hinders a comprehensive understanding of the mountain water cycle. As glaciers retreat, permafrost thaws and snowpack diminishes, the relative importance of mountain groundwater is expected to increase. However, shifting and declining recharge from the cryosphere may decrease absolute groundwater amounts and fluxes with as-yet unknown effects on catchment-scale hydrological processes. We therefore stress the need to better quantify mountain cryosphere–groundwater connectivity to predict climate change impacts on mountain water supply and to support sustainable water resource management of downstream socio-ecological systems.

Accelerating glacier melt rates were observed during the last decades. Substantial ice loss occurs particularly during heat waves that are expected to intensify in the future. Because measuring and modelling glacier mass balance on a daily scale remains challenging, short-term mass balance variations, including extreme melt events, are poorly captured. Here, we present a novel approach based on computer-vision techniques for automatically determining daily mass balance variations at the local scale. The approach is based on the automated recognition of colour-taped ablation stakes from camera images and is tested and validated at six stations installed on three Alpine glaciers during the summers of 2019-2022. Our approach produces daily mass balance with an uncertainty of ±0.81 cm w.e. d-1, which is about half of the accuracy obtained from visual readouts. The automatically retrieved daily mass balances at the six sites were compared to average daily mass balances over the last decade derived from seasonal in situ observations to detect and assess extreme melt events. This allows analysing the impact that the summer heat waves which occurred in 2022 had on glacier melt. Our results indicate 23 d with extreme melt, showing a strong correspondence between the heat wave periods and extreme melt events. The combination of below-average winter snowfall and a suite of summer heat waves led to unprecedented glacier mass loss. The Switzerland-wide glacier storage change during the 25 d of heat waves in 2022 is estimated as 1.27 ± 0.10 km3 of water, corresponding to 35 % of the overall glacier mass loss during that summer. The same 25 d of heat waves caused a glacier mass loss that corresponds to 56 % of the average mass loss experienced over the entire melt season during the summers 2010-2020, demonstrating the relevance of heat waves for seasonal melt.

Ground penetrating radar (GPR) has been extensively used in glaciology to infer glacier's ice thickness, liquid water content, water drainage pathways, and other properties. The interpretation of such GPR data is not always straightforward and for temperate glaciers, the signal is often affected by strong scattering and attenuation. It has often been suggested that such effects originate from englacial water inclusions, since water and ice have a large contrast in their di-electric permittivity. To investigate such effects quantitatively, we perform an extensive numerical modeling study of GPR signals. By exploring how different liquid water contents (LWC) and water-inclusions size affect the GPR signal, we show that their effects are much larger than the potential presence of a wet snowpack or a heterogeneous distribution of ice permittivity. In particularly, we show that the presence of such water inclusions is a necessary and sufficient condition for reproducing the typical characteristics of GPR data acquired in the field. Further, we find that for 25 MHz GPR antennas, a bulk LWC ≳ 0.2%, associated with decimeters-scale water inclusions already limits bedrock detectability for ice thicknesses ≳ 100 m. Since these values are typical for Alpine glaciers, they clarify why the quality of GPR data is often poor in such environments.

Glacier mass loss affects sea level rise, water resources, and natural hazards. We present global glacier projections, excluding the ice sheets, for shared socioeconomic pathways calibrated with data for each glacier. Glaciers are projected to lose 26 ± 6% (+1.5°C) to 41 ± 11% (+4°C) of their mass by 2100, relative to 2015, for global temperature change scenarios. This corresponds to 90 ± 26 to 154 ± 44 millimeters sea level equivalent and will cause 49 ± 9 to 83 ± 7% of glaciers to disappear. Mass loss is linearly related to temperature increase and thus reductions in temperature increase reduce mass loss. Based on climate pledges from the Conference of the Parties (COP26), global mean temperature is projected to increase by +2.7°C, which would lead to a sea level contribution of 115 ± 40 millimeters and cause widespread deglaciation in most mid-latitude regions by 2100.

