Intense surface melt and subsequent meltwater ponding are the key triggers for the disintegration of ice shelves in the Antarctic Peninsula (AP). Although a long-term decline in AP surface melt has been evident since the early 1990s, episodes of intense surface melt events have frequently been reported in recent years. Here, using 1979-2023 daily surface melt rates from regional climate models, we show that this declining trend has reversed, with November-February surface melt increasing significantly by 3% year-1 (p < 0.05) between 2009 and 2022. Decomposition of trends based on circulation classification indicates that changes in the frequency of atmospheric circulation patterns cannot account for this enhancement. Instead, the thermodynamics-linked to variations in the surface energy budget independent of atmospheric circulation contribute 80% of the positive trend in AP surface melt. Analysis of extreme surface melt events further supports the dominant thermodynamic contribution.

Abstract. Accurately estimating the surface mass balance (SMB) of the Greenland Ice Sheet (GrIS) is essential to quantify its contribution to sea-level rise. The polar regional atmospheric climate model MAR is widely used to simulate GrIS SMB and to force ice sheet dynamics models, highlighting the need for a thorough evaluation. Here, we evaluate the latest MAR version (MARv3.14) over Greenland at 5 km spatial resolution and examine the impact of coarser resolutions (10–30 km) on the simulated SMB and its components. MAR outputs are compared to a range of independent observations, including in situ SMB measurements, automatic weather station (AWS) records of near-surface meteorological variables, satellite-derived melt extent, and albedo products. At 5 km, MAR reproduces the observed SMB with a root-mean-square error (RMSE) of 0.51 m and a correlation of 0.93. For near-surface meteorological variables and surface energy budget fluxes, the model RMSE is smaller than the corresponding observed natural variability (i.e., standard deviation), indicating non-significant model error. Prescribing bare-ice albedo improves the model performance in the ablation zone, while biases remain in the accumulation zone, suggesting that further improvements are required in the snow albedo scheme. In addition, simulated melt timing is consistent with satellite-based melt extent products. Sensitivity experiments reveal that discrepancies between simulations at different spatial resolutions are mostly limited to the ice sheet margins where strong SMB and topographic gradients occur, notably in the southeast of Greenland where precipitation peaks. Differences in integrated SMB generally remain small and mostly non-significant, while individual components, i.e., precipitation and runoff, exhibit larger resolution-dependent variations. We find that a resolution of at least 10 km is required to accurately capture the GrIS climate and SMB. Reducing computation time about 10-fold relative to 5 km simulation, a 10 km grid makes a good compromise for long-term climate projections.

Due to increasing air temperatures, surface melt and meltwater runoff expand to ever higher elevations on the Greenland ice sheet and reach far into its firn area. Here, we evaluate how two regional climate models (RCMs) simulate the expansion of the ice sheet runoff area: MAR, and RACMO with its offline firn model IMAU-FDM. For the purpose of this comparison we first improve an existing algorithm to detect daily visible runoff limits from MODIS satellite imagery. We then apply the improved algorithm to most of the Greenland ice sheet and compare MODIS to RCM runoff limits for the years 2000 to 2021. We find that RACMO/IMAU-FDM runoff limits are on average somewhat lower than MODIS and show little fluctuation from year to year. MAR runoff limits are higher than MODIS, but their inter-annual fluctuations are more similar to MODIS. Both models apply a bucket scheme to route meltwater vertically. Focusing on the K-transect, we demonstrate that differences in modelled firn temperatures and in the implementation of the bucket scheme govern RCM simulated runoff limits. The formulation of the runoff condition is of large influence: in RACMO/IMAU-FDM meltwater is only considered runoff when it reaches the bottom of the simulated firn pack; in MAR runoff can also occur from within the firn pack, which contributes to its high runoff limits. We show that total runoff along the K-transect, simulated by the two RCMs, diverges by up to 29 % in extraordinary melt years. This difference is mostly caused by the diverging simulated runoff limits, which emphasizes the importance of improving the simulations of Greenland's melting firn area.

