Surface Mass Balance Model Research Articles

Surface mass balance modelling of the Juneau Icefield highlights the potential for rapid ice loss by the mid-21st century

Surface mass balance modelling of the Juneau Icefield highlights the potential for rapid ice loss by the mid-21st century

Mitigation of black carbon emissions could immediately reduce 6.3% of glacier melting in the Qilian Mountains

Global warming in tandem with surface albedo reduction caused by black carbon (BC) deposition on glaciers accelerated glacier melting; however, their respective contributions remain unclear. Glaciers in the Qilian Mountains are crucial for the development of oases in the Hexi Corridor; however, their area has decreased by more than 20% over the past half-century. Thus, this study developed a dynamic deposition model for light-absorbing particles (LAPs), coupled with a surface energy and mass balance model. We comprehensively assessed the effects of BC and warming on the melting of a typical glacier in the Qilian Mountains based on the coupled model. BC on the glacier surface caused 13.1% of annual glacier-wide melting, of which directly deposited atmospheric BC reduced the surface albedo by 0.02 and accounted for 9.1% of glacier melting. The air temperature during 2000–2010 has increased by 1.5 °C relative to that during the 1950s, accounting for 51.9% of current glacier melting. Meanwhile, BC emission have increased by 4.6 times compared to those of the early Industrial Revolution recorded in an ice core, accounting conservatively for 6.3% of current glacier melting. Mitigating BC emissions has a limited influence on current glacier melting; however, in the long-term, mitigation should exert a noteworthy impact on glacier melting through the self-purification of glaciers.

Analysis of gap filling techniques for GRACE/GRACE-FO terrestrial water storage anomalies in Canada

Terrestrial water storage anomaly (TWSA) data derived from the Gravity Recovery and Climate Experiment (GRACE/GRACE-FO) have become indispensable for hydrological monitoring since the first mission launched in 2002. Evaluation of basin dynamics is enabled through TWSA integration with independent hydrological and climate datasets such as precipitation, evapotranspiration, and surface runoff. With over 20 years of observations, long-term statistical analysis reveals water storage trends, provided the 11-month gap between the two missions is filled. This study compares four methods for reconstructing GRACE-like TWSA over Canada, namely: extreme gradient boosting, artificial neural networks, automated machine learning, and projection onto convex sets. The GRACE mascon product released by the Jet Propulsion Laboratory is used over the study region. Nine sets of hydrological and climate parameters are used as predictors for the machine learning models, namely GRACE average seasonal signals, TWSA from the GLDAS Catchment Land Surface Model, precipitation, air temperature, glacier surface mass balance, ocean tides, the North Atlantic Oscillation, the Multivariate ENSO Index, and sea surface temperature. For each of the four methods, 20 % of the GRACE TWSA data (the ‘testing data’) is omitted from the model training, and the model is used to fill the artificial gap. Root mean square error (RMSE) is computed using the difference between testing data and model predictions. Normalized RMSE expresses the RMSE as a proportion of the range of the GRACE TWSA data. The automated machine learning algorithm performs best in terms of mean normalized root mean square error, with 6 % (2.4 cm equivalent water height RMSE), followed by projection onto convex sets, extreme gradient boosting, and artificial neural networks. Inclusion of glacier surface mass balance models derived from the GMAO Modern-Era Retrospective Analysis for Research and Applications Version 2 reanalysis and the Randolph Glacier Inventory improved the automated machine learning average root mean square error by 70 %. Results indicate that filling the gap between missions allows for more comprehensive analysis of terrestrial water storage changes, including basin-by-basin analysis, which is ongoing.