Intensifying droughts under climatic warming are of widespread concern owing to their devastating impacts on water resources, societies and ecosystems. However, the effects of exogeneous drivers on regional droughts remain poorly understood. Using the Lagrangian method, atmospheric reanalysis data and climate projections from the Coupled Model Inter-comparison Project phase 6 (CMIP6), we show how exogenous precipitation minus evaporation (PME) deficit drives droughts across China. More specifically, we demonstrate that four distinct trajectories of such exogenous PME deficit fuel regional droughts. Three of these trajectories relate to oceanic PME deficit originating from the North Atlantic, eastern Bering Sea and Indian Ocean, and one trajectory characterizes exogenous terrestrial PME deficit from the Siberian Plateau. We show that during 1980–2020, droughts induced by exogenous PME deficit account for 45% of all droughts that occurred in China’s coastal region, and for 7% of all droughts in the northwestern regions. Under climate scenario SSP245 (SSP585), limiting warming to 1.5 °C compared to 2 °C above pre-industrial levels could avoid 60% (84%) of exogenous drought exposure. This would in turn reduce population exposure by 40% (49%), and economic exposure by 73% (66%). Our study unravels how exogenous PME deficit drives droughts in China, underscoring the role that external drivers have on regional droughts and associated future prediction.

Water resources sustainability in High Mountain Asia (HMA) surrounding the Tibetan Plateau (TP)—known as Asia’s water tower—has triggered widespread concerns because HMA protects millions of people against water stress. However, the mechanisms behind the heterogeneous trends observed in terrestrial water storage (TWS) over the TP remain poorly understood. Here we use a Lagrangian particle dispersion model and satellite observations to attribute about 1 Gt of monthly TWS decline in the southern TP during 2003–2016 to westerlies-carried deficit in precipitation minus evaporation (PME) from the southeast North Atlantic. We further show that HMA blocks the propagation of PME deficit into the central TP, causing a monthly TWS increase by about 0.5 Gt. Furthermore, warming-induced snow and glacial melt as well as drying-induced TWS depletion in HMA weaken the blocking of HMA’s mountains, causing persistent northward expansion of the TP’s TWS deficit since 2009. Future projections under two emissions scenarios verified by satellite observations during 2020–2021 indicate that, by the end of the twenty-first century, up to 84% (for scenario SSP245) and 97% (for scenario SSP585) of the TP could be afflicted by TWS deficits. Our findings indicate a trajectory towards unsustainable water systems in HMA that could exacerbate downstream water stress.

Glaciers around the world are shrinking rapidly and will continue to do so in the next decades. Anticipating the consequences resulting from such glacier changes is key to design and implement adequate mitigation measures. Here, we focus on the future evolution of potential ice-dammed and supraglacial lakes in High Mountain Asia, as such lakes are responsible for the majority of glacier lake outburst floods in the region. We identify 11,129 potential lakes at present, with a total maximum volume of 2070 million m³. We find a strong correlation between large modelled lakes and historical outburst floods. By accounting for the evolution of glaciers under different climate change mitigation measures, we project that the number of potential ice-dammed lakes could increase by between 15 and 18% until 2080, with a concomitant 45–55% increase in their volume. Our findings thus suggest that a temporary increase of glacier lake outburst floods is to be expected in the coming decades.

Currently, about 12 %–13 % of High Mountain Asia’s glacier area is debris-covered, which alters its surface mass balance. However, in regional-scale modelling approaches, debris-covered glaciers are typically treated as clean-ice glaciers, leading to a bias when modelling their future evolution. Here, we present a new approach for modelling debris area and thickness evolution, applicable from single glaciers to the global scale. We derive a parameterization and implement it as a module into the Global Glacier Evolution Model (GloGEMflow), a combined mass-balance ice-flow model. The module is initialized with both glacier-specific observations of the debris' spatial distribution and estimates of debris thickness. These data sets account for the fact that debris can either enhance or reduce surface melt depending on thickness. Our model approach also enables representing the spatiotemporal evolution of debris extent and thickness. We calibrate and evaluate the module on a selected subset of glaciers and apply GloGEMflow using different climate scenarios to project the future evolution of all glaciers in High Mountain Asia until 2100. Explicitly accounting for debris cover has only a minor effect on the projected mass loss, which is in line with previous projections. Despite this small effect, we argue that the improved process representation is of added value when aiming at capturing intra-glacier scales, i.e. spatial mass-balance distribution. Depending on the climate scenario, the mean debris-cover fraction is expected to increase, while mean debris thickness is projected to show only minor changes, although large local thickening is expected. To isolate the influence of explicitly accounting for supraglacial debris cover, we re-compute glacier evolution without the debris-cover module. We show that glacier geometry, area, volume, and flow velocity evolve differently, especially at the level of individual glaciers. This highlights the importance of accounting for debris cover and its spatiotemporal evolution when projecting future glacier changes.

