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Ice loss from the Greenland ice sheet is one of the largest sources of contemporary sea-level rise (SLR). While process-based models place timescales on Greenland’s deglaciation, their confidence is obscured by model shortcomings including imprecise atmospheric and oceanic couplings. Here, we present a complementary approach resolving ice sheet disequilibrium with climate constrained by satellite-derived bare-ice extent, tidewater sector ice flow discharge and surface mass balance data. We find that Greenland ice imbalance with the recent (2000–2019) climate commits at least 274 ± 68 mm SLR from 59 ± 15 × 103km2ice retreat, equivalent to 3.3 ± 0.9% volume loss, regardless of twenty-first-century climate pathways. This is a result of increasing mass turnover from precipitation, ice flow discharge and meltwater run-off. The high-melt year of 2012 applied in perpetuity yields an ice loss commitment of 782 ± 135 mm SLR, serving as an ominous prognosis for Greenland’s trajectory through a twenty-first century of warming.

With nine southern Greenland ice sheet ablation area locations, the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) “Q‐transect” is a source of snow accumulation and ice ablation data spanning 17 years (2000 to present). Snow water equivalence measurements below equilibrium line altitude enable resolving the location and magnitude of an orographic precipitation maximum. Snow depth skillfully predicts snow water equivalence in this region, for which we find no evidence of change 2001–2017. After describing observed accumulation and ablation spatiotemporal patterns, we examine surface mass balance (SMB) in 5.5‐km HIRHAM5, 7.5‐km Modèle Atmosphèrique Régional (MAR) v3.7, and 1‐km Regional Atmospheric Climate Model (RACMO2.3p2) regional climate model (RCM) output. HIRHAM5 and RACMO2.3p2 overestimate accumulation below equilibrium line altitude by 2 times. MAR SMB is closer to observations but lacks a distinct orographic peak. RCM ablation underestimation is attributable to overestimated snowfall (HIRHAM5 and RACMO2.3p2), overestimated bare ice albedo (MAR), and underestimation of downward turbulent heat fluxes. Calibrated ablation area RCM SMB data yield −0.3 ± 0.5 Gt/a SMB of the 559‐km2marine‐terminating Sermilik glacier (September 2000 to October 2012). Using Enderlin et al. (2014, https://doi.org/10.1002/2013GL059010) ice discharge data, Sermilik glacier's total mass balance is −1.3 ± 0.5 Gt/a with interannual variability dominated by SMB. The area specific mass loss is 17 to 20 times greater than the whole ice sheet mass loss after Andersen et al. (2015, https://doi.org/10.1016/j.epsl.2014.10.015) and Colgan et al. (2015, https://doi.org/10.1016/j.rse.2015.06.016), highlighting the Q‐transect's situation in an ice mass loss hot spot. Surface mass balance dominates the interannual variability in Sermilik glacier total mass balanceSouth Greenland ice sheet accumulation and ablation observations reveal Sermilik glacier total mass loss being 20 times the Greenland ice sheet averageThree RCMs underrate melt below ELA due to some combination of overestimated snowfall and ice albedo and underestimated downward turbulent heat flux

We document the existence of widespread firn aquifers in an elevation range of ~1200–2000 m, in the high snow‐accumulation regions of the Greenland ice sheet. We use NASA Operation IceBridge accumulation radar data from five campaigns (2010–2014) to estimate a firn‐aquifer total extent of 21,900 km2. We investigate two locations in Southeast Greenland, where repeated radar profiles allow mapping of aquifer‐extent and water table variations. In the upper part of Helheim Glacier the water table rises in spring following above‐average summer melt, showing the direct firn‐aquifer response to surface meltwater production changes. After spring 2012, a drainage of the firn‐aquifer lower margin (5 km) is inferred from both 750 MHz accumulation radar and 195 MHz multicoherent radar depth sounder data. For 2011–2014, we use a ground‐penetrating radar profile located at our Ridgeline field site and find a spatially stable aquifer with a water table fluctuating less than 2.5 m vertically. When combining radar data with surface topography, we find that the upper elevation edge of firn aquifers is located directly downstream of locally high surface slopes. Using a steady state 2‐D groundwater flow model, water is simulated to flow laterally in an unconfined aquifer, topographically driven by ice sheet surface undulations until the water encounters crevasses. Simulations suggest that local flow cells form within the Helheim aquifer, allowing water to discharge in the firn at the steep‐to‐flat transitions of surface topography. Supported by visible imagery, we infer that water drains into crevasses, but its volume and rate remain unconstrained. Firn aquifers represent a total area of 21,900 km2when inferred from airborne radar data collected between 2010 and 2014Water table interannual variations imply filling and drainageWater flows in the firn aquifer under low hydraulic gradients following local surface topography