Accurate simulation of the Greenland Ice Sheet (GrIS) surface mass balance (SMB) is essential for quantifying its contribution to sea-level rise. The regional atmospheric climate model MAR is widely used to study GrIS SMB changes and force ice-sheet models, highlighting the importance of assessing its performance and sensitivity to horizontal resolution. Here, we evaluate the latest MARv3.14 version at 5 km resolution and assess the impact of coarser resolutions (10–30 km) on simulated GrIS SMB and its components.MAR outputs are evaluated against a range of independent observations, including in situ SMB measurements, automatic weather station records of near-surface meteorological variables, and satellite-derived melt extent and albedo products. At 5 km resolution, MAR reproduces observed SMB with a root-mean-square error of 0.53 m w.e. yr⁻¹. For near-surface meteorological variables and surface energy budget fluxes, model errors are smaller than the corresponding observed variability. The assimilation of bare-ice albedo, implemented in the latest MAR version, improves model performance in the ablation zone. Remaining biases in the accumulation zone suggest that improvements to the snow albedo scheme are further required. Simulated melt timing is consistent with satellite-based melt extent products.Comparing simulations at different spatial resolutions, we find that SMB discrepancies mainly occur at the ice-sheet margins, characterized by strong topographic gradients. While integrated SMB differences generally remain within interannual variability, precipitation and runoff are highly sensitive to the model spatial resolution.Corrections based on a vertical SMB gradient (as in Franco et al., 2012) or a sub-pixel methodology allowing the surface scheme (SISVAT) to be run at a higher resolution than the atmospheric model could deal in part with runoff discrepancies vs spatial resolution but precipitation anomalies remain a challenge. We conclude by discussing ongoing model developments, in particular the implementation of a sub-pixel methodology.

The Greenland Ice Sheet is a major contributor to global sea-level rise, having lost ~4,900 Gt of ice since 1992 and already added ~13 mm to global mean sea-level. Even without further warming, it is committed to at least ~274 mm of additional sea-level rise, and complete melting would ultimately raise sea level by ~7 m. In this Review, we synthesise changes in Greenland Ice Sheet surface melt from 1500 to 2200 CE. Surface melt has increased rapidly by ~1% per year since the 1990s, driven by regional warming and changes in atmospheric circulation, particularly enhanced blocking. Several unprecedented extreme melt events lasting several days have occurred since 2007, with record cases such as in July 2012 affecting nearly the entire ice sheet surface. Absorbed shortwave radiation is the dominant driver of seasonal melt, but turbulent heat fluxes, cloud processes and albedo feedbacks strongly modulate melt variability across space and time. Climate models diverge in their representation of these processes, with projected melt and surface mass loss differing by up to a factor of two between three different state-of-the-art regional climate models even under identical forcing. Despite advances in regional climate and Greenland melt modelling, key uncertainties remain in quantifying extreme melt events and their drivers, meltwater retention, firn processes and the coupling between atmospheric forcing and surface energy balance, limiting confidence in projections. Addressing these gaps requires expanded observations, improved process representation in models and integrated use of emerging data-driven approaches to better constrain future melt and its contribution to sea-level rise. Greenland Ice Sheet melt has intensified since the 1990s with implications for sea-level rise. This Review synthesises paleoclimate records, observations and regional climate melt model simulations to explore the patterns and drivers of melt variability and extremes, and assess uncertainties in future projections.

Patagonian glaciers have been rapidly losing mass in the last two decades, but the driving processes remain poorly known. Here we use two state-of-the-art regional climate models to reconstruct long-term (1940-2023) glacier surface mass balance (SMB), i.e., the difference between precipitation accumulation, surface runoff and sublimation, at about 5 km spatial resolution, further statistically downscaled to 500 m. High-resolution SMB agrees well with in-situ observations and, combined with solid ice discharge estimates, captures recent GRACE/GRACE-FO satellite mass change. Glacier mass loss coincides with a long-term SMB decline (-0.35 Gt yr-2), primarily driven by enhanced surface runoff (+0.47 Gt yr-2) and steady precipitation. We link these trends to a poleward shift of the subtropical highs favouring warm northwesterly air advections towards Patagonia (+0.14°C dec-1 at 850 hPa). Since the 1940s, Patagonian glaciers have lost 1350  ± 449 Gt of ice, equivalent to 3.7  ± 1.2 mm of global mean sea-level rise.

