The reason previous studies could not answer this question is technical as much as scientific. Most global climate models do not include an interactive Antarctic Ice Sheet; instead, they prescribe where and how much ice flows into the ocean, which means they cannot capture the slow, centennial-to-millennial feedbacks between ocean temperatures and ice dynamics. Höse and her team broke new ground by coupling the CM2Mc Earth system model, developed at the Geophysical Fluid Dynamics Laboratory and modified at Potsdam, to the Parallel Ice Sheet Model, or PISM, which simulates the entire Antarctic Ice Sheet at a horizontal resolution of 16 kilometers. The two models exchange information through the Potsdam Ice-shelf Cavity model, known as PICO, which calculates how fast ice melts from below based on the temperature and salinity of water entering 19 Antarctic drainage basins. Crucially, the meltwater and heat released by the ice sheet are fed back into the ocean model, closing the loop between the two components.

To force an AMOC collapse, the team followed the protocol of the North Atlantic Hosing Model Intercomparison Project, adding artificial freshwater at a rate of 0.3 Sverdrups, roughly 300,000 cubic meters per second, to the surface of the North Atlantic and Arctic Oceans. This deluge of freshwater stratifies the subpolar North Atlantic, suppressing the deep convection that drives the overturning circulation. Within 100 years, the simulated AMOC weakened from about 21.5 Sverdrups to just 5 Sverdrups, a state the researchers treat as a collapse. They then let the coupled model run for another 1,400 years, long enough for the deep ocean and the ice sheet to respond on their own sluggish timescales, while a parallel control run without freshwater forcing provided a baseline against which every anomaly could be measured.

The immediate consequences of the collapse matched what earlier modeling work had established. Northern Hemisphere surface temperatures dropped sharply, by up to 9 degrees Celsius over the North Atlantic, while the Southern Hemisphere warmed as the oceanic heat transport reversed its imbalance. The Intertropical Convergence Zone shifted southward, the mid-latitude westerly winds over the Southern Ocean strengthened, and the Antarctic Circumpolar Current intensified by roughly 20 Sverdrups. Heat accumulated in the subsurface South Atlantic north of 40 degrees south, exactly as the bipolar seesaw theory, developed to explain the antiphased temperature oscillations recorded in Greenland and Antarctic ice cores, would predict. On the surface, then, everything pointed toward trouble for Antarctica.

But the surface is not where the ice sheet lives. What matters for basal melting, the erosion of ice shelves from below, is the temperature of water at depths of 500 to 1,000 meters, near the cavities beneath floating ice. And here the simulation delivered its first counterintuitive finding: for the first eight centuries after the AMOC collapse, subsurface temperatures along most of the Antarctic margin did not warm at all. In fact, they cooled slightly, by around 0.15 degrees Celsius on average, because residual North Atlantic Deep Water, chilled by the collapsed overturning, was carried southward and upwelled near the continent before being swept around the coast by the Circumpolar Current. As a result, basal melt rates actually declined, by up to 100 gigatonnes per year in some periods, and the total Antarctic ice volume barely changed, remaining within the range of natural variability seen in the control run.

The story took another turn around model year 830, when the Southern Ocean underwent a dramatic regime shift. Deep convection, the vertical mixing of the water column, intensified in the Ross Sea and later spread to coastal regions east of the Weddell Sea, releasing centuries of accumulated heat from the deep ocean to the surface. Antarctic Bottom Water formation surged by more than 10 Sverdrups, maximum sea ice extent abruptly shrank by about 40 percent, and sea surface temperatures around the continent rose roughly four times more than they had in the immediate aftermath of the AMOC collapse. Yet paradoxically, this convective heat release cooled the subsurface waters at ice-shelf cavity depths, producing average negative temperature anomalies of 1.4 degrees Celsius along the continental slope. Basal melting dropped further, with a mean decline of 160 gigatonnes per year, and ice shelves grew thicker.

Herein lies the elegant compensating mechanism that kept the ice sheet stable. As reduced basal melting allowed the ice shelves to expand, their calving fronts extended into deeper water and became more prone to fracturing, so the calving flux increased by an average of 170 gigatonnes per year, almost exactly offsetting the reduction in melt. The net change in sea-level-rise potential after 1,500 years was a decrease of only about 2.5 centimeters, a trivial amount compared with the several meters locked in the West Antarctic Ice Sheet. The authors conclude that the widely assumed positive feedback, in which an AMOC shutdown destabilizes Antarctica through surface warming, is not supported when the full ocean-ice interaction is simulated: it is the subsurface temperature at cavity depths, not the sea surface temperature, that governs the ice sheet’s fate.