Approximately half of Greenland’s current annual mass loss is attributed to runoff from surface melt. At higher elevations, however, melt does not necessarily equal runoff, because meltwater can refreeze in the porous near-surface snow and firn. Two recent studies suggest that all or most of Greenland’s firn pore space is available for meltwater storage, making the firn an important buffer against contribution to sea level rise for decades to come. Here, we employ in situ observations and historical legacy data to demonstrate that surface runoff begins to dominate over meltwater storage well before firn pore space has been completely filled. Our observations frame the recent exceptional melt summers in 2010 and 2012 (refs ,), revealing significant changes in firn structure at different elevations caused by successive intensive melt events. In the upper regions (more than ∼1,900 m above sea level), firn has undergone substantial densification, while at lower elevations, where melt is most abundant, porous firn has lost most of its capability to retain meltwater. Here, the formation of near-surface ice layers renders deep pore space difficult to access, forcing meltwater to enter an efficient surface discharge system and intensifying ice sheet mass loss earlier than previously suggested.

Turbulent heat fluxes, that is, the sensible heat flux and latent heat flux, are important sources/sinks of energy for surface melt over glaciers and ice sheets. Therefore, credible simulations of for example, future Greenland Ice Sheet mass loss need an accurate description of these fluxes. However, the parameterization of surface turbulent heat fluxes in climate models requires knowledge about the surface roughness lengths for momentum, heat and moisture, which are currently either unknown or tuned to indirect observations. In this study we take advantage of a large data set of eddy covariance observations acquired during multiple years and at multiple sites over the Greenland Ice Sheet. These in‐situ observations are used to develop an improved parameterization for the roughness length for momentum, and update the parameterization for the roughness lengths for heat and moisture over rough ice surfaces. The newly derived parameterizations are implemented in a surface energy balance model that is used to compute surface melt. Sensitivity experiments confirm the high sensitivity of surface melt to the chosen roughness length models. The new parameterization models the sensible heat flux to within 10 W m−2, and the cumulative ice ablation within 10% at three out of four sites. Two case studies demonstrate the important contribution of the turbulent heat fluxes to surface ablation. The presented roughness parameterizations can be implemented in climate models to improve the physical representation of surface roughness over rough snow and ice surfaces, which is expected to improve the modeled turbulent heat fluxes and thus surface melt. Accurately modeling the surface melt over glaciers and ice sheets requires accurately modeling the turbulent heat fluxes between the surface and the atmosphere, which in turn requires a description of the surface aerodynamic roughness. The surface aerodynamic roughness is poorly known, especially in remote areas such as the Greenland ice sheet. In this study we present a large data set of turbulent flux measurements acquired over rough melting ice over the Greenland Ice Sheet and in Iceland. This unique data set is used to develop an improved model for surface roughness lengths of rough ice. We then compute surface melt at different sites on the Greenland Ice Sheet between 2016 and 2021 with a surface energy balance model that includes these newly derived formulations. We find that realistically representing the variations in ice surface roughness leads to a more accurate representation of turbulent heat fluxes, and therefore surface melt. The importance of accurately modeling the turbulent heat fluxes is highlighted further during two cases of extreme melt events. The findings of this study can be used in energy balance models and climate models to improve simulations of surface melt. Observed roughness lengths for momentum over rough ice surfaces are accurately parameterized using snow depth and melting rateThe parameterization of the roughness length for heat over melting rough ice is updated based on 14 eddy covariance data setsImproving the roughness length parameterization improves both the modeled turbulent heat fluxes and the modeled ice ablation Observed roughness lengths for momentum over rough ice surfaces are accurately parameterized using snow depth and melting rate The parameterization of the roughness length for heat over melting rough ice is updated based on 14 eddy covariance data sets Improving the roughness length parameterization improves both the modeled turbulent heat fluxes and the modeled ice ablation

During two exceptionally large July 2012 multiday Greenland ice sheet melt episodes, nonradiative energy fluxes (sensible, latent, rain, and subsurface collectively) dominated the ablation area surface energy budget of the southern and western ice sheet. On average the nonradiative energy fluxes contributed up to 76% of daily melt energy at nine automatic weather station sites in Greenland. Comprising 6% of the ablation period, these powerful melt episodes resulted in 12–15% of the south and west Greenland automatic weather station annual ablation totals. Analysis of high resolution (~5 km) HIRHAM5 regional climate model output indicates widespread dominance of nonradiative energy fluxes across the western ablation area during these episodes. Yet HIRHAM5 still underestimates melt by up to 56% during these episodes due to a systematic underestimation of turbulent energy fluxes typical of regional climate models. This has implications for underestimating future melt, when exceptional melt episodes are expected to occur more frequently. Detailed observations of exceptional daily melt rates on the Greenland ice sheet in July 2012We show this exceptional melt was dominated by nonradiative energy fluxesConventional models underestimate melt episodes dominated by nonradiative energy fluxes