Land ice in the Arctic is losing mass as temperatures increase, contributing to global sea level rise. While this loss is largely driven by melt induced by atmospheric warming, precipitation can alter the rate at which loss occurs depending on its intensity and phase. Case studies have illustrated varied potential impacts of extreme precipitation events on the surface mass balance (SMB) of land ice, but the importance of extreme precipitation to seasonal SMB has not been investigated. In this study, simulations from the Regional Atmospheric Climate Model (RACMO) and Variable-Resolution Community Earth System Model (VR-CESM) are explored over historical (1980–1998) and future (2080–2098, SSP5-8.5) periods to reconstruct and further project seasonal SMB for the Greenland Ice Sheet and ice caps of the Eastern Canadian Arctic. Historically, extreme precipitation days consistently had higher SMB than non-extreme precipitation days throughout the study area in both the cold season (DJFM) and warm season (JJAS). In future simulations, this relationship persists for the cold season. However, for the warm season, projections indicate a shift towards less positive and more variable SMB responses to extreme precipitation days in the future, accounting for a larger portion of cumulative seasonal positive and negative SMB. Mass loss during extreme precipitation days becomes more common, particularly in SW Greenland and Baffin Island. This likely occurs in part because of a shift toward more rainfall during extreme precipitation events. In other words, in a strong warming scenario, extreme warm season precipitation may no longer reliably yield mass gain for the Greenland Ice Sheet and surrounding ice caps.

Study region: BelgiumStudy focus: In July 2021, Western Germany, the Netherlands and Belgium were hit by extreme rainfall events of unprecedented intensity, raising concerns about future trends. To assess future trends in extreme precipitation frequency and intensity, we use the regional climate model MAR at 5-km spatial resolution to conduct climate projections until 2100. MAR is forced by a set of six CMIP6 Earth System model (ESMs) with 4 IPCC scenarios ranging from low to high-end warming.Study insights: First, an Extreme Value Analysis (EVA) is performed on bias-adjusted daily model outputs over 30-year moving windows. We find that, on average, extreme precipitation intensity rises following the Clausius-Clapeyron scaling, i.e., a 7% increase per additional degree of global warming. This trend results from a clear increase in the spread and in the modes of the extreme precipitation event distributions. Second, an EVA is performed over the complete simulated period (2015-2100). Our analyses reveal that, even under low-warming scenarios, return level maps, i.e., representing the precipitation values associated with a certain return period, are more intense than those obtained using observational data over 1951-2021. For the 21st century, the 20-year daily return level can locally reach 100 mm per day, which represents a 25%–30% increase relative to the present day.

Regional climate models are fundamental tools in understanding and quantifying the contribution of the Greenland ice sheet to sea-level rise. We perform an extensive evaluation of the daily air temperature simulated by two regional climate models, MARv3.12 and RACMO2.3p2, and a global atmospheric reanalysis, ERA5, at 35 locations across the ice sheet over the period 1995 - 2020. We compare model results to weather station data from two climate networks, focusing on the spatial and temporal variability in mean biases. All three models perform well at low elevations (< 1500 m a.s.l.) with a mean bias of 0.16 degrees C (MAR), 0.36 degrees C (RACMO), and 0.41 degrees C (ERA5), while warm biases (> 1.70 degrees C) are found at high elevations (> 1500 m a.s.l.). Temperature biases exhibit a strong seasonality, being more pronounced during winter and much smaller during summer ranging from 0.11 degrees C to 0.59 degrees C. No interannual variability is found in the biases of all three datasets. Daily variability within each month is captured well by both climate models and the reanalysis at most locations. Finally, all three models perform overall better in the ablation zone during summer, i.e., where and when considerable melt production occurs.

The surface elevation of the Greenland Ice Sheet is constantly changing due to the interplay between surface mass balance processes and ice dynamics, each exhibiting distinct spatiotemporal patterns. Here, we employ satellite and airborne altimetry data with fine spatial (1 km) and temporal (monthly) resolutions to document this spatiotemporal evolution from January 2003 to August 2023. To estimate elevation changes of the Greenland Ice Sheet (GIS), we utilize radar altimetry data from CryoSat-2 and EnviSat, laser altimetry data from the ICESat and ICESat-2, and laser altimetry data from NASA's Operation IceBridge Airborne Topographic Mapper. We produce continuous monthly ice surface elevation changes from January 2003 to August 2023 on a 1 km grid covering the entire GIS. We estimate cumulative ice loss of 4352 Gt +/- 315 Gt (12.1 +/- 0.9 mm sea level equivalent) during this period, excluding peripheral glaciers. Between 2003 and 2023, the ice sheet land-terminating margin underwent a significant cumulative thinning of several meters. Ocean-terminating glaciers exhibited thinning between 20-40 m, with Jakobshavn Isbr ae experiencing an exceptional thinning of nearly 70 m. This dataset of fine-resolution altimetry data in both space and time will support studies of ice mass loss and will be useful for GIS modeling. To validate our monthly mass changes of the Greenland ice sheet, we use mass change from satellite gravimetry and mass change from the input-output method. On multiannual timescales, there is a strong correlation between the time series, with R values ranging from 0.88 to 0.92 (10.5061/dryad.s4mw6m9dh, Khan et al., 2025)