Universal differential equations for glacier ice flow modelling

Abstract. Geoscientific models are facing increasing challenges to exploit growing datasets coming from remote sensing. Universal differential equations (UDEs), aided by differentiable programming, provide a new scientific modelling paradigm enabling both complex functional inversions to potentially discover new physical laws and data assimilation from heterogeneous and sparse observations. We demonstrate an application of UDEs as a proof of concept to learn the creep component of ice flow, i.e. a nonlinear diffusivity differential equation, of a glacier evolution model. By combining a mechanistic model based on a two-dimensional shallow-ice approximation partial differential equation with an embedded neural network, i.e. a UDE, we can learn parts of an equation as nonlinear functions that then can be translated into mathematical expressions. We implemented this modelling framework as ODINN.jl, a package in the Julia programming language, providing high performance, source-to-source automatic differentiation (AD) and seamless integration with tools and global datasets from the Open Global Glacier Model in Python. We demonstrate this concept for 17 different glaciers around the world, for which we successfully recover a prescribed artificial law describing ice creep variability by solving ∼ 500 000 ordinary differential equations in parallel. Furthermore, we investigate which are the best tools in the scientific machine learning ecosystem in Julia to differentiate and optimize large nonlinear diffusivity UDEs. This study represents a proof of concept for a new modelling framework aiming at discovering empirical laws for large-scale glacier processes, such as the variability in ice creep and basal sliding for ice flow, and new hybrid surface mass balance models.

New proglacial meteorology and river stage observations from Inglefield Land and Pituffik, NW Greenland

Abstract. Meltwater runoff from the Greenland ice sheet (GrIS) is an important contributor to global sea level rise, but substantial uncertainty exists in its measurement and prediction. Common approaches for estimating ice sheet runoff are in situ gauging of proglacial rivers draining the ice sheet and surface mass balance (SMB) modeling. To obtain hydrological and meteorological data sets suitable for both runoff stage characterization and, pending the establishment of stage–discharge curves, SMB model evaluation, we established an automated weather station (AWS) and a cluster of traditional and experimental river stage sensors on the Minturn River, the largest proglacial river draining Inglefield Land, NW Greenland. Secondary installations measuring river stage were installed in the Fox Canyon River and North River at Pituffik Space Base, NW Greenland. Proglacial runoff at these sites is dominated by supraglacial processes only, uniquely advantaging them for SMB studies. The three installations provide rare hydrological time series and an opportunity to evaluate experimental measurements of river stage from a harsh, little-studied polar region. The installed instruments include submerged vented and non-vented pressure transducers, a bubbler sensor, experimental bank-mounted laser rangefinders, and time-lapse cameras. The first 3 years of observations (2019 to 2021) from these stations indicate (a) a meltwater runoff season from late June to late August/early September that is roughly synchronous throughout the region; (b) the early onset (∼ 23 June to 8 July) of a strong diurnal runoff signal in 2019 and 2020, suggesting minimal meltwater storage in snow and/or firn; (c) 1 d lagged air temperature that displays the strongest correlation with river stage; (d) river stage that correlates more strongly with ablation zone albedo than with net radiation; and (e) the late-summer rain-on-ice events appear to trigger the region's sharpest and largest floods. The new gauging stations provide valuable in situ hydrological observations that are freely available through the PROMICE network (https://promice.org/weather-stations/, last access: 14 September 2023).

Widespread slowdown in thinning rates of West Antarctic ice shelves

Abstract. Antarctica's floating ice shelves modulate discharge of grounded ice into the ocean by providing a backstress. Ice shelf thinning and grounding line retreat have reduced this backstress, driving rapid drawdown of key unstable areas of the Antarctic Ice Sheet, leading to sea-level rise. If ice shelf loss continues, it may initiate irreversible glacier retreat through the marine ice sheet instability. Identification of areas undergoing significant change requires knowledge of spatial and temporal patterns in recent ice shelf loss. We used 26 years (1992–2017) of satellite-derived Antarctic ice shelf thickness, flow, and basal melt rates to construct a time-dependent dataset of ice shelf thickness and basal melt on a 3 km grid every 3 months. We used a novel data fusion approach, state-of-the-art satellite-derived velocities, and a new surface mass balance model. Our data revealed an overall pattern of thinning all around Antarctica, with a thinning slowdown starting around 2008 widespread across the Amundsen, Bellingshausen, and Wilkes sectors. We attribute this slowdown partly to modulation in external ocean forcing, altered in West Antarctica by negative feedbacks between ice shelf thinning rates and grounded ice flow, and sub-ice-shelf cavity geometry and basal melting. In agreement with earlier studies, the highest rates of ice shelf thinning are found for those ice shelves located in the Amundsen and Bellingshausen sectors. Our study reveals that over the 1992–2017 observational period the Amundsen and Bellingshausen ice shelves experienced a slight reduction in rates of basal melting, suggesting that high rates of thinning are largely a response to changes in ocean conditions that predate our satellite altimetry record, with shorter-term variability only resulting in small deviations from the long-term trend. Our work demonstrates that causal inference drawn from ice shelf thinning and basal melt rates must take into account complex feedbacks between thinning and ice advection and between ice shelf draft and basal melt rates.