AbstractSuspended sediment concentration and transport is modeled for the Mittivakkat Glacier located on Ammassalik Island, South-East Greenland, using a numerical sediment model based on lumped-elements. Empirical equations calculate sediment erosion and deposition within a constant idealized glacier drainage system. The sediment model is forced by observations and an energy balance model based on meteorological observations that provide a simulated Surface Melt and liquid Precipitation available for supra-, en-, sub-, and proglacial flow processes after vertical percolation and potential storage within the snowpack (henceforth SMP) from the glacier surface which is available for subglacial erosion, glaciofluvial transport, and deposition within the drainage system. The idealized drainage system is constrained following the descriptions and conclusions from previous work. A model simulation run for summer 2005 shows that the cumulative modeled suspended sediment transport lies within 3% when compared with observations. Model results show that the temporal changes in the calculated suspended sediment concentrations vary over the melt season in some agreement with measured field data for the summer of 2005. Forcing the sediment model gives a correlation coefficient of 0.89 using observed proglacial meltwater discharge values and the correlation coefficient is 0.63 using modeled supraglacial meltwater runoff. The sediment model successfully captures the observed concentration and transport of suspended sediment which indicates a sufficient sediment reservoir available for transport through the idealized drainage system.

Rainfall at the Greenland ice sheet Summit 14 August 2021, was delivered by an atmospheric river (AR). Extreme surface ablation expanded the all‐Greenland bare ice area to near‐record‐high with snowline climbing up to 788 ± 90 m. Ice sheet wet snow extent reached 46%, a record high for the 15–31 August AMSR data since 2003. Heat‐driven firn deflation averaged 0.14 ± 0.05 m at four accumulation area automatic weather stations (AWSs). Energy budget calculations from AWS data indicate that surface heating from rainfall is much smaller than from either the sensible, latent, net‐longwave or solar energy fluxes. Sensitivity tests show that without the heat‐driven snow‐darkening, melt at 1,840 m would have totaled 28% less. Similarly, at 1,270 m elevation, without the bare ice exposure, melting would have been 51% less. Proglacial river discharge was the highest on record since 2006 for late August and confirms the melt‐sustaining effect of the albedo feedback. While rainfall at Summit station atop of the Greenland Ice Sheet in mid‐August 2021 captured global attention, its direct surface thermal effects were weak and unable to explain the major melt and river discharge that occurred during and after the event. Exceptional heating of the ice sheet first occurred due to the heat transfer from condensation and the elevated air temperature during an atmospheric river (AR) episode. Satellite measurements reveal a rapid retreat of the snowline to higher elevations, exposing a large extent of relatively dark bare ice. Where snow remained, darkening due to wet snow metamorphism was responsible for sustained additional solar heating of the upper ice sheet elevations for the following 2 weeks. Observations from automatic weather stations and satellites, and river gauging, reveal that the AR had an immediate and sustained impact. A mid‐August 2021 Greenland atmospheric river (AR) produced extreme ice sheet snow cover changes and high proglacial river dischargeSurface heating from rainfall is small compared to latent and sensible heating, net longwave radiation or sunlight absorptionMelt‐albedo feedback enhanced upper elevations snow melt under clear skies following the heating delivered by the AR A mid‐August 2021 Greenland atmospheric river (AR) produced extreme ice sheet snow cover changes and high proglacial river discharge Surface heating from rainfall is small compared to latent and sensible heating, net longwave radiation or sunlight absorption Melt‐albedo feedback enhanced upper elevations snow melt under clear skies following the heating delivered by the AR