Glacier monitoring in Switzerland has resulted in some of the longest and most complete data series globally. Mass balance observations at individual locations, starting in the 19th century, are the backbone of the monitoring as they represent the raw and original glaciological data demonstrating the response of snow accumulation and snow/ice melt to changes in climate forcing. So far, however, the variety of sources of historic measurements has not been systematically processed and documented. Here, we present a new complete and extensive point glacier mass balance dataset for the Swiss Alps that provides attributes for data quality and corresponding uncertainties. Original sources were digitized or re-assessed to validate or to correct existing entries and to identify metadata. The sources of data are highly diverse and stem from almost 140 years of records, originating from handwritten field notes, unpublished project documents, various digital sources, published reports, and meta-knowledge of the observers. The project resulted in data series with metadata for 63 individual Swiss glaciers, including more than 60000 point observations of mass balance. Data were systematically analysed and homogenized, e.g. by supplementing partly missing information based on correlations inferred from direct measurements. A system to estimate uncertainty in all individual observations was developed indicating that annual point balance is measured with a typical error of 0.07m water equivalent (w.e.), while the average error in winter snow measurements is 0.20mw.e. Our dataset permits further investigating the climate change impacts on Swiss glaciers. Results show an absence of long-term trends in snow accumulation over glaciers while melt rates have substantially increased over the last 3 decades. The complete dataset is available at DOI 10.18750/massbalance.point.2021.r2021 (GLAMOS, 2021).

The monitoring of Earth's and planetary surface elevations at larger and finer scales is rapidly progressing through the increasing availability and resolution of digital elevation models (DEMs). Surface elevation observations are being used across an expanding range of fields to study topographical attributes and their changes over time, notably in glaciology, hydrology, volcanology, seismology, forestry, and geomorphology. However, DEMs frequently contain large-scale instrument noise and varying vertical precision that lead to complex patterns of errors. Here, we present a validated statistical workflow to estimate, model, and propagate uncertainties in DEMs. We review the state-of-the-art of DEM accuracy and precision analyses, and define a conceptual framework to consistently address those. We show how to characterize DEM precision by quantifying the heteroscedasticity of elevation measurements, i.e., varying vertical precision with terrain- or sensor-dependent variables, and the spatial correlation of errors that can occur across multiple spatial scales. With the increasing availability of high-precision observations, our workflow based on independent elevation data acquired on stable terrain can be applied almost anywhere on Earth. We illustrate how to propagate uncertainties for both pixel-scale and spatial elevation derivatives, using terrain slope and glacier volume changes as examples. We find that uncertainties in DEMs are largely underestimated in the literature, and advocate that new metrics of DEM precision are essential to ensure the reliability of future land elevation assessments.

Accumulating evidence suggests that glacier basal motion can produce seismogenic stick-slip events caused by frictional resistance at the ice-bed interface. Frequent and subsequent failure of multiple stick-slip patches may constitute sliding tremor in seismic recordings. We show that during stick-slip tremor at the base of an Alpine glacier, the released seismic moment increases by an order of magnitude. The tremor emerges during melt-intensive days and is associated with water pressure peaks in a nearby subglacial channel. We propose an extended slider-block model that explains the regular occurrence of stick-slip tremor by coupling seismically sliding patches to surrounding aseismically sliding bed regions. The model predicts that the stick-slip patches control the movement of their surrounding smoothly sliding bed regions via elastic coupling and stress transfer. Thus, tremor producing stick-slip patches could affect large-scale ice flow to a degree, which is underestimated in models, with implications on sea level rise projections.