Everest South Col Glacier did not thin during the period 1984–2017

Abstract. The South Col Glacier is a small body of ice and snow (approx. 0.2 km2) located at the very high elevation of 8000 m a.s.l. (above sea level) on the southern ridge of Mt. Everest. A recent study by Potocki et al. (2022) proposed that South Col Glacier is rapidly losing mass. This is in contradiction to our comparison of two digital elevation models derived from aerial photographs taken in December 1984 and a stereo Pléiades satellite acquisition from March 2017, from which we estimate a mean elevation change of 0.01 ± 0.05 m a−1. To reconcile these results, we investigate some aspects of the surface energy and mass balance of South Col Glacier. From satellite images and a simple model of snow compaction and erosion, we show that wind erosion has a major impact on the surface mass balance due to the strong seasonality in precipitation and wind and that it cannot be neglected. Additionally, we show that the melt amount predicted by a surface energy and mass balance model is very sensitive to the model structure and implementation. Contrary to previous findings, melt is likely not a dominant ablation process on this glacier, which remains mostly snow-covered during the monsoon.

Strategies for regional modeling of surface mass balance at the Monte Sarmiento Massif, Tierra del Fuego

Abstract. This study investigates strategies for calibration of surface mass balance (SMB) models in the Monte Sarmiento Massif (MSM), Tierra del Fuego, with the goal of achieving realistic simulations of the regional SMB. Applied calibration strategies range from a local single-glacier calibration to a regional calibration with the inclusion of a snowdrift parameterization. We apply four SMB models of different complexity. In this way, we examine the model transferability in space, the benefit of regional mass change observations and the advantage of increasing the complexity level regarding included processes. Measurements include ablation and ice thickness observations at Schiaparelli Glacier as well as elevation changes and flow velocity from satellite data for the entire study site. Performance of simulated SMB is validated against geodetic mass changes and stake observations of surface melting. Results show that transferring SMB models in space is a challenge, and common practices can produce distinctly biased estimates. Model performance can be significantly improved by the use of remotely sensed regional observations. Furthermore, we have shown that snowdrift does play an important role in the SMB in the Cordillera Darwin, where strong and consistent winds prevail. The massif-wide average annual SMB between 2000 and 2022 falls between −0.28 and −0.07 m w.e. yr−1, depending on the applied model. The SMB is mainly controlled by surface melting and snowfall. The model intercomparison does not indicate one obviously best-suited model for SMB simulations in the MSM.

Glaciers Variation at ‘Shocking’ Pace in the Northeastern Margin of Tibetan Plateau from 1957 to 21st Century: A Case Study of Qiyi Glacier

Accelerating glacier shrinkage is one of the most consequential of global warming. Yet, projections for the region remain ambiguous because of the tremendous spatial heterogeneity, especially in the Qilian Mountains, where glacier melt runoff is a vital water resource for the arid downstream area. To better understand glacier changes in this region, this study took regional representative Qiyi Glacier as an example and applied an enhanced distributed surface mass balance (SMB) model to glimpse the SMB variation and possible impacts on melt runoff under the RCP 4.5 and RCP 8.5 scenarios. Further, we combined a modified volume-scaling method to update the glacier geometry gradually to enhance long-term reliability. When forced with observed daily temperature and precipitation, the reconstructed glacier SMB, from 1957 through 2013, agrees well with the in situ observations. The result indicates an abrupt change for SMB from positive to negative in 1992 and subsequent mass accelerated loss after 2000. The increased summer air temperature and the pattern of large-scale atmospheric circulation shifts might both cause these changes. Using projected climate forcing from as many as 31 coupled GCMs from the CMIP 5 ensemble, the Qiyi Glacier is projected to undergo sustained SMB loss throughout the 21st century for both RCPs. By 2100, the Qiyi Glacier will lose ~25 m water equivalent (w.e.) for RCP 4.5 and ~37 m w.e. for RCP 8.5. Whereas the glacier area will shrink by 43% for RCP 4.5 and 54% for RCP 8.5 relative to 2013 glacier content, corresponding to the volume of the Qiyi Glacier will lose by 54% for RCP 4.5 and by 65% for RCP 8.5, accordingly. Simultaneously, the glacier terminus will experience extreme melts. The terminus elevation of the Qiyi Glacier will retreat from 4310 m a.s.l. in 2013 to 4810 m a.s.l. (RCP 4.5) and 4838 m a.s.l. (RCP 8.5) by the end of 2100, which will exceed the multi-year average ELA (4749 m) from 1957 to 2013. If the warming trends keep and glaciers melt like the Qiyi Glacier with this ‘shocking’ rate, it will raise the possibility of crippling, long-term water shortages for Hexi corridors.