Abstract. Land ice in the Arctic is losing mass as temperatures increase, contributing to global sea level rise. While this loss is largely driven by melt induced by atmospheric warming, precipitation can alter the rate at which loss occurs depending on its intensity and phase. Case studies have illustrated varied potential impacts of extreme precipitation events on the surface mass balance (SMB) of land ice, but the importance of extreme precipitation to seasonal SMB has not been investigated. In this study, simulations from the Regional Atmospheric Climate Model (RACMO) and Variable-Resolution Community Earth System Model (VR-CESM) are explored over historical (1980–1998) and future (2080–2098, SSP5-8.5) periods to reconstruct and further project seasonal SMB for the Greenland Ice Sheet and ice caps of the Eastern Canadian Arctic. Historically, extreme precipitation days consistently had higher SMB than non-extreme precipitation days throughout the study area in both the cold season (DJFM) and warm season (JJAS). In future simulations, this relationship persists for the cold season. However, for the warm season, projections indicate a shift towards less positive and more variable SMB responses to extreme precipitation in the future and extreme precipitation events account for a larger portion of cumulative seasonal positive and negative SMB. Mass loss during extreme precipitation days becomes more common, particularly in SW Greenland and Baffin Island. This likely occurs in part because of a shift toward more rainfall during extreme precipitation events. In other words, in a strong warming scenario, extreme warm season precipitation will no longer reliably yield mass gain for the Greenland Ice Sheet and surrounding ice caps.

The Patagonian ice fields have been rapidly losing mass in the last decades, but little is known about the driving processes. Here we use state-of-the-art regional climate models to reconstruct the contemporary climate and glacier surface mass balance (SMB), i.e., the difference between snowfall accumulation and meltwater runoff, in the Southern Andes at 5 km spatial resolution for the period 1940-2022. Model outputs are further statistically downscaled to a 500 m grid that resolves SMB processes in high spatial detail. Our high-resolution SMB products show good agreement with both in-situ observations and GRACE/GRACE-FO satellite mass change measurements, when combined to solid ice discharge. We link recent glacier mass loss to an ongoing poleward shift of the subtropical highs that warms the ocean and atmosphere nearby Patagonian ice fields, in turn enhancing meltwater runoff.

The magnitude, source, release location, and timing of freshwater that ends up in the numerous Greenland fjords is of special interest for ice–ocean interactions and ecosystems. In this study, we investigate intra- and interannual variability in the various freshwater sources for Greenland's fjords in seven climatologically distinct regions. For this, we use direct and statistically downscaled output from regional climate models for the mass fluxes, process-based estimates of basal melt, and observational data for solid ice discharge. For the period 1940/1958 through 2023, we separately quantify runoff from the Greenland ice sheet, peripheral ice caps and tundra regions, and precipitation directly falling in the fjords. From 2009 onwards, the available data allow us to resolve the full seasonal cycle of freshwater input. The results indicate a diverse range of relative contributions from freshwater sources between seasons and regions. Freshwater input in fjords in the wet South-East and North-West is dominated by solid ice discharge (55 % and 67 %, respectively) with a small contribution of tundra runoff, whereas in the relatively drier North, North-East, and South-West the contribution of tundra runoff is more important (20 %, 25 %, and 30 %, respectively). Precipitation in fjords and tundra runoff can represent a large fraction of the monthly total, i.e. up to 11 % and 35 %, respectively, for winter and spring. However, the relative contribution of tundra runoff has been decreasing with time as the result of rapid increases in ice sheet and ice cap runoff over the past decades following atmospheric and oceanic warming. We show that the regional glacier-integrated melt-over-accumulation (MoA) ratio is a good predictor for the relative contributions of solid ice discharge, tundra runoff, and ice sheet runoff. These findings have implications for the use of freshwater fluxes forcing in regional ocean models and fjord studies and enhance our understanding of their impact on ocean and fjord circulation and biogeochemistry.

