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	<title>ice shelf melt &#8211; Science</title>
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	<title>ice shelf melt &#8211; Science</title>
	<link>https://scienmag.com</link>
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		<title>Antarctica Is Locked In to Sea-Level Rise by 2100, Machine-Learning Study Finds</title>
		<link>https://scienmag.com/antarctica-is-locked-in-to-sea-level-rise-by-2100-machine-learning-study-finds/</link>
		
		<dc:creator><![CDATA[Thomas Green]]></dc:creator>
		<pubDate>Thu, 08 Oct 2026 11:49:07 +0000</pubDate>
				<category><![CDATA[Earth Science]]></category>
		<category><![CDATA[Antarctic contribution to global sea level]]></category>
		<category><![CDATA[Antarctic Ice Sheet]]></category>
		<category><![CDATA[Antarctic ice sheet melting]]></category>
		<category><![CDATA[Bayesian calibration]]></category>
		<category><![CDATA[climate change adaptation strategies]]></category>
		<category><![CDATA[Climate Change Impact on Antarctica]]></category>
		<category><![CDATA[climate projections]]></category>
		<category><![CDATA[coastal risk]]></category>
		<category><![CDATA[effects of greenhouse gas emission scenarios]]></category>
		<category><![CDATA[emissions scenarios]]></category>
		<category><![CDATA[ice shelf melt]]></category>
		<category><![CDATA[ice-sheet model uncertainties]]></category>
		<category><![CDATA[ice-sheet modelling]]></category>
		<category><![CDATA[implications of irreversible ice loss]]></category>
		<category><![CDATA[ISMIP6]]></category>
		<category><![CDATA[ISMIP6 climate models]]></category>
		<category><![CDATA[long-term sea-level rise predictions]]></category>
		<category><![CDATA[Machine learning]]></category>
		<category><![CDATA[machine-learning in climate modeling]]></category>
		<category><![CDATA[marine ice-sheet instability]]></category>
		<category><![CDATA[sea level rise]]></category>
		<category><![CDATA[sea level rise projections]]></category>
		<category><![CDATA[sea-level rise by 2100]]></category>
		<category><![CDATA[sliding laws]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=247454</guid>

					<description><![CDATA[A machine-learning analysis of ice-sheet model ensembles shows the Antarctic Ice Sheet is very likely committed to mass loss by 2100 even under the most aggressive emissions cuts, with high-emissions pathways capable of driving up to 25.4 centimetres of sea-level rise.]]></description>
										<content:encoded><![CDATA[<p>The Antarctic Ice Sheet, Earth&#8217;s largest reservoir of freshwater and the equivalent of 57.9 metres of potential global sea-level rise, is now very likely committed to losing mass through the end of this century no matter how aggressively humanity cuts emissions, according to a new study published in Nature Geoscience. Using a machine-learning emulation framework trained on the Ice Sheet Model Intercomparison Project (ISMIP6), researchers led by Yucheng Lin of City University of Hong Kong and CSIRO Environment quantified, for the first time, how each individual physical assumption in ice-sheet models cascades into projection uncertainty. Their observation-calibrated results suggest a probability of at least 0.92 that the ice sheet continues losing mass by 2100 even under the most ambitious emissions-reduction scenario, SSP1-1.9, rising to at least 0.95 under the very high-emissions SSP5-8.5 pathway.</p>
<p>The central problem the team tackled is that Antarctic sea-level projections have long been dominated by a bewildering spread of outcomes. In ISMIP6, the flagship model intercomparison feeding into the IPCC Sixth Assessment Report, projections of the Antarctic contribution to sea-level rise by 2100 under SSP5-8.5 ranged from less than minus 7 centimetres to more than 40 centimetres of sea-level equivalent, with models outside the exercise suggesting an even broader range. Traditional intercomparison exercises follow a &#8216;one model, one vote&#8217; approach, which can bias ensemble results towards whichever modelling choices happen to be adopted by more research groups, regardless of their physical plausibility or consistency with observations. Until now, the contribution of each individual modelling decision to that spread had never been systematically disentangled.</p>
<p>To break the problem open, the researchers built a statistical emulator that mimics the behaviour of computationally expensive numerical ice-sheet models. They compiled a database of 340 ISMIP6-2300 simulations from 41 model submissions, spanning 29,240 samples across 86 annual time steps, and characterised each simulation with 21 features: 18 ice-dynamical modelling choices, plus the driving atmosphere-ocean general circulation model, the emissions scenario and the projection year. After testing six machine-learning algorithms with tenfold cross validation, they adopted Gradient Boosting, which sequentially builds decision trees that each correct the errors of the last. The emulator achieved a coefficient of determination of 0.98, outperforming previous long-short-term-memory and Gaussian-process emulators, and its 95 per cent credible intervals captured 95.5 per cent of true simulation values. Running at roughly 30,000 samples per second on a laptop, it allowed the team to generate ensembles of half a million projections that would have been computationally impossible with full numerical models.</p>