Insights from the first winter weather observations near Mount Everest's summit

Insights from the first winter weather observations near Mount Everest's summit

Climatic control of the surface mass balance of the Patagonian Icefields

Abstract. The Patagonian Icefields (Northern and Southern Patagonian Icefield) are the largest ice masses in the Andes Cordillera. Despite its importance, little is known about the main mechanisms that underpin the interaction between these ice masses and climate. Furthermore, the nature of large-scale climatic control over the surface mass variations of the Patagonian Icefields still remains unclear. The main aim of this study is to understand the present-day climatic control of the surface mass balance (SMB) of the Patagonian Icefields at interannual timescales, especially considering large-scale processes. We modeled the present-day (1980–2015) glacioclimatic surface conditions for the southern Andes Cordillera by statistically downscaling the output from a regional climate model (RegCMv4) from a 10 km spatial resolution to a 450 m resolution grid and then using the downscaled fields as input for a simplified SMB model. Series of spatially averaged modeled fields over the Patagonian Icefields were used to derive regression and correlation maps against fields of climate variables from the ERA-Interim reanalysis. Years of relatively high SMB are associated with the establishment of an anomalous low-pressure center near the Drake Passage, the Drake low, that induces an anomalous cyclonic circulation accompanied with enhanced westerlies impinging on the Patagonian Icefields, which in turn leads to increases in the precipitation and the accumulation over the icefields. Also, the Drake low is thermodynamically maintained by a core of cold air that tends to reduce the ablation. Years of relatively low SMB are associated with the opposite conditions. We found low dependence of the SMB on main atmospheric modes of variability (El Niño–Southern Oscillation, Southern Annular Mode), revealing a poor ability of the associated indices to reproduce the interannual variability of the SMB. Instead, this study highlights the Drake Passage as a key region that has the potential to influence the SMB variability of the Patagonian Icefields.

Evaluating Greenland surface-mass-balance and firn-densification data using ICESat-2 altimetry

Abstract. Surface-mass-balance (SMB) and firn-densification (FD) models are widely used in altimetry studies as a tool to separate atmospheric-driven from ice-dynamics-driven ice-sheet mass changes and to partition observed volume changes into ice-mass changes and firn-air-content changes. Until now, SMB models have been principally validated based on comparison with ice core and weather station data or comparison with widely separated flight radar-survey flight lines. Firn-densification models have been primarily validated based on their ability to match net densification over decades, as recorded in firn cores, and the short-term time-dependent component of densification has rarely been evaluated at all. The advent of systematic ice-sheet-wide repeated ice-surface-height measurements from ICESat-2 (the Ice Cloud, and land Elevation Satellite, 2) allows us to measure the net surface-height change of the Greenland ice sheet at quarterly resolution and compare the measured surface-height differences directly with those predicted by three FD–SMB models: MARv3.5.11 (Modèle Atmosphérique Régional version 3.5.11) and GSFCv1.1 and GSFCv1.2 (the Goddard Space Flight Center FD–SMB models version 1.1 and 1.2). By segregating the data by season and elevation, and based on the timing and magnitude of modelled processes in areas where we expect minimal ice-dynamics-driven height changes, we investigate the models' accuracy in predicting atmospherically driven height changes. We find that while all three models do well in predicting the large seasonal changes in the low-elevation parts of the ice sheet where melt rates are highest, two of the models (MARv3.5.11 and GSFCv1.1) systematically overpredict, by around a factor of 2, the magnitude of height changes in the high-elevation parts of the ice sheet, particularly those associated with melt events. This overprediction seems to be associated with the melt sensitivity of the models in the high-elevation part of the ice sheet. The third model, GSFCv1.2, which has an updated high-elevation melt parameterization, avoids this overprediction.