The researchers are careful to spell out the limitations of their approach. The coupling between the climate and ice-sheet models is restricted to the ocean-ice interface, so atmospheric changes over Antarctica, including warming of 0.5 to 5 degrees Celsius and increased coastal precipitation, were not transmitted to the ice sheet surface. The artificial freshwater hosing, maintained continuously for 1,500 years, freshened the global ocean without compensation, an amount of water roughly seven times the current freshwater flux from Greenland, and the coarse ocean model does not resolve the Antarctic continental shelf, so bottom water forms through open-ocean convection rather than shelf processes, a known bias shared by about 80 percent of CMIP6 models. The timing of the convective regime shift, and therefore of the subsurface cooling, may also be model-specific, and the authors emphasize that repeating the experiment with other coupled models is essential before general conclusions can be drawn.

Nevertheless, the study marks a milestone: the first freshwater hosing experiment ever conducted with an interactively coupled climate-ice sheet model capable of resolving the millennial response of Antarctica. Its message cuts both ways for the climate conversation. On one hand, it suggests that a collapsing AMOC would not, at least through the ocean pathway alone, immediately push the West Antarctic Ice Sheet over its tipping point, which previous work places at an oceanic warming of about 1.5 degrees Celsius above preindustrial levels. On the other hand, it warns that simple assumptions about tipping cascades, in which one tipping element triggers another through a single variable such as sea surface temperature, may be dangerously oversimplified in a system where deep convection can invert the sign of a temperature anomaly within a few centuries. As freshwater pours from Greenland and Antarctic ice shelves melt at accelerating rates, understanding these cross-hemispheric connections has never mattered more, and this first coupled glimpse suggests the true dynamics are far stranger than the seesaw metaphor implies.

Subject of Research: The impact of an AMOC collapse on the stability of the Antarctic Ice Sheet simulated with a coupled climate-ice sheet model

Article Title: Simulating the impact of an AMOC weakening on the Antarctic Ice Sheet using a coupled climate and ice-sheet model

Article References: Höse, A., Kreuzer, M., Huiskamp, W., Petri, S., & Feulner, G. (2026). Simulating the impact of an AMOC weakening on the Antarctic Ice Sheet using a coupled climate and ice-sheet model. Earth System Dynamics, 17(4), 1025-1059. https://doi.org/10.5194/esd-17-1025-2026

Image Credits: AI Generated

DOI: 10.5194/esd-17-1025-2026

Keywords: AMOC, Antarctic Ice Sheet, climate tipping points, bipolar seesaw, Southern Ocean, ice sheet modeling, basal melt, Antarctic Bottom Water, deep convection, sea level rise, PISM, freshwater hosing

The scale of the analysis is formidable. The researchers examined 13,266 distinct datasets, spanning 54 climate models run under five shared socio-economic pathways, from the ambitious SSP119 scenario to the high-emissions SSP585. Twelve ocean, sea-ice, and atmospheric variables were scrutinised, including sea-surface temperature and salinity, sea-ice concentration, mixed-layer depth, sea-surface height, and the overturning streamfunctions that track the Atlantic Meridional Overturning Circulation, or AMOC. Crucially, the team replaced the expert visual inspection used in an earlier CMIP5 catalogue with a fully automated, reproducible detection algorithm, harnessing modern computing power and machine-learning tools such as the unsupervised clustering method HDBSCAN to isolate candidate regions of at least one million square kilometres.

The detection pipeline works in phases. Monthly model output is first averaged to yearly values and regridded onto a common Gaussian grid, and the historical runs are stitched to the scenario runs while checking that no artificial jump appears at the 2014 seam between them. Four different region-finding approaches then flag promising areas, using thresholds iteratively relaxed from the 99.99th percentile down to the 85th, and comparing variability against preindustrial control runs. Finally, six formal sets of criteria, labelled Ab1, Ab2, and St1 through St4, decide whether a region hosts an abrupt change on decadal timescales or a slower state transition too large to be attributed to the forcing alone. The criteria demand, for example, that a jump exceed 4.5 standard deviations of preindustrial variability, or that sea ice decline by at least 95 percent across an area of five million square kilometres.

The results are grouped into 11 categories, and their composition is telling. Roughly 45 percent of the surprises involve sea-ice cover, 29 percent mixed-layer depth, 19 percent ocean currents, and 7 percent atmospheric systems such as the Intertropical Convergence Zone. The single largest category concerns the transition to large, year-round ice-free areas in the Arctic, detected in 22 models. In the previous CMIP5 catalogue, only five models showed a winter sea-ice collapse, and only under the most extreme scenario, with thresholds between 4.5 and 8.2 degrees Celsius of global warming. In CMIP6, the corresponding warming levels fall to a 68 percent confidence interval of 2.5 to 4.1 degrees, meaning winter Arctic sea-ice disappearance could plausibly begin by the end of this century even under moderate emissions.