In this work, we examine connections between patterns of future Greenland precipitation and large-scale atmospheric circulation changes over the Northern Hemisphere. In the last three decades of the 21st century, CMIP5 and CMIP6 ensemble mean precipitation significantly decreases over the northern part of the North Atlantic Ocean with respect to 1951–1980. This drying signal extends from the ocean to the southeastern margin of Greenland. The 500 hPa geopotential height change shows a clear pattern including a widespread increase across the Arctic with a negative anomaly centered over Iceland and surrounding regions. To identify the mechanisms linking atmospheric circulation variability with Greenland precipitation, we perform a singular value decomposition (SVD) and center of action (COA) analysis. We find that a northeastward shift of the Icelandic Low (IL) under the SSP5‐8.5 warming scenario leads to the drying signal found in southeast Greenland. This implies that the IL location will have a strong influence on precipitation changes over southeast Greenland in the future, impacting projections of Greenland ice sheet surface mass balance.

Over the past two decades, the Canadian Arctic Archipelago has undergone significant glacier mass loss, driven primarily by surface melt. This study presents a detailed analysis of supraglacial drainage evolution along Ellesmere Island's similar to 830 km latitudinal extent using satellite imagery, historical aerial photographs and DEMs from 1959 to 2020. Analysis of five glaciers shows that drainage density (Dd) has increased over time, driven by the expansion of perennial rivers, especially at higher elevations. Far northern glaciers exhibit stable, well-developed drainage systems, while southern glaciers show a relatively greater increase in canyon development since 1959. Cold surface ice in the north supports higher Dd, while southern glaciers with extensive sinks (moulins and large crevasses) exhibit stronger surface-to-bed connectivity. Despite increased channelization, sinuosity changes remain statistically insignificant, reflecting dynamic canyon behavior governed by surface slope and meltwater discharge. Results align with modeled increases in melt, especially on southern glaciers where supraglacial systems have expanded most rapidly. Continued equilibrium line altitude rise under future warming is expected to intensify melt and result in the expansion of supraglacial drainage systems up-glacier, particularly for glaciers with large amounts of ice at mid-elevation.

Surface melt and subsequent runoff have been the main contributors to recent Greenland mass loss. However, previous studies mainly focused on the extent and persistence of surface melt. The variations in surface melt rates and extreme events have not been adequately known, especially the role of extremes in the long-term surface melt changes. Here, using two high-resolution regional climate models (RACMO2.3p2 and MARv3.14), we analyzed the variations in Greenland surface melt in 1958-2023. Both models (RACMO/MAR) show that annual surface melt is rapidly increasing post-1990 at a rate of 8.6 +/- 4.9/7.2 +/- 4.4 Gt per year. The northern regions show the strongest relative regional increase rate (3.9% +/- 1.9%/3.4% +/- 1.6% per year), contributing more surface melt to the whole Greenland. Based on the 90th percentile of the daily distribution, we found that extreme surface melt events from May to September (M-S) have become more frequent post-1990 (0.7/0.8 +/- 0.5 d per year). Compared with 1958-1990, M-S surface melt from extreme events has increased by 134/105 Gt per year and dominates the increase in the total surface melt. During extreme surface melt events, we found an increase in downward longwave radiation, net shortwave radiation and sensible heat flux. The rise in surface melt and extreme events post-1990 is linked to more frequent atmospheric blocking. This study improves our understanding of the role in ice sheet mass balance played by long-term variations in ice sheet surface melt and extreme events.