Summertime surface mass balance and energy balance of Urumqi Glacier No. 1, Chinese Tien Shan, modeled by linking COSIMA and in-situ measured meteorological records

To get a better overview of atmosphere-driven mass changes at Urumqi Glacier No.1, Chinese Tien Shan, the surface energy budget and mass balance is modeled by linking the COupled Snowpack and Ice surface energy and MAss balance model (COSIMA) with in-situ measured meteorological records for the ablation period in 2018. The COSIMA is calibrated by manual optimization and the modeled results agree well with the in-situ surface temperature, snow height and seasonal mass balance. Our results reveal that Urumqi Glacier No.1 experienced a significant mass loss, with an average value of − 0.77 m w.e. over the ablation period 2018. The surface energy budget components can be classified into two categories: radiation (shortwave and longwave) and turbulent fluxes. Surface melt and solid precipitation were dominated components of mass balance. The COSIMA can reproduce the glaciological mass balance compared with other models. Sensitivity analysis showed that the mass balance was more sensitive to the temperature than precipitation, and mass loss caused by temperature increase of 1 K needed to be compensated by at least 40% precipitation increase. Air temperature during the ablation period was more important than annual precipitation in controlling mass balance changes on Urumqi Glacier No. 1. These findings will enhance our understanding of the mechanisms underlying mass balance processes of ablation period and their contribution to the acceleration of glacier retreat in Tien Shan.

Energy and glacier mass balance of Fürkeleferner, Italy: past, present, and future

The energy and mass balance of mountain glaciers translate into volume changes that play out as area changes over time. From this, together with former moraines during maximum advances, information on past climate conditions and the climatic drivers behind during glacier advances can be obtained. Here, we use the distributed COupled Snowpack and Ice surface energy and mass balance model in PYthon (COSIPY) to simulate the present state of an Italian glacier, named Fürkeleferner, for the mass balance years 2013–2017. Next, we investigate the local climate during the time of the last “Little Ice Age” (LIA) maximum glacier advance using COSIPY together with the LIA glacier outline retrieved from moraine mapping and a digital elevation model (DEM) adapted for the glacier’s geometry at the time of the LIA as a benchmark. Furthermore, the glacier’s sensitivity to future air temperature increase of +1 K and +2 K is investigated using the same model. For all simulations, meteorological data of closely located climate stations are used to force the model. We show the individual monthly contribution of individual energy and mass balance components. Refreezing during the summer months is an important component of the energy and mass balance, on average about 9 % relative to total annual ablation. The results from simulating past climate show a 2.8 times larger glacier area for Fürkeleferner during the LIA than today. This further implies a 2.5 K colder climate, assuming that the amount of precipitation was 10 %–20 % in excess of today’s value. Concerning further temperature increase of 2 K, the glacier would only consist of the ablation area implying sustained mass loss and eventual total mass loss. Even under current climatic conditions, the glacier area would have to decrease to 17 % of its current area to be in a steady state. We discuss the reliability of the results by comparing simulated present mass balance to measured mass balances of neighboring glaciers in the European Alps and with short-term measurements on Fürkeleferner itself. In conclusion, we are able to show how the glacier responds to past and future climate change and determine the climatic drivers behind.