The physics behind these sea-ice surprises involves a well-understood web of positive feedbacks. As open water replaces ice, the lower atmosphere moistens and warms, increasing downward longwave radiation and inhibiting freezing. Thinner winter ice then lowers the surface albedo, boosting springtime shortwave absorption, while enhanced ocean heat uptake further erodes the ice pack. The catalogue also documents how sea-ice loss cascades into other variables: in several models, the disappearance of the ice lid unleashes abrupt shifts in sea-surface salinity, near-surface air temperature, and even sea-surface height, as the ocean and atmosphere suddenly exchange heat and freshwater far more vigorously than before.

Perhaps the most consequential finding concerns the North Atlantic. Ten models show a collapse of winter deep convection and mixed-layer depth in the subpolar gyre and Nordic Seas, often beginning around 2020 and in some cases even at warming levels near one degree. In nine models, this convective collapse is followed by a transition of the AMOC to an extremely weak state in which the cell associated with North Atlantic Deep Water formation has essentially vanished, leaving only a shallow, wind-driven residual overturning of about three Sverdrups. The onset of AMOC decline begins between 1980 and 2020 in these models, and the five-Sverdrup boundary is crossed between 2100 and 2140 in most of them. Strikingly, in the MRI-ESM2 model the collapse proceeds even under the low-emissions SSP126 scenario, a novel result suggesting the overturning may become largely independent of the forcing once a tipping point is passed.

The sequencing matters as much as the outcome. By comparing cumulative distributions of the warming level at which each change is maximal, the authors show that the mixed-layer collapse precedes the AMOC shutdown by roughly 0.3 to 0.5 degrees Celsius of global warming, equivalent to about twenty to thirty years. This is a clear example of a tipping point cascade: freshening and reduced heat loss stratify the subpolar North Atlantic, deep mixing fails, and the resulting buoyancy changes then starve the overturning of the dense water it needs. Notably, the freshening is driven by a weakening AMOC transporting less salty water northward, because meltwater from the Greenland Ice Sheet is not included in CMIP6 simulations, meaning the real-world freshwater forcing could be even stronger.

Not every surprise in the catalogue carries equal weight, and the authors are candid about model limitations. An abrupt shift in the North Atlantic Current pathway in the GISS-E2-1-H model appears tied to a known cold bias east of Newfoundland. A reorganisation of the Intertropical Convergence Zone in four models stems from the notorious double-ITCZ bias, though the underlying cloud-convection feedbacks exist in nature. A projected 50 percent intensification of the Antarctic Circumpolar Current is likely spurious, since coarse-resolution models cannot capture eddy saturation, which buffers the current against strengthening winds. By contrast, abrupt sea-ice loss in the Southern Ocean linked to the onset of deep convection, and the eastward expansion of the Ross Gyre, are corroborated by high-resolution regional modelling and observations of the Weddell Polynya mechanism.

To characterise timing, the team built probability density functions for the global warming level at which each surprise’s change is maximal, applying flexible 20-to-50-year windows to account for methodological uncertainty. These distributions show the frequency of surprises rising steeply below two degrees of warming and remaining high between two and four degrees. Importantly, the authors stress that these are conditional distributions describing when changes peak, not probabilities that a given event will occur, a deliberate choice to avoid politicised threshold debates. They also note that if a tipping point underlies a surprise, it is crossed before the temperature at which the transition is fastest.

The overall message is a sharpened warning. Compared with the 2015 CMIP5 catalogue, which identified 37 abrupt shifts, the new analysis finds nearly twice as many, occurring earlier and at lower warming levels, particularly for Arctic sea ice, North Atlantic convection, and the AMOC. Part of the increase reflects more extended simulations running to 2300 and improved detection methods, but the authors argue that genuinely higher sensitivity in CMIP6 also plays a role, and that observational constraints and the absence of Greenland meltwater both point toward underestimation rather than exaggeration of the risk. Because the criteria remain somewhat subjective and individual surprises can be stochastic, appearing in some ensemble members but not others, any single case demands caution. Yet the pattern across 54 models is difficult to dismiss: the newest generation of climate models suggests that strong nonlinear surprises, from an ice-free Arctic year-round to a shutdown of the Atlantic overturning, may arrive sooner, and at lower levels of warming, than the scientific community had previously assessed.