Over recent decades, the Greenland Ice Sheet (GrIS) has lost mass through increased melting and solid ice discharge into the ocean. Surface meltwater features such as supraglacial lakes (SGLs), channels and slush are becoming more abundant as a result of the former and are implicated as a control on the latter when they drain. It is not yet clear, however, how these different surface hydrological features will respond to future climate changes, and it is likely that GrIS surface melting will continue to increase as the Arctic warms. Here, we use Sentinel-2 and Landsat 8 optical satellite imagery to compare the distribution and evolution of meltwater features (SGLs, channels, slush) in the Russell–Leverett glacier catchment, southwest Greenland, in relatively high (2019) and low (2018) melt years. We show that (1) supraglacial meltwater covers a greater area and extends further inland to higher elevations in 2019 than in 2018; (2) slush – generally disregarded in previous Greenland surface hydrology studies – is far more widespread in 2019 than in 2018; (3) the supraglacial channel system is more interconnected in 2019 than in 2018; (4) a greater number and larger total area of SGLs drained in 2019, although draining SGLs were, on average, deeper and more voluminous in 2018; (5) small SGLs (≤0.0495 km2) – typically disregarded in previous studies – form and drain in both melt years, although this behaviour is more prevalent in 2019; and (6) a greater proportion of SGLs refroze in 2018 compared to 2019. This analysis provides new insight into how the ice sheet responds to significant melt events, and how a changing climate may impact meltwater feature characteristics, SGL behaviour and ice dynamics in the future.

During the Holocene, the Greenland Ice Sheet (GrIS) experienced substantial thinning, with some regions losing up to 600 m of ice. Ice sheet reconstructions, paleoclimatic records, and geological evidence indicate that, during the Last Glacial Maximum, the GrIS extended far beyond its current boundaries and was connected with the Innuitian Ice Sheet (IIS) in the northwest. We investigate these long-term geometry changes and explore several possible factors driving those changes by using the Parallel Ice Sheet Model (PISM) to simulate the GrIS thinning throughout the Holocene period, from 11.7 ka ago to the present. We perform an ensemble study of 841 model simulations in which key model parameters are systematically varied to determine the parameter values that, with quantified uncertainties, best reproduce the 11.7 ka of surface-elevation records derived from ice cores, providing confidence in the modeled GrIS paleo evolution. We find that since the Holocene onset, 11.7 ka ago, the GrIS mass loss has contributed 5.3 ± 0.3 m to the mean global sea-level rise, which is consistent with the ice-core-derived thinning curves spanning the time when the GrIS and the Innuitian Ice Sheet were bridged. Our results suggest that the GrIS is still responding to these past changes, having raised the sea level by 23 ± 26 mm SLE ka−1 in the last 500 years. Our results have implications for future ice sheet evolution, which should account for this long-term transient trend.

We present an ensemble of physically-based ice sheet model projections for the Greenland ice sheet (GrIS) that was produced as part of the European project PROTECT. Our ice sheet model (ISM) simulations are forced by high-resolution regional climate model (RCM) output and other climate model forcing, including a parameterisation for the retreat of marine-terminating outlet glaciers. The experimental design builds on the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6) protocol and extends it to more fully account for uncertainties in sea-level projections. We include a wider range of CMIP6 climate model output, more climate change scenarios, several climate downscaling approaches, a wider range of sensitivity to ocean forcing and we extend projections beyond the year 2100 up to year 2300, including idealised overshoot scenarios. GrIS sea-level rise contributions range from 16–76 mm (SSP1-2.6/RCP2.6), 22–163 mm (SSP2-4.5) and 27–354 mm (SSP5-8.5/RCP8.5) in the year 2100 (relative to 2014). The projections are strongly dependent on the climate scenario, moderately sensitive to the choice of RCM, and relatively insensitive to the ice sheet model choice. In year 2300, contributions reach 49 to 3127 mm, indicative of large uncertainties and a potentially very large long-term response. Idealised overshoot experiments to 2300 produce sea-level contributions in a range from 49 to 201 mm, with the ice sheet seemingly stabilised in a third of the experiments. Repeating end of the 21st century forcing until 2300 results in contributions of 58–163 mm (repeated SSP1-2.6), 98–218 mm (repeated SSP2-4.5) and 282–1230 mm (repeated SSP5-8.5). The largest contributions of more than 3000 mm by year 2300 are found for extreme scenarios of extended SSP5-8.5 with unabated warming throughout the 22nd and 23rd century. We also extend the ISMIP6 forcing approach backwards over the historical period and successfully produce consistent simulations in both past and future for three of the four ISMs. The ensemble design of ISM experiments is geared towards the subsequent use of emulators to facilitate statistical interpretation of the results and produce probabilistic projections of the GrIS contribution to future sea-level rise.