The Greenland Ice Sheet is the primary source of global Barystatic sea‐level rise, and at least half of its recent mass‐loss acceleration is caused by surface meltwater runoff. Previous studies on surface melt have examined various thermodynamic and dynamic drivers, yet their contributions are not compared using unified observations. We use decade‐long in‐situ measurements from automatic weather stations throughout the ablation zone to assess energy components and identify the leading physical processes in this area. Large melt events exceeding 3σcontribute only ∼2% to total surface melt since 2007. The day‐to‐day variability of all melt is dominated by sensible heat exchange (31 ± 7%) and shortwave radiation (28 ± 5%). Sensible and solar heating correlate with the occurrence of dry and fast gravity‐driven winds. These katabatic winds increase sensible heating of the surface mainly by enhancing vertical mixing that reduces the temperature inversion. The concomitant low humidity and clear skies yield increased solar heating. Greenland's surface melt is a primary contributor to global sea‐level rise. However, the leading causal mechanisms are still unclear. Here, we use decade‐long measurements from automatic weather stations in the most melt‐susceptible regions on the Greenland Ice Sheet to identify dominant energy components and associated physical processes for surface mass loss. Surprisingly, large melt events, such as the one in 2012 during which almost the entire Greenland Ice Sheet experienced surface melt, contribute only 2% to total surface melt since 2007. The day‐to‐day variability of normal‐rate melt events is dominated by sensible heat exchange (31%) and shortwave radiation (28%). They are likely caused by katabatic winds, a gravity‐driven downslope wind that can be forceful and often associated with clear skies. In Greenland, grounds are usually colder than the air above as sunlight gets reflected by snow and ice. These katabatic winds enhance vertical mixing to bring down warm air aloft to heat grounds. With katabatic winds occurring during clear skies, they coincide with periods of increased shortwave radiation. Since high‐melt regions along the ice sheet margins will typically have relatively steep slopes, these downslope winds will continue to have a large impact on Greenland's surface melt in the future. Large melt events contribute little to total surface mass lossDay‐to‐day melt variability is dominated by sensible and solar heatingPrevailing katabatic winds enhance sensible and solar heating Large melt events contribute little to total surface mass loss Day‐to‐day melt variability is dominated by sensible and solar heating Prevailing katabatic winds enhance sensible and solar heating

Mass‐balance estimates of the polar ice sheets presently rely on static ice masks to identify the area under investigation. However, the vintage of available ice masks can differ by more than a decade, and the resolution of the imagery used to delineate ice extent can differ by an order of magnitude, despite evidence of ongoing ice‐sheet retreat. We show that using a fine‐resolution, time‐varying ice mask significantly improves mass‐balance estimates of the northwestern sector of the Greenland Ice Sheet and affects interpretation of local crustal uplift. Accounting for ice margin retreat using a time‐varying ice mask between 2003 and 2015 results in 1.0%–6.8% less ice‐sheet mass loss relative to assuming one of several existing static ice masks. This indicates that mass‐balance estimates that use a static ice mask will progressively overestimate mass loss where the ice sheet is predominantly retreating, meaning a negative bias on mass‐balance. This trend is anticipated to be amplified in a future warming scenario unless updated ice masks are incorporated. For altimetry‐derived mass‐balance estimates, this ice‐mask‐induced bias approaches the magnitude of the ice‐sheet‐wide uncertainty presently associated with spatiotemporal variability in modeled firn compaction. Further, at five Greenland GPS Network (GNET) stations, the ice‐mask‐induced bias is equivalent to 5%–15% of the modeled uplift due to elastic deformation. Given present and projected negative trends in Greenland Ice Sheet mass‐balance and areal extent, we conclude that studies of its mass‐balance should begin incorporating dynamic, periodically updated, fine‐resolution ice masks. This methodological refinement will reduce bias in estimates of both ice‐sheet mass‐balance and crustal uplift. Implementing a time‐varying ice mask in northwestern Greenland between 2003 and 2015 decreases inferred mass loss by up to 6.8%This bias approaches the magnitude of ice‐sheet‐wide mass‐balance uncertainty attributed to spatiotemporal variability in firn compactionThe difference in modeled elastic crustal uplift induced by the choice of ice mask is 5%–15% of the modeled uplift at nearby GNET sites Implementing a time‐varying ice mask in northwestern Greenland between 2003 and 2015 decreases inferred mass loss by up to 6.8% This bias approaches the magnitude of ice‐sheet‐wide mass‐balance uncertainty attributed to spatiotemporal variability in firn compaction The difference in modeled elastic crustal uplift induced by the choice of ice mask is 5%–15% of the modeled uplift at nearby GNET sites

ABSTRACTIce-sheet melting is the primary water source for the proglacial Watson River in southern west Greenland. Discharge from the large, approximately 12,000 km2ice-sheet catchment draining through the Watson River has been monitored since 2006. While this record is of respectable length for a Greenland monitoring effort, it is too short to resolve climate signals. Therefore, we use observed Tasersiaq lake discharge and Kangerlussuaq air temperature to reconstruct annual Watson River discharge back to 1949. The resulting sixty-five-year record shows that average ice-sheet runoff since 2003 has roughly increased by 46 percent relative to the 1949–2002 period. The time series suggests that the five top-ranking discharge years occurred since 2003. The three top-ranking discharge years (2010, 2012, and 2016) are characterized by melt seasons that were both long and intense. Interannual variability more than doubled since 2003, which we speculate to be because of hypsometric runoff amplification enhanced by albedo decrease and decreased firn permeability. The reconstructed time series proves to be a valuable tool for long-term evaluation of Greenland Ice Sheet surface mass balance models. A comparison with freshwater fluxes calculated by a downscaled version of the regional climate model RACMO2 reveals high correlation (r = 0.89), and also shows that the model possibly underestimates runoff by up to 26 percent in above-average melt years.