Subject of Research: Abrupt climate changes and state transitions in ocean, sea-ice, and atmospheric variables in CMIP6 future scenarios

Article Title: Catalogue of strong nonlinear surprises in ocean, sea-ice, and atmospheric variables in CMIP6

Article References: Angevaare, J. R., & Drijfhout, S. S. (2026). Catalogue of strong nonlinear surprises in ocean, sea-ice, and atmospheric variables in CMIP6. Earth System Dynamics, 17(4), 1081-1115. https://doi.org/10.5194/esd-17-1081-2026

Image Credits: AI Generated

DOI: 10.5194/esd-17-1081-2026

Keywords: CMIP6, climate tipping points, Arctic sea ice, AMOC, mixed-layer collapse, abrupt climate change, North Atlantic, deep convection, climate models, nonlinear feedbacks, sea-ice albedo, Earth System Dynamics

The research, led by Xiner Wu of the Université du Québec à Montréal together with Anne de Vernal and Paul G. Myers, forms part of the Paleoclimate Modelling Intercomparison Project, or PMIP4, a coordinated international effort that uses past climates as out-of-sample tests for the same numerical models that project future warming. The mid-Holocene is an ideal target for such a test. At 6,000 years before present, continental geometry was essentially identical to today’s and greenhouse gas concentrations were close to preindustrial levels, but subtle differences in Earth’s orbit redistributed sunlight across latitudes and seasons, producing warmer Northern Hemisphere summers and cooler winters. If a model cannot faithfully reproduce how the ocean responded to that modest, well-documented forcing, confidence in its response to the far larger forcing of the coming century is necessarily shaken.

To establish what the ocean actually did during that interval, the team turned to an ingenious biological archive: dinoflagellate cysts. These microscopic, extraordinarily resistant structures are produced by single-celled plankton in the surface ocean, and the species composition of the assemblages preserved in layered marine sediments reflects the environmental conditions under which the organisms lived. Crucially, recent work by the same group showed that dinocyst assemblages respond to wintertime deepening of the mixed layer associated with deep convection, allowing quantitative reconstruction of past mixed layer depths. Drawing on twenty-four Holocene sediment records from the modern deep convection regions of the subpolar North Atlantic, the researchers applied a modern analogue technique with a demonstrated error of about 41 metres for winter mixed layer depth — a precision that makes meaningful model comparison possible for the first time.

The comparison was conducted using anomalies rather than absolute values, subtracting the preindustrial baseline from the mid-Holocene simulation for each model and from each proxy record. This sidesteps systematic biases that plague both models and reconstructions. The team recomputed mixed layer depth from modelled temperature and salinity fields using a standardized density threshold, since different modelling groups define the mixed layer in incompatible ways, and they evaluated agreement with two complementary statistics: root mean square error, which measures the magnitude of disagreement, and Cohen’s kappa, which tests whether a model captures the direction of change — deeper or shallower — better than random chance would allow.

The results revealed a strikingly wide spread across the fifteen PMIP4 models. Some, such as ACCESS-ESM1.5, produced very large winter mixed layer anomalies, while others, like INM-CM4-8, barely responded at all. A recurring pattern emerged in several models: deepening in the Labrador Sea alongside a northwestward shift of the deep-mixing zone in the Nordic Seas, a response the authors link to reduced winter sea ice. Higher Northern Hemisphere summer insolation melts more Arctic sea ice, reducing its winter export into the subpolar North Atlantic; where ice retreats, the ocean loses heat to the atmosphere more readily, buoyancy fluxes intensify, and convection deepens — a self-reinforcing feedback in which rising warm, salty subsurface water further suppresses local ice formation.

Yet when the models were confronted with the proxy data, the picture fractured along a geographic line that carries real weight for future projections. In the Nordic Seas, the ensemble mean aligned broadly with the reconstructions, which indicate increased winter mixing at western and southeastern sites and shallower mixing in the east. In the Labrador Sea, however, the disagreement was stark and systematic. All four proxy sites there recorded shallower winter mixed layers during the mid-Holocene, while nearly every model — from both the current PMIP4 generation and the older PMIP3 ensemble — simulated the opposite, a deeper mixed layer. Only one model, MRI-ESM2.0, achieved statistically significant agreement with the direction of reconstructed change, and even the ensemble mean failed the test, demonstrating that averaging models together does not guarantee better performance.

The explanation the authors propose is meltwater — a forcing that the mid-Holocene experiment deliberately omits. The protocol prescribes modern ice sheets in equilibrium, but the real Labrador Sea of 6,000 years ago was anything but equilibrium. Residual ice caps lingered in eastern North America until roughly 6,000 to 5,500 years ago, and the Greenland Ice Sheet did