Dust dominates the summer melting of glacier ablation zones on the northeastern Tibetan Plateau

Dust and black carbon (BC) can darken snow and ice surface and play pivotal roles in glacier mass loss. Thus, a quantitative assessment of their contributions to glacier summer melting is critical. During the summer of 2018, surface snow and ice were sampled, and the albedo and mass balance were continuously measured in the ablation zone of Laohugou Glacier No. 12 in the western Qilian Mountains. The physical properties of dust and BC were measured in the laboratory, and their impacts on glacier surface albedo reduction and melting were simulated. The results indicate that the ice surface in the ablation zone was enriched with substantial amounts of particles, and the average particle concentrations of these samples were hundreds of times higher than those of fresh snow. The BC mass absorption cross-sections (MACs) ranged from 3.1 m2 g−1 at 550 nm for dirty ice to 4.6 m2 g−1 for fresh snow, largely owing to meltwater percolation and particle collapse. The spectral variations in dust MACs were significantly different in the visible light bands and near-infrared bands from those in the other areas. Moreover, the two-layer surface energy and mass balance model with the new albedo parameterization formula was validated and agreed well with the experimental measurements of spectral albedo, broadband albedo, and mass balance. BC and dust combined resulted in 26.7 % and 54.4 % of the total mass loss on the cleaner and dirtier (particle enriched) surfaces in the ablation zone, respectively, compared to particle-free surfaces, and although both impurities played vital roles, dust was the more prominent factor in accelerating glacier melting on the northeastern Tibetan Plateau. This study emphasizes the importance of dust in cryosphere changes where Tibetan glaciers are strongly affected by Asian dust deposition.

The Relationship Between Submarine Melt and Subglacial Discharge From Observations at a Tidewater Glacier

AbstractAt tidewater glacier termini, ocean‐glacier interactions hinge on two sources of freshwater—submarine melt and subglacial discharge—yet these freshwater fluxes are often unconstrained in their magnitude, seasonality, and relationship. With measurements of ocean velocity, temperature and salinity, fjord budgets can be evaluated to partition the freshwater flux into submarine melt and subglacial discharge. We apply these methods to calculate the freshwater fluxes at LeConte Glacier, Alaska, across a wide range of oceanic and atmospheric conditions during six surveys in 2016–2018. We compare these ocean‐derived fluxes with an estimate of subglacial discharge from a surface mass balance model and with estimates of submarine melt from multibeam sonar and autonomous kayaks, finding relatively good agreement between these independent estimates. Across spring, summer, and fall, the relationship between subglacial discharge and submarine melt follows a scaling law predicted by standard theory (melt ∼ discharge1/3), although the total magnitude of melt is an order of magnitude larger than theoretical estimates. Subglacial discharge is the dominant driver of variability in melt, while the dependence of melt on fjord properties is not discernible. A comparison of oceanic budgets with glacier records indicates that submarine melt removes 33%–49% of the ice flux into the terminus across spring, summer, and fall periods. Thus, melt is a significant component of the glacier's mass balance, and we find that melt correlates with seasonal retreat; however, melt does not appear to directly amplify calving.

A new Level 4 multi-sensor ice surface temperature product for the Greenland Ice Sheet

Abstract. The Greenland Ice Sheet (GIS) is subject to amplified impacts of climate change and its monitoring is essential for understanding and improving scenarios of future climate conditions. Surface temperature over the GIS is an important variable, regulating processes related to the exchange of energy and water between the surface and the atmosphere. Few local observation sites exist; thus spaceborne platforms carrying thermal infrared instruments offer an alternative for surface temperature observations and are the basis for deriving ice surface temperature (IST) products. In this study several satellite IST products for the GIS were compared, and the first multi-sensor, gap-free (Level 4, L4) product was developed and validated for 2012. High-resolution Level 2 (L2) products from the European Space Agency (ESA) Land Surface Temperature Climate Change Initiative (LST_cci) project and the Arctic and Antarctic Ice Surface Temperatures from Thermal Infrared Satellite Sensors (AASTI) dataset were assessed using observations from the PROMICE (Programme for Monitoring of the Greenland Ice Sheet) stations and IceBridge flight campaigns. AASTI showed overall better performance compared to LST_cci data, which had superior spatial coverage and availability. Both datasets were utilised to construct a daily, gap-free L4 IST product using the optimal interpolation (OI) method. The resulting product performed satisfactorily when compared to surface temperature observations from PROMICE and IceBridge. Combining the advantages of satellite datasets, the L4 product allowed for the analysis of IST over the GIS during 2012, when a significant melt event occurred. Mean summer (June–August) IST was −5.5 ± 4.5 ∘C, with an annual mean of −22.1 ± 5.4 ∘C. Mean IST during the melt season (May–August) ranged from −15 to −1 ∘C, while almost the entire GIS experienced at least between 1 and 5 melt days when temperatures were −1 ∘C or higher. Finally, this study assessed the potential for using the satellite L4 IST product to improve model simulations of the GIS surface mass balance (SMB). The L4 IST product was assimilated into an SMB model of snow and firn processes during 2012, when extreme melting occurred, to assess the impact of including a high-resolution IST product on the SMB model. Compared with independent observations from PROMICE and IceBridge, inclusion of the L4 IST dataset improved the SMB model simulated IST during the key onset of the melt season, where model biases are typically large and can impact the amount of simulated melt.

