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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.

Present understanding of Greenland's subglacial geology is derived mostly from interpolation of geologic mapping of its ice‐free margins and unconstrained by geophysical data. Here we refine the extent of its geologic provinces by synthesizing geophysical constraints on subglacial geology from seismic, gravity, magnetic and topographic data. North of 72°N, no province clearly extends across the whole island, leaving three distinct subglacial regions yet to be reconciled with margin geology. Geophysically coherent anomalies and apparent province boundaries are adjacent to the onset of faster ice flow at both Petermann Glacier and the Northeast Greenland Ice Stream. Separately, based on their subaerial expression, dozens of unusually long, straight and sub‐parallel subglacial valleys cross Greenland's interior and are not yet resolved by current syntheses of its subglacial topography. The Greenland Ice Sheet obscures the rocks beneath 79% of Greenland. By necessity, scientists have relied mostly on studying the rocks exposed along Greenland's edge to understand the island's interior geology. We examine geophysical data from seismometers on the ground, satellites that measure Earth's gravity and magnetic fields and surface topography, and aircraft that measure those same properties and ice thickness. We draw a new map of Greenland's geology beneath the ice sheet by examining where those data show similar signals regarding the nature of the underlying rock, and where they could be related to mapped rock exposures. We also find evidence of some areas with geophysical expressions that are distinct from the rocks found at the island's edges. Some geologic structures, which are entirely covered by ice, may affect how ice flows from Greenland's vast interior toward its coast. Finally, we identify many valleys beneath the ice that are very long and often aligned with each other, but which are not yet fully captured in present maps of the topography beneath the ice. We produced a new synthesis of subglacial boundaries for Greenland's geologic provinces from seismic, gravity, magnetic and topography dataThree subglacial regions in central and northern Greenland cannot yet be reconciled with surface‐exposed geologic provincesWe find evidence for a large subglacial valley network that is not fully resolved by subglacial topography syntheses for Greenland We produced a new synthesis of subglacial boundaries for Greenland's geologic provinces from seismic, gravity, magnetic and topography data Three subglacial regions in central and northern Greenland cannot yet be reconciled with surface‐exposed geologic provinces We find evidence for a large subglacial valley network that is not fully resolved by subglacial topography syntheses for Greenland

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 present the first 1992–2020 record of Greenland Ice Sheet (GrIS) mass balance derived from multisatellite Ku‐band altimetry. We employ an empirical approach as an alternative detailed to radar‐propagation modeling, and instead convert elevation changes observed by radar altimetry into mass changes using spatiotemporal calibration fields. This calibration field is derived from a machine learning approach that optimizes the prediction of a previously published mass balance field as a function of ice sheet variables. Our mass balance record shows a GrIS contribution of 12.1 ± 2.3 mm sea‐level equivalent since 1992, with more than 80% of this contribution occurring after 2003. Our record also suggests that the 2017 hydrological year is the first year in the 21st century which, within uncertainties, the GrIS was in balance. Overall, the 28‐year radar‐derived mass balance record we present highlights the potential of the method to provide operational mass balance estimates derived from multisatellite Ku‐band altimetry. Earth's land ice masses are shrinking due to climate change. The Greenland Ice Sheet (GrIS) has been a major contributor to sea‐level rise in recent years. Earth‐observing satellites have enabled us to monitor ice‐sheet changes, but common problems for these estimates of ice‐sheet mass balance are mission gaps and changing instrumentation. Since 1991, the European Space Agency has used the same instrumentation for satellite radar altimeters in orbits applicable for monitoring the GrIS. Additionally, before retiring one satellite altimeter, a replacement has been commissioned with a sufficient timespan of overlapping measurements to estimate offsets between satellites. The resulting satellite altimetry record can be processed to provide a lengthy, and consistent, record of ice‐sheet elevation and volume changes. Here, we apply machine learning to convert radar‐derived volume changes to radar‐derived mass changes. This novel mass balance record shows a contribution from the GrIS to global sea level rise of 12.1 ± 2.3 mm since 1992, with more than 80% of this contribution originating after 2003. The method we present is an alternative to modeling both radar propagation and firn compaction, and provides a path toward operational mass‐balance estimates from satellite altimetry. Novel estimate of Greenland Ice Sheet mass balance from calibrated multisatellite Ku‐band altimetryTotal eustatic sea‐level rise contribution of 12.1 ± 2.3 mm from the ice sheet since 1992Atmospheric circulation can shift ice‐sheet mass balance by 3σwithin 5 years Novel estimate of Greenland Ice Sheet mass balance from calibrated multisatellite Ku‐band altimetry Total eustatic sea‐level rise contribution of 12.1 ± 2.3 mm from the ice sheet since 1992 Atmospheric circulation can shift ice‐sheet mass balance by 3σwithin 5 years

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