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The number of Arctic glaciers with direct, long–term measurements of mass balance is limited. Here we used satellite–based observations of the glacier snowline altitude (SLA), the location of the transition between snow cover and ice late in the summer, to approximate the position of the equilibrium line altitude (ELA)–a parameter important for mass balance assessment and for understanding the response of glaciers to climate change. We mapped the snowline (SL) on a subset of 269 land–terminating glaciers above 60 °N latitude in the latest available summer, clear–sky Landsat satellite image between 1984 and 2022. The mean SLA was extracted using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM). We compare remotely–observed SLA observations with available long–term field–based measurements of ELA and with ERA5–Land reanalysis climate data. Over the last four decades, Arctic glacier SLAs have risen an average of ~152 m (3.9±0.4 m yr–1; R2=0.74, p<0.001), with a corresponding summer (June, July, August) temperature shift of +1.2 °C at the glacier locations. This equates to a 127±5 m shift per 1 °C of summer warming. However, along with warming, we observe an overall decrease in snowfall, an increase in rainfall, and a decrease in the total number of days in which the mean daily temperature is less than or equal to 0 °C. Glacier SLA is most strongly correlated with the number of freezing days, emphasizing the dual effect of multi–decadal trends in mean annual temperature on both ablation (increasing melt) and accumulation processes (reducing the number of days in which snow can fall). Although we find evidence for a negative morpho–topographic feedback that occurs as glaciers retreat to higher elevations, we show that more than 50 % of the glaciers studied here could be entirely below the SLA by 2100, assuming the pace of global warming and the mean rate of SLA rise is maintained. [ABSTRACT FROM AUTHOR]

Mass loss from iceberg calving at marine-terminating glaciers is one of the largest and most poorly constrained contributors to sea-level rise. However, our understanding of the processes controlling ice fracturing and crevasse evolution is incomplete. Here, we use Gabor filter banks to automatically map crevasse density and orientation through time on a ~150 km2 terminus region of Narsap Sermia, an outlet glacier of the southwest Greenland ice sheet. We find that Narsap Sermia is dominated by transverse (flow-perpendicular) crevasses near the ice front and longitudinal (flow-aligned) crevasses across its central region. Measured crevasse orientation varies on sub-annual timescales by more than 45 $^\circ$ in response to seasonal velocity changes, and also on multi-annual timescales in response to broader dynamic changes and glacier retreat. Our results show a gradual up-glacier propagation of the zone of flow-transverse crevassing coincident with frontal retreat and acceleration occurring in 2020/21, in addition to sub-annual crevasse changes primarily in transition zones between longitudinal to transverse crevasse orientation. This provides new insight into the dynamics of crevassing at large marine-terminating glaciers and a potential approach for the rapid identification of glacier dynamic change from a single pair of satellite images. [ABSTRACT FROM AUTHOR]

The Greenland Ice Sheet is a major contributor to current and projected sea level rise in the warming climate. However, uncertainties in Greenland's contribution to future sea level rise remain, partly due to challenges in constraining the role of ice dynamics. Transient ice accelerations, or ice speed-up events, lasting from 1 d to 1 week, have the potential to indirectly affect the mass budget of the ice sheet. They are triggered by an overload of the subglacial drainage system due to an increase in water supply. In this study, we identify melt-induced ice speed-up events at the Russell Glacier, southwest Greenland, in order to analyse synoptic patterns driving these events. The short-term speed-up events are identified from daily ice velocity time series collected from six GPS stations along the glacier for each summer (May–October) from 2009 to 2012. In total, 45 ice speed-up events are identified, of which we focus on the 36 melt-induced events, where melt is derived from two in situ observational datasets and one regional climate model forced by ERA5 reanalysis. We identify two additional potential water sources, namely lake drainages and extreme rainfall, which occur during 14 and 4 out of the 36 melt-induced events, respectively. The 36 melt-induced speed-up events occur during synoptic patterns that can be grouped into three main clusters: (1) patterns that resemble atmospheric rivers with a landfall in southwest Greenland, (2) patterns with anticyclonic blocking centred over southwest Greenland, and (3) patterns that show low-pressure systems centred either south or southeast of Greenland. Out of these clusters, the one resembling atmospheric river patterns is linked to the strongest speed-up events induced by 2 to 3 d continuously increasing surface melt driven by anomalously high sensible heat flux and incoming longwave radiation. In the other two clusters, the net shortwave radiation dominates the contribution to the melt energy. As the frequency and intensity of these weather patterns may change in the warming climate, so may the frequency and intensity of ice speed-up events, ultimately altering the mass loss of the ice sheet. [ABSTRACT FROM AUTHOR]