Indus River Basin Glacier Melt at the Subbasin Scale

Pakistan is the most glaciated country on the planet but faces increasing water scarcity due to the vulnerability of its primary water source, the Indus River, to changes in climate and demand. Glacier melt constitutes over one-third of the Indus River’s discharge, but the impacts of glacier shrinkage from anthropogenic climate change are not equal across all eleven subbasins of the Upper Indus. We present an exploration of glacier melt contribution to Indus River flow at the subbasin scale using a distributed surface energy and mass balance model run 2001–2013 and calibrated with geodetic mass balance data. We find that the northern subbasins, the three in the Karakoram Range, contribute more glacier meltwater than the other basins combined. While glacier melt discharge tends to be large where there are more glaciers, our modeling study reveals that glacier melt does not scale directly with glaciated area. The largest volume of glacier melt comes from the Gilgit/Hunza subbasin, whose glaciers are at lower elevations than the other Karakoram subbasins. Regional application of the model allows an assessment of the dominant drivers of melt and their spatial distributions. Melt energy in the Nubra/Shyok and neighboring Zaskar subbasins is dominated by radiative fluxes, while turbulent fluxes dominate the melt signal in the west and south. This study provides a theoretical exploration of the spatial patterns to glacier melt in the Upper Indus Basin, a critical foundation for understanding when glaciers melt, information that can inform projections of water supply and scarcity in Pakistan.

Increasing surface runoff from Greenland's firn areas.

At high elevations of ice sheets, melting snow generally percolates and refreezes, so does not contribute to the shrinking of the ice sheet. Here, we systematically map the runoff area of the Greenland ice sheet, using surface rivers visible on satellite imagery. Between 1985 and 2020, the maximum runoff elevation rose by 58-329 metres, expanding the runoff area by 29% (-8%/+6%). Excess melt beyond the refreezing capacity of pores in snowfall has created near-impermeable ice slabs that sustain surface runoff even in cooler summers. We show that two surface mass balance models over-estimate the runoff area by 16-30%. Once restricted to our observed areas they indicate that 5-10% of recent runoff likely comes from the expanded runoff area. Runoff from higher elevations is sensitive to projected warming as further increases in the runoff limit will increase the runoff area disproportionately.

Multitemporal mass change analysis of Greenland Ice Sheet using variational mode decomposition

SUMMARY The Greenland Ice Sheet (GrIS) is the largest ice body in the Northern Hemisphere. Quantifying the spatiotemporal characteristics of its mass change is crucial for understanding global climate change. Many studies have been focused on the long-term ice mass change and acceleration, but a more detailed analysis of multitemporal signals, including annual, interannual and transient variations, is still imperative to study the periodic ice mass change. Here, we comprehensively characterize the multitemporal mass changes of the entire GrIS and subregions using a variational mode decomposition method, applied to Gravity Recovery and Climate Experiment satellite data, surface mass balance model output, climate parameters and GPS observations. We found that both the interannual and transient mass variations of the southern subregions have larger amplitudes associated with pronounced precipitations, indicating that the southern mass change patterns are more vulnerable to short-term climate variability. We also found that the reported rapid mass loss in 2010, 2012, 2016 and 2019 should be attributed to the interannual signals that result from low precipitations, significant runoff and evapotranspiration. The largest interannual mass variation was discovered in 2019 (−235 Gt), but due to the combined effect of interannual loss (−147 Gt) and transient attenuation (−380 Gt), the greatest mass loss (−527 Gt) was observed at the end of 2012. Our study emphasizes the importance of multitemporal signals in characterizing the spatiotemporal GrIS mass change and exploring the coupling effect between ice mass change and climate conditions.