<p>The variance decomposition delivered a striking verdict: in raw, uncorrected simulations, ice-model features dominate twenty-first-century Antarctic uncertainty, accounting for an average of 64 per cent of projection variance. Sliding laws, the equations relating basal shear stress to sliding velocity at the ice-bed interface, alone contributed 21 per cent of the variance between 2015 and 2100. A Budd-type sliding law yielded 5.0 plus or minus 4.2 centimetres more sea-level rise by 2100 than a linear Weertman law. Ice-shelf melt parameterizations, which translate coarse ocean warming signals into spatially variable basal melt beneath floating ice, contributed another 20 per cent; an observation-calibrated linear thermal forcing function produced 7.8 plus or minus 5.2 centimetres more than the ISMIP6 standard non-local parameterization. Numerical choices mattered too: running models at 1-kilometre resolution instead of 8 kilometres reduced projected sea-level rise by 4.3 plus or minus 2.8 centimetres, because fine grids better resolve the topography controlling ice streams and grounding-line migration.</p>
<p>The picture changes when drift-corrected simulations are used, in which each model&#8217;s control-run variability is subtracted to isolate the dynamical response to climate change. Because control-run variability accounts for 45 per cent of raw-simulation variance, removing it cuts ice-model feature uncertainty to 23 per cent and elevates climate forcing to nearly half of the total, with the choice of atmosphere-ocean model contributing 31 per cent and global mean surface temperature 17 per cent. The team also quantified how the spatial geometry of Antarctic mass loss, which generates gravitational, rotational and deformational sea-level fingerprints, adds location-specific uncertainty. For London and Singapore the fingerprint effect contributes less than 1 per cent of variance, rising to 5 per cent in New York and 3 per cent in Shanghai, but near the ice sheet itself it becomes a major factor, reaching 17 per cent in Buenos Aires and 21 per cent in Melbourne.</p>
<p>Probing the relationship between warming and ice loss, the study found it to be delayed, non-stationary and strongly nonlinear. Distinguishable differences between emissions scenarios in Antarctic sea-level contribution emerge only late in the century, long after global temperature trajectories diverge, reflecting the substantial forcing needed to initiate mass loss and the lag between climate perturbation and dynamical response. By 2100, the sensitivity of Antarctic sea-level rise to warming more than an order of magnitude higher in the calibrated high-end analysis: from 0.56 plus or minus 0.01 centimetres per degree Celsius at 0 to 2 degrees of warming to 5.97 plus or minus 0.01 centimetres per degree at 2 to 4.5 degrees. The choice of climate model also exerts dominant control over whether Antarctica gains or loses mass by 2100. Notably, UKESM1-0-LL, the model producing the highest twenty-first-century warming of any tested, yields net mass gain from enhanced snowfall and modest regional ocean warming, a transient gain the authors caution is confined to this century before sustained ocean-driven dynamic losses overtake surface accumulation.</p>
<p>A key innovation was Bayesian calibration against satellite observations. Many raw ISMIP6 simulations fail to reproduce observed mass-loss trends or exhibit unrealistic model drift, partly because they are initialised to fit static rather than transient observations. The team updated their prior assumptions using the observed 2002-2021 Antarctic mass-loss rate of 0.44 plus or minus 0.04 millimetres per year of sea-level equivalent, measured by the GRACE and GRACE Follow-On gravimetry missions. Calibration reduced projection uncertainty by 30 to 42 per cent and raised median projections by 15 to 25 per cent, while the posterior probabilities shifted decisively against sliding-law formulations, such as pseudo-plastic and Budd variants, that produce unrealistically fast ice flow. Crucially, the calibrated projections raise the probability of committed mass loss under SSP1-1.9 from 0.80 to 0.92, indicating that warming-enhanced snowfall is very unlikely to compensate for ocean-driven losses.</p>