The Greenland Ice Sheet (GrIS) is losing mass as the climate warms through both increased meltwater runoff and ice discharge at marine terminating sectors. At the ice sheet surface, meltwater runoff forms a dynamic supraglacial hydrological system which includes stream/river networks and large supraglacial lakes (SGLs). Streams/rivers can route water into crevasses, or into supraglacial lakes with crevasses underneath, both of which can then hydrofracture to the ice sheet base, providing a mechanism for the surface meltwater to access the bed. Understanding where, when and how much meltwater is transferred to the bed is important because variability in meltwater supply to the bed can increase ice flow speeds, potentially impacting the hypsometry of the ice sheet in grounded sectors, and iceberg discharge to the ocean. Here we present a new, physically-based, supraglacial hydrology model for the GrIS that is able to simulate a) surface meltwater routing and SGL filling, b) rapid meltwater drainage to the ice-sheet bed via the hydrofracture of surface crevasses both in, and outside of, SGLs, c) slow SGL drainage via overflow in supraglacial meltwater channels and, by offline coupling with a second model, d) the freezing and unfreezing of SGLs from autumn to spring. We call the model Supraglacial Hydrology Evolution and Drainage (or SHED). We apply the model to three study regions in South West Greenland between 2015 and 2019 inclusive and evaluate its performance with respect to observed supraglacial lake extents, and proglacial discharge measurements. We show that the model reproduces 80% of observed lake locations, and provides good agreement with observations in terms of the temporal evolution of lake extent. Modelled moulin density values are in keeping with those previously published and seasonal and inter-annual variability in proglacial discharge agrees well with that observed, though the observations lag the model by a few days since they include transit time through the subglacial system and the model does not. Our simulations suggest that lake drainage behaviours may be more complex than traditional models suggest, with lakes in our model draining through a combination of both overflow and hydrofracture, and some lakes draining only partially and then refreezing. This suggests that in order to simulate the evolution of Greenland's surface hydrological system with fidelity, then a model that includes all of these processes needs to be used. In future work we will couple our model to a subglacial model and an ice flow model, and thus use our estimates of where, when and how much meltwater gets to the bed to understand the consequences for ice flow. [ABSTRACT FROM AUTHOR]

Iceberg calving accounts for up to half of mass loss from the Greenland Ice Sheet (GrIS), with their size distributions providing insights into glacier calving dynamics and impacting fjord environments through their melting and subsequent freshwater release. Iceberg area and volume data for the GrIS are currently limited to a handful of fjord locations, while existing approaches to iceberg detection are often time-consuming and are not always suited for long time series analysis over large spatial scales. This study presents a highly automated workflow that detects icebergs and appends their associated metadata within Google Earth Engine using high spatial resolution timestamped ArcticDEM (Arctic Digital Elevation Model) strip data. This is applied to three glaciers that exhibit a range of different iceberg concentrations and size distributions: Sermeq Kujalleq (Jakobshavn Isbræ), Umiammakku Isbræ and Kangiata Nunaata Sermia. A total of 39 ArcticDEM scenes are analysed, detecting a total of 163 738 icebergs with execution times of 6 min to 2 h for each glacier depending on the number of DEMs available and total area analysed, comparing well with the mapping of manually digitised outlines. Results reveal two distinct iceberg distributions at Sermeq Kujalleq and Kangiata Nunaata Sermia where iceberg density is high, and one distribution at Umiammakku Isbræ where iceberg density is low. Small icebergs (< 1000 m 2) are found to account for over 80 % of each glacier's icebergs; however, they only contribute to 10 %–37 % of total iceberg volume suggesting that large icebergs are proportionally more important for glacier mass loss and as fjord freshwater reservoirs. The overall dataset is used to construct new area-to-volume conversions (with associated uncertainties) that can be applied elsewhere to two-dimensional iceberg outlines derived from optical or synthetic aperture radar imagery. When data are expressed in terms of total iceberg count and volume, insight is provided into iceberg distributions that have potential applicability to observations and modelling of iceberg calving behaviour and fjord freshwater fluxes. Due to the speed and automated nature of our approach, this workflow offers the potential to interrogate iceberg data on a pan-Arctic scale where ArcticDEM strip data coverage allows. [ABSTRACT FROM AUTHOR]

Marine-terminating outlet glacier terminus traces, mapped from satellite and aerial imagery, have been used extensively in understanding how outlet glaciers adjust to climate change variability over a range of timescales. Numerous studies have digitized termini manually, but this process is labor intensive, and no consistent approach exists. A lack of coordination leads to duplication of efforts, particularly for Greenland, which is a major scientific research focus. At the same time, machine learning techniques are rapidly making progress in their ability to automate accurate extraction of glacier termini, with promising developments across a number of optical and synthetic aperture radar (SAR) satellite sensors. These techniques rely on high-quality, manually digitized terminus traces to be used as training data for robust automatic traces. Here we present a database of manually digitized terminus traces for machine learning and scientific applications. These data have been collected, cleaned, assigned with appropriate metadata including image scenes, and compiled so they can be easily accessed by scientists. The TermPicks data set includes 39 060 individual terminus traces for 278 glaciers with a mean of 136 ± 190 and median of 93 of traces per glacier. Across all glaciers, 32 567 dates have been digitized, of which 4467 have traces from more than one author, and there is a duplication rate of 17 %. We find a median error of ∼ 100 m among manually traced termini. Most traces are obtained after 1999, when Landsat 7 was launched. We also provide an overview of an updated version of the Google Earth Engine Digitization Tool (GEEDiT), which has been developed specifically for future manual picking of the Greenland Ice Sheet. [ABSTRACT FROM AUTHOR]

