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More than 60% of meteorite finds on Earth originate from Antarctica. Using a data-driven analysis that identifies meteorite-rich sites in Antarctica, we show climate warming causes many extraterrestrial rocks to be lost from the surface by melting into the ice sheet. At present, approximately 5,000 meteorites become inaccessible per year (versus ~1,000 finds per year) and, independent of the emissions scenario, ~24% will be lost by 2050, potentially rising to ∼76% by 2100 under a high-emissions scenario.

The land ice contribution to global mean sea level rise has not yet been predicted1using ice sheet and glacier models for the latest set of socio-economic scenarios, nor using coordinated exploration of uncertainties arising from the various computer models involved. Two recent international projects generated a large suite of projections using multiple models2–8, but primarily used previous-generation scenarios9and climate models10, and could not fully explore known uncertainties. Here we estimate probability distributions for these projections under the new scenarios11,12using statistical emulation of the ice sheet and glacier models. We find that limiting global warming to 1.5 degrees Celsius would halve the land ice contribution to twenty-first-century sea level rise, relative to current emissions pledges. The median decreases from 25 to 13 centimetres sea level equivalent (SLE) by 2100, with glaciers responsible for half the sea level contribution. The projected Antarctic contribution does not show a clear response to the emissions scenario, owing to uncertainties in the competing processes of increasing ice loss and snowfall accumulation in a warming climate. However, under risk-averse (pessimistic) assumptions, Antarctic ice loss could be five times higher, increasing the median land ice contribution to 42 centimetres SLE under current policies and pledges, with the 95th percentile projection exceeding half a metre even under 1.5 degrees Celsius warming. This would severely limit the possibility of mitigating future coastal flooding. Given this large range (between 13 centimetres SLE using the main projections under 1.5 degrees Celsius warming and 42 centimetres SLE using risk-averse projections under current pledges), adaptation planning for twenty-first-century sea level rise must account for a factor-of-three uncertainty in the land ice contribution until climate policies and the Antarctic response are further constrained.

The Antarctic ice sheet has been losing mass over past decades through the accelerated flow of its glaciers, conditioned by ocean temperature and bed topography. Glaciers retreating along retrograde slopes (that is, the bed elevation drops in the inland direction) are potentially unstable, while subglacial ridges slow down the glacial retreat. Despite major advances in the mapping of subglacial bed topography, significant sectors of Antarctica remain poorly resolved and critical spatial details are missing. Here we present a novel, high-resolution and physically based description of Antarctic bed topography using mass conservation. Our results reveal previously unknown basal features with major implications for glacier response to climate change. For example, glaciers flowing across the Transantarctic Mountains are protected by broad, stabilizing ridges. Conversely, in the marine basin of Wilkes Land, East Antarctica, we find retrograde slopes along Ninnis and Denman glaciers, with stabilizing slopes beneath Moscow University, Totten and Lambert glacier system, despite corrections in bed elevation of up to 1 km for the latter. This transformative description of bed topography redefines the high- and lower-risk sectors for rapid sea level rise from Antarctica; it will also significantly impact model projections of sea level rise from Antarctica in the coming centuries.

In some areas of Antarctica, blue‐colored bare ice is exposed at the surface. These blue ice areas (BIAs) can trap meteorites or old ice and are vital for understanding the climatic history. By combining multi‐sensor remote sensing data (MODIS, RADARSAT‐2, and TanDEM‐X) in a deep learning framework, we map blue ice across the continent at 200‐m resolution. We use a novel methodology for image segmentation with “noisy” labels to learn an underlying “clean” pattern with a neural network. In total, BIAs cover ca. 140,000 km2(∼1%) of Antarctica, of which nearly 50% located within 20 km of the grounding line. There, the low albedo of blue ice enhances melt‐water production and its mapping is crucial for mass balance studies that determine the stability of the ice sheet. Moreover, the map provides input for fieldwork missions and can act as constraint for other geophysical mapping efforts. While most of the continent of Antarctica is covered by snow, in some areas, ice is exposed at the surface, with a typical blue color. At lower elevations, blue ice enhances melt‐water production, which is important for studying the future of the ice sheet. Moreover, scientific teams frequently visit blue ice areas (BIAs) as they act as traps for meteorites and very old ice. In this study, we map the extent and the exact location of BIAs using various satellite observations. These diverse observations are efficiently combined in an artificial intelligence algorithm. We develop the algorithm so that it can learn to map blue ice even though existing training labels, which teach the algorithm what blue ice looks like, are imperfect. We quantify that the new map scores better on various performance metrics compared to the current most‐used blue ice map. Moreover, for the first time, we estimate uncertainties of the detection of blue ice. The map indicates that ca. 1% of the surface of Antarctica exposes blue ice and will be important for fieldwork missions and understanding surface processes leading to melt and potential sea level rise. We map blue ice areas in Antarctica by combining multi‐sensor satellite observations in a convolutional neural networkBlue ice covers ca. 140,000 km2(∼1%) of Antarctica, of which ca. 50% located in the grounding zoneOur map will improve mass balance estimates and studies on ice‐shelf stability, and will support searches for meteorites or old ice We map blue ice areas in Antarctica by combining multi‐sensor satellite observations in a convolutional neural network Blue ice covers ca. 140,000 km2(∼1%) of Antarctica, of which ca. 50% located in the grounding zone Our map will improve mass balance estimates and studies on ice‐shelf stability, and will support searches for meteorites or old ice

The buttressing potential of ice shelves is modulated by changes in subshelf melting, in response to changing ocean conditions. We analyze the temporal variability in subshelf melting using an autonomous phase‐sensitive radio‐echo sounder near the grounding line of the Roi Baudouin Ice Shelf in East Antarctica. When combined with additional oceanographic evidence of seasonal variations in the stratification and the amplification of diurnal tides around the shelf break topography (Gunnerus Bank), the results suggest an intricate mechanism in which topographic waves control the seasonal melt rate variability near the grounding line. This mechanism has not been considered before and has the potential to enhance local melt rates without advecting different water masses. As topographic waves seem to strengthen in a stratified ocean, the freshening of Antarctic surface water, predicted by observations and models, is likely to increase future basal melting in this area. Ice shelves (or the floating parts of the Antarctic ice sheet) lose primarily mass through melting at their bottom in contact with the ocean. This thins them and makes them more vulnerable to potential collapse. To understand the processes governing such thinning, direct and long‐time measurements are essential. Here we report on the first high‐resolution time series of direct melt measurements on the Roi Baudouin Ice Shelf in Dronning Maud Land during 2016. We find that subshelf melt varies on both seasonal and daily time scales. Temporal variations stem from topographical ocean waves that originate on the continental shelf and transfer ocean properties without time delay within the ice shelf cavity. Therefore, seasonal variations highly depend on the presence/absence of sea ice in front of the ice shelf, which impact the strength of topographical waves. This mechanism is highly efficient at increasing the ice‐ocean exchanges and may explain regional differences in ice shelf melt. Variation in ice shelf basal melt rates is observed over a broad range of time scales, from tidal to seasonalTopographic shelf waves dominate the observed temporal melt rate variability in the study regionSea ice concentration and tidal currents modulate the magnitude and temporal variation of melt rates

Even if anthropogenic warming were constrained to less than 2 °C above pre-industrial, the Greenland and Antarctic ice sheets will continue to lose mass this century, with rates similar to those observed over the past decade. However, nonlinear responses cannot be excluded, which may lead to larger rates of mass loss. Furthermore, large uncertainties in future projections still remain, pertaining to knowledge gaps in atmospheric (Greenland) and oceanic (Antarctica) forcing. On millennial timescales, both ice sheets have tipping points at or slightly above the 1.5–2.0 °C threshold; for Greenland, this may lead to irreversible mass loss due to the surface mass balance–elevation feedback, whereas for Antarctica, this could result in a collapse of major drainage basins due to ice-shelf weakening.

ABSTRACTGRANTISM (GReenland and ANTarctic Ice Sheet Model) is an educational Excel™ model introduced by Pattyn (2006). Here, GRANTISM is amended to simulate the Svalbard-Barents-Sea Ice Sheet during the Last Glacial Maximum, an analogue for the contemporary West Antarctic Ice Sheet. A new name, “GRANTSISM,” is suggested; the added S represents Svalbard. GRANTSISM introduces students of bachelor's or master's programs in Earth sciences (first or second cycle program in the Bologna system for higher education), but with little or no background in numerical modeling, to basic ice sheet modeling. GRANTSISM provides hands-on learning experiences related to ice sheet dynamics in response to climate forcing, and fosters understanding of processes and feedbacks. GRANTSISM was successfully used in noncompulsory courses in which students have been able to reproduce paleo-ice sheet evolution scenarios discussed here as examples. Students progressed further by designing, developing, and analyzing their own modeling scenarios. Here, we describe GRANTSISM and report on how learning activities with GRANTSISM were assessed by students who had no prior experience in ice sheet modeling. The response rate for a noncompulsory survey of the learning activity was less than 40%. A subsequent control experiment with a compulsory survey, however, showed the same patterns of answers, so the student response is considered representative. First, GRANTSISM is concluded to be a highly attractive tool to introduce learners with an interest in ice sheet behaviorto ice sheet modeling. Second, it triggers an interest for more in-depth learning experiences related to numerical ice sheet modeling.

Antarctic ice rises originate from the contact between ice shelves and one of the numerous topographic highs emerging from the edge of the continental shelf. While investigations of the Raymond effect indicate their millennial‐scale stability, little is known about their formation and their role in ice shelf stability. Here we present for the first time the simulation of an ice rise using the BISICLES model. The numerical results successfully reproduce several field‐observable features, such as the substantial thinning downstream of the ice rise and the successive formation of a promontory and ice rise with stable radial ice flow center, showing that ice rises are formed during the ice sheet deglaciation. We quantify the ice rise buttressing effect, found to be mostly transient, delaying grounding line retreat significantly but resulting in comparable steady state positions. We demonstrate that ice rises are key in controlling simulations of Antarctic deglaciation. First‐time numerical simulation of the formation of an ice riseIce rises are formed during the deglaciation of an ice sheetIce rise buttressing may delay ice sheet retreat to several millennia

The limited number of surface mass balance (SMB) observations in the Antarctic inland hampers estimates of ice‐sheet contribution to global sea level and locations with million‐year‐old ice. We present finely resolved SMB over the past three centuries in a low‐accumulation region with significant depth hoar formation on Dome Fuji derived from ∼1,100 km of microwave radar stratigraphy dated with a firn core. The regional‐mean SMB over the past 264 years is estimated to ∼22.5 ± 3.3 kg m−2a−1, but with large local variability of up to 30%. We found that local SMB is negatively correlated with surface slope at scales of a few hundred meters, resulting in anomalous zones of low SMB which represent as much as 8–10% of the total SMB on the inland plateau if the SMB‐slope relationship is more widely valid. This impact should be investigated further to improve estimates of Antarctic mass balance and sea‐level contribution. Sampling the world's Oldest Ice (more than 1 million years) is crucial for understanding why pacing of glacier‐interglacial cycles has changed in the past. Such ice will be preserved at the base of the Antarctic ice‐sheet interior, though its location depends on many factors, including snow accumulation rate. We mapped snow accumulation in the Dome Fuji region, using radar‐detected snow layers dated with volcanic signals in ice cores. Although climate models indicate a very low and nearly uniform snow accumulation in this region, the observations show large variations of up to about 30% which we found to be related to local surface slope at a scale of a kilometer or less. This new knowledge contributes to better locate Oldest Ice and to improve estimates of ice‐sheet mass changes and its contributions to global sea level. Ultrawide band microwave radar reveals spatially highly variable surface mass balance (SMB) over the past three centuries in inland AntarcticaSMB anomalies resulting from local surface slopes may represent as much as 8–10% of the total SMB on the inland plateauThe new SMB data have direct implications for the search for million‐year‐old ice in the Dome Fuji area, East Antarctica Ultrawide band microwave radar reveals spatially highly variable surface mass balance (SMB) over the past three centuries in inland Antarctica SMB anomalies resulting from local surface slopes may represent as much as 8–10% of the total SMB on the inland plateau The new SMB data have direct implications for the search for million‐year‐old ice in the Dome Fuji area, East Antarctica

Projections of the sea level contribution from the Greenland and Antarctic ice sheets (GrIS and AIS) rely on atmospheric and oceanic drivers obtained from climate models. The Earth System Models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6) generally project greater future warming compared with the previous Coupled Model Intercomparison Project phase 5 (CMIP5) effort. Here we use four CMIP6 models and a selection of CMIP5 models to force multiple ice sheet models as part of the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6). We find that the projected sea level contribution at 2100 from the ice sheet model ensemble under the CMIP6 scenarios falls within the CMIP5 range for the Antarctic ice sheet but is significantly increased for Greenland. Warmer atmosphere in CMIP6 models results in higher Greenland mass loss due to surface melt. For Antarctica, CMIP6 forcing is similar to CMIP5 and mass gain from increased snowfall counteracts increased loss due to ocean warming. The melting of the Greenland and Antarctic ice sheets (GrIS and AIS) will result in higher sea level in the future. How sea level will change depends in part on how the atmosphere and ocean warm and how this affects the ice sheets. We use multiple ice sheet models to estimate possible future sea levels under climate scenarios from the models participating in the new Coupled Model Intercomparison Project phase 6 (CMIP6), which generally indicate a warmer world that the previous effort (CMIP5). Our results show that the possible future sea level change due Antarctica is similar for CMIP5 and CMIP6, but the warmer atmosphere in CMIP6 models leads to higher sea‐level contributions from Greenland by the end of the century. We compare results from an ice sheet model inter‐comparison forced using Coupled Model Intercomparison Project phase 6 and phase 5 climate projectionsProjected sea level at 2100 is higher for Greenland under CMIP6 scenarios than CMIP5, but similar for Antarctica under both scenariosCMIP6 warmer climate results in increased Greenland surface melt while increased snowfall mitigates loss from ocean warming for Antarctica We compare results from an ice sheet model inter‐comparison forced using Coupled Model Intercomparison Project phase 6 and phase 5 climate projections Projected sea level at 2100 is higher for Greenland under CMIP6 scenarios than CMIP5, but similar for Antarctica under both scenarios CMIP6 warmer climate results in increased Greenland surface melt while increased snowfall mitigates loss from ocean warming for Antarctica

The Antarctic ice sheet (AIS) lies on a solid Earth that displays large spatial variations in rheological properties, with a thin lithosphere and low‐viscosity upper mantle (weak Earth structure) beneath West Antarctica and an opposing structure beneath East Antarctica. This contrast is known to have a significant impact on the ice‐sheet grounding‐line stability. Here, we embed within an ice‐sheet model a modified glacial‐isostatic Elastic Lithosphere‐Relaxing Asthenosphere model that considers a dual pattern for the Earth structure beneath West and East Antarctica supplemented with an approximation of gravitationally consistent geoid changes, allowing to approximate near‐field relative sea‐level changes. We show that this elementary GIA model captures the essence of global Self‐Gravitating Viscoelastic solid‐Earth Models (SGVEMs) and compares well with both SGVEM outputs and geodetic observations, allowing to capture the essential features and processes influencing Antarctic grounding‐line stability in a computationally efficient way. In this framework, we perform a probabilistic assessment of the impact of uncertainties in solid‐Earth rheological properties on the response of the AIS to future warming. Results show that on multicentennial‐to‐millennial timescales, spatial variability in solid‐Earth deformation plays a significant role in promoting the stability of the West Antarctic ice sheet (WAIS). However, WAIS collapse cannot be prevented under high‐emissions climate scenarios. On longer timescales and for unmitigated climate scenarios, continent‐wide mass loss projections may be underestimated because spatially uniform Earth models, as typically considered in numerical ice sheet models, will overestimate the stabilizing effect of GIA across East Antarctica, which is characterized by thick lithosphere and high upper‐mantle viscosity. When an ice sheet loses mass, the pressure it exerts on the underlying solid Earth decreases and the Earth surface rebounds. This process, called glacial isostatic adjustment, is important to consider in ice sheet models because it can stabilize an ice sheet undergoing unstable retreat. Most models consider that the solid Earth response to ice mass changes is uniform. However, because of the weak mantle observed beneath West Antarctica, the isostatic rebound in this region is much faster than previously thought. Oppositely, a slow Earth response is observed in East Antarctica, characterized by a more rigid mantle. In this study, we consider this contrast in the isostatic response of the Antarctic solid Earth and show that it plays a crucial role on the future evolution of the Antarctic ice sheet. More specifically, we find that the rapid Earth response in West Antarctica significantly stabilizes the ice sheet on multicentennial‐to‐millennial timescales, even though a collapse of the West Antarctic ice sheet cannot be avoided under high‐emissions climate scenarios. We also find that the slow Earth response in East Antarctica has an influence on long timescales, potentially leading to an underestimation of future mass loss in the East Antarctic ice sheet. We developed an elementary glacial isostatic adjustment (GIA) model featuring a spatially varying Elastic Lithosphere‐Relaxing Asthenosphere model and an approximation to geoid changesOn multicentennial‐to‐millennial timescales, GIA feedbacks significantly promote the stability of the West Antarctic ice sheetOn millennial timescales, considering a uniform Antarctic Earth structure may overestimate the stabilizing role of GIA feedbacks in the East Antarctic ice sheet We developed an elementary glacial isostatic adjustment (GIA) model featuring a spatially varying Elastic Lithosphere‐Relaxing Asthenosphere model and an approximation to geoid changes On multicentennial‐to‐millennial timescales, GIA feedbacks significantly promote the stability of the West Antarctic ice sheet On millennial timescales, considering a uniform Antarctic Earth structure may overestimate the stabilizing role of GIA feedbacks in the East Antarctic ice sheet