<p>For risk-averse planners responsible for long-lived infrastructure, the team also characterised a physically plausible high-end pathway consistent with satellite observations. This posterior high-end scenario, defined as the top 1 per cent of calibrated 2100 projections under SSP5-8.5, unfolds as a cascade: a highly sensitive ocean warming response coincides with a sensitive melt parameterization, converting warming into vigorous basal melt; paired with a strongly plastic sliding law that lowers basal resistance, ice discharge accelerates, particularly under higher-order stress-balance formulations; and subgrid-scale melt and ice-shelf collapse then reduce buttressing, enabling rapid grounding-line retreat and potentially triggering marine ice-sheet instability. Together these mechanisms yield a median of 15.7 centimetres of sea-level rise by 2100, with a 95th-percentile value of 25.4 centimetres, and a probability of at least 0.99 that higher emissions produce higher sea-level rise than the lowest scenario.</p>
<p>The authors emphasise that several processes remain largely unexplored within ISMIP6, including marine ice cliff instability, coupled ice-ocean-atmosphere interactions, high-resolution surface mass balance, ice damage mechanisms and subglacial hydrology, any of which could accelerate mass loss once incorporated into future experiments. Their framework, they argue, offers a template for transparent documentation of ice-model features and a route to integrating new process representations coherently. The bottom line for coastal communities is sobering but actionable: Antarctic mass loss this century is effectively locked in, higher emissions directly amplify near-term risk with a probability of at least 0.89, and managing that risk demands both rapid emissions reductions in line with the Paris Agreement and sharper constraints on the modelling choices, climate model selection, sliding laws and ice-shelf melt parameterizations, that drive the deepest uncertainties in sea-level projections.</p>
<p><strong>Subject of Research:</strong> Committed twenty-first-century mass loss of the Antarctic Ice Sheet and its contribution to sea-level rise</p>
<p><strong>Article Title:</strong> Committed Antarctic Ice Sheet mass loss by the end of the twenty-first century</p>
<p><strong>Article References:</strong> Lin, Y., Zhang, X., Golledge, N. R., Kopp, R. E., Church, J. A., Jin, Y., Zhao, C., &amp; Stokes, C. R. (2026). Committed Antarctic Ice Sheet mass loss by the end of the twenty-first century. <em>Nature Geoscience</em>. <a href="https://doi.org/10.1038/s41561-026-02102-1" rel="noopener noreferrer">https://doi.org/10.1038/s41561-026-02102-1</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1038/s41561-026-02102-1" rel="noopener noreferrer">10.1038/s41561-026-02102-1</a></p>
<p><strong>Keywords:</strong> Antarctic Ice Sheet, sea-level rise, ice-sheet modelling, ISMIP6, machine learning, Bayesian calibration, emissions scenarios, ice-shelf melt, sliding laws, marine ice-sheet instability, climate projections, coastal risk</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">247454</post-id>	</item>
		<item>
		<title>Mapping the Hidden Freshwater of East Antarctic Glaciers in Three Dimensions</title>
		<link>https://scienmag.com/mapping-the-hidden-freshwater-of-east-antarctic-glaciers-in-three-dimensions/</link>
		
		<dc:creator><![CDATA[Violet Maxwell]]></dc:creator>
		<pubDate>Sun, 20 Sep 2026 21:24:35 +0000</pubDate>
				<category><![CDATA[Earth Science]]></category>
		<category><![CDATA[Antarctic Bottom Water]]></category>
		<category><![CDATA[Antarctic glacier meltwater mapping]]></category>
		<category><![CDATA[challenges in tracking Antarctic glacier melt]]></category>
		<category><![CDATA[climate change]]></category>
		<category><![CDATA[East Antarctic coastal sea circulation]]></category>
		<category><![CDATA[East Antarctica]]></category>
		<category><![CDATA[end-member-independent hydrographic parameterization]]></category>
		<category><![CDATA[freshwater penetration in Antarctic water column]]></category>
		<category><![CDATA[glacial meltwater]]></category>
		<category><![CDATA[glacial meltwater contribution to Southern Ocean]]></category>
		<category><![CDATA[hydrography]]></category>
		<category><![CDATA[ice shelf melt]]></category>
		<category><![CDATA[impact of Antarctic melt on sea-level rise]]></category>
		<category><![CDATA[implications for climate change and sea-level projections]]></category>
		<category><![CDATA[meltwater influence on Antarctic marine ecosystems]]></category>
		<category><![CDATA[ocean circulation]]></category>
		<category><![CDATA[ocean tracer-based meltwater analysis]]></category>
		<category><![CDATA[oceanography]]></category>
		<category><![CDATA[sea level rise]]></category>
		<category><![CDATA[Southern Ocean]]></category>
		<category><![CDATA[subglacial outflow and grounding line processes]]></category>
		<category><![CDATA[temperature-salinity analysis]]></category>
		<category><![CDATA[three-dimensional ocean hydrography]]></category>
		<category><![CDATA[water mass analysis]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=202784</guid>