Our ability to improve prognostic modeling of the Greenland Ice Sheet relies on understanding the long-term relationships between climate and mass flux (via iceberg calving) from marine-terminating tidewater glaciers (TWGs). Observations of recent TWG behavior are widely available, but long-term records of TWG advance are currently lacking. We present glacial geomorphological, sedimentological, archaeological, and modeling data to reconstruct the -20 km advance of Kangiata Nunaata Sermia (KNS; the largest tidewater glacier in southwest Greenland) during the first half of the past millennium. The data show that KNS advanced -15 km during the 12th and 13th centuries CE at a rate of -115 m a-1, contemporaneous with regional climate cooling toward the Little Ice Age and comparable to rates of TWG retreat witnessed over the past -200 years. Presence of Norse farmsteads proximal to KNS demonstrates their resilience to climate change, manifest as a rapidly advancing TWG in a cooling climate. The results place limits on the magnitude of ice-margin advance and demonstrate TWG sensitivity to climate cooling as well as warming. These data combined with our grounding-line stability analysis provide a long-term record that validates approaches to numerical modeling aiming to link calving to climate. [ABSTRACT FROM AUTHOR]

Gaining knowledge of tidewater glacier (TWG) margin evolution, solid ice flux and their responses to climate over large spatio-temporal scales provides valuable context for the projection of future Greenland ice sheet (GrIS) change. Although studies of sector-wide responses of TWGs exist, studies at an ice-sheet-wide scale have only just become feasible. Here, we present a dataset of 224 annual TWG margins for 1984–2017 (n = 3801), showing that averaged over regional scales, normalised terminus change is linear. Regionally linear retreat trends were identified across most sectors of the GrIS starting in the mid-1990s, although in contrast to previous studies, the northeastern sector is shown to have experienced sustained retreat since the mid-1980s. Through cointegration analyses, individual glaciers are shown to have differing sensitivities to potential climate drivers, though on a sector-wide scale the northwest and southeast are shown to be especially sensitive to annual sea surface temperature and June–July–August air temperature, respectively. Although 92% of the analysed glaciers experience retreat across the GrIS, observed increases in absolute flux for the entire ice sheet can be explained by changes in just 11 of these TWGs. [ABSTRACT FROM AUTHOR]

High Mountain Asia (HMA) hosts the largest glacier concentration outside of polar regions. It is also distinct glaciologically as it forms one of two major surge clusters globally, and many glaciers there contradict the globally observed glacier recession trend. Surging glaciers are critical to our understanding of HMA glacier dynamics, threshold behaviour and flow instability, and hence have been the subject of extensive research, yet many dynamical uncertainties remain. Using the cloud-based geospatial data platform, Google Earth Engine (GEE) and GEE-developed tool, GEEDiT, to identify and quantify trends in the distribution and phenomenological characteristics of surging glaciers synoptically across HMA, we identified 137 glaciers as surging between 1987–2019. Of these, 55 were newly identified, 15 glaciers underwent repeat surges, and 18 were identified with enhanced glaciological hazard potential, most notably from Glacier Lake Outburst Floods (GLOFs). Terminus position time series analysis from 1987–2019 facilitated the development of a six-part phenomenological classification of glacier behaviour, as well as quantification of surge variables including active phase duration, terminus advance distance and rate, and surge periodicity. This research demonstrates the application of remote sensing techniques and the GEE platform to develop our understanding of surging glacier distribution and terminus phenomenology across large areas, as well as their ability to highlight potential geohazard locations, which can subsequently be used to focus monitoring efforts. [ABSTRACT FROM AUTHOR]

Kangerdlugssuaq Glacier is one of Greenland's largest tidewater outlet glaciers, accounting for approximately 5 % of all ice discharge from the Greenland Ice Sheet. In 2018 the Kangerlussuaq ice front reached its most retreated position, since observations began in 1932. We determine the relationship between retreat and: (i) ice velocity; and (ii) surface elevation change, to assess the impact of the retreat on the glacier trunk. Between 2016 and 2018 the glacier retreated ~5 km and brought the Kangerlussuaq ice front into a major (~15 km long) overdeepening. Coincident with this retreat, the glacier thinned as a result of near-terminus acceleration in ice flow. The subglacial topography means that 2016-18 terminus recession is likely to trigger a series of feedbacks between retreat, thinning and glacier acceleration, leading to a rapid and high-magnitude increase in discharge and sea level rise contribution. Dynamic thinning may continue until the glacier reaches the upward sloping bed ~10 km inland of its current position. Given the complexity and scale of the processes involved, such changes will not be represented in prognostic models of the Greenland Ice Sheet to 2100 and beyond. [ABSTRACT FROM AUTHOR]