					<description><![CDATA[A new end-member-independent method reconstructs the three-dimensional distribution of glacier-derived freshwater across East Antarctic coastal waters, revealing deep meltwater layers and offshore export pathways with fewer assumptions than traditional analyses.]]></description>
										<content:encoded><![CDATA[<p>Beneath the frigid surface waters of East Antarctica, a quiet river of meltwater is spreading through the ocean, and for the first time scientists have reconstructed its full three-dimensional architecture without relying on the assumptions that have long constrained such studies. A new analysis published in Nature Communications introduces an end-member-independent hydrographic parameterization that traces glacier-derived freshwater through the coastal seas of East Antarctica, revealing where melt accumulates, how deeply it penetrates, and how it reshapes the water column. The achievement matters because the fate of Antarctic meltwater is one of the central uncertainties in projections of sea-level rise and Southern Ocean circulation.</p>
<p>Tracking glacial melt in the ocean is deceptively difficult. When ice shelves and glacier termini discharge freshwater, whether as basal melt from floating ice or as subglacial outflow at grounding lines, that water mixes almost immediately with ambient seawater. Oceanographers traditionally quantify the meltwater fraction using tracer-based calculations that require predefined source water types, known as end members. In the classic approach, an analyst assumes the ocean can be described as a mixture of a small number of pure inputs, for example warm deep water, winter-modified shelf water, and pure glacial melt, each with known temperature and salinity. The meltwater fraction is then inferred from the leftover properties that cannot be explained by the mixing of those assumed sources.</p>
<p>The problem is that the answers depend heavily on the choices made. Pick a different deep-water definition, adjust the salinity of the meltwater end member, or allow a glacial ice end member in addition to liquid melt, and the estimated freshwater fractions can shift substantially. In regions with complex hydrography, where Antarctic Bottom Water formation, modified Circumpolar Deep Water intrusions, and seasonal sea-ice processes all compete to shape water properties, the ambiguity grows worse. East Antarctica, with its thousands of kilometers of ice front and sparse observations, has been especially vulnerable to these methodological uncertainties, leaving the meltwater budget of the region poorly constrained.</p>
<p>The new study sidesteps the end-member problem entirely. Rather than prescribing source water types and solving for their proportions, the researchers developed a parameterization that identifies glacier-derived freshwater directly from the structure of the hydrographic data itself. The technique exploits the fact that glacial melt alters temperature and salinity along characteristic lines in property space: because meltwater enters the ocean at the freezing point and carries negligible salt, its addition moves water masses in predictable directions in temperature-salinity coordinates. By parameterizing these trajectories without fixing the end points, the method estimates the freshwater contribution at every measured depth, producing not just a surface map but a three-dimensional reconstruction of the meltwater field.</p>
<p>The reconstruction is built from the vast archive of hydrographic observations collected across the East Antarctic shelf and slope, including conductivity-temperature-depth profiles, seal-mounted sensor data, and ship-based measurements gathered over multiple decades. Each profile is processed to separate the meltwater signal from other processes that also modify salinity, such as sea-ice formation and melting, precipitation, and the intrusion of off-shelf water masses. The end-member-independent framework then assembles these individual column estimates into a continuous three-dimensional field, resolved in longitude, latitude, and depth, that captures the horizontal pathways and vertical distribution of glacier-derived freshwater around the continent&#8217;s eastern half.</p>
<p>The resulting picture is striking. Meltwater is not distributed uniformly along the coast. Instead, the reconstruction shows concentrated lenses and layers of freshwater that accumulate at intermediate depths, typically well below the surface, where melt-laden water spreads neutrally according to its density. Along several major glacier systems, plumes of meltwater extend tens to hundreds of kilometers offshore, following the contours of shelf banks and canyon systems that steer the flow. In some locations the freshwater signal reaches the upper slope, hinting that glacial melt from East Antarctica may be exported into the broader Southern Ocean circulation rather than being trapped locally over the shelf, as older, two-dimensional assessments often implied.</p>
<p>These vertical details carry significant implications for ocean physics and climate. Freshwater stabilizes the water column by reducing surface density, which suppresses vertical mixing and can alter the formation of dense shelf waters that ultimately feed Antarctic Bottom Water, a key component of the global overturning circulation. By quantifying where melt accumulates at depth, the reconstruction allows scientists to test whether meltwater is interfering with bottom-water formation sites, potentially weakening the engine that ventilates the deep ocean and stores carbon and heat on centennial timescales. The three-dimensional view also provides essential validation data for ocean and coupled climate models, which historically have struggled to represent meltwater pathways realistically and often rely on crude runoff schemes at the ice-ocean boundary.</p>
<p>The methodological advance is as important as the observational findings. Because the parameterization does not require users to specify source water properties, it can be applied consistently across regions and through time, enabling fair comparisons between sectors of Antarctica and between different observational eras. Consistency is precisely what large-scale budget studies need: aggregating meltwater estimates produced with different end-member choices has been a persistent obstacle to constructing a continent-wide picture. An end-member-independent approach also reduces the risk of circular reasoning, in which assumptions about meltwater properties determine the meltwater fraction that is then used to infer melt rates. The authors show that their framework yields robust meltwater distributions under a range of environmental conditions, offering a template that can be transferred to other glacier-influenced seas.</p>
<p>For East Antarctica specifically, the study arrives at a pivotal moment. Long considered more stable than the marine-terminating glaciers of West Antarctica, the eastern ice sheet is increasingly showing signs of change, with warm modified deep water reaching the flanks of some major ice shelves and several basins identified as potential candidates for future accelerated retreat. A reliable reconstruction of where glacier-derived freshwater already enters the ocean provides both a baseline against which future change can be measured and a diagnostic of which systems are presently discharging melt at elevated rates. If meltwater export from the region strengthens, the three-dimensional fields produced by this method will help determine how quickly that signal propagates into the abyssal circulation.</p>
<p>The work also demonstrates how reanalysis of existing observations can yield new science without new expeditions. Decades of shipboard hydrography and the growing record of instrumented seals have created an underexploited treasure trove for the Southern Ocean; the challenge has been extracting subtle signals, like glacial freshwater, from noisy, unevenly sampled data. By turning a long-standing methodological weakness, the dependence on assumed source waters, into a solved problem, the researchers have converted scattered profiles into a coherent, multidimensional dataset of one of climate science&#8217;s most consequential tracers. As observations accumulate and parameterization techniques mature, the approach promises continuously updated maps of Antarctic meltwater, giving scientists and policymakers a clearer view of how the ice sheet, the ocean, and the global climate system are entangling beneath the surface of the far South.</p>
<p><strong>Subject of Research:</strong> Three-dimensional mapping of glacier-derived freshwater in East Antarctic coastal waters using an end-member-independent hydrographic method</p>
<p><strong>Article Title:</strong> Three-dimensional reconstruction of glacier-derived freshwater in East Antarctica using an end-member-independent hydrographic parameterization</p>
<p><strong>Article References:</strong> Watanabe, Y. W., Hirano, D., Ohashi, Y., Sugita, M., Nakano, Y., Makabe, R., &amp; Mizobata, K. (2026). Three-dimensional reconstruction of glacier-derived freshwater in East Antarctica using an end-member-independent hydrographic parameterization. <em>Nature Communications, 17</em>(1), Article 9498. <a href="https://doi.org/10.1038/s41467-026-77441-z" rel="noopener noreferrer">https://doi.org/10.1038/s41467-026-77441-z</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1038/s41467-026-77441-z" rel="noopener noreferrer">10.1038/s41467-026-77441-z</a></p>
<p><strong>Keywords:</strong> East Antarctica, glacial meltwater, hydrography, ice shelf melt, Southern Ocean, Antarctic Bottom Water, temperature-salinity analysis, sea-level rise, ocean circulation, water mass analysis, climate change, oceanography</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">202784</post-id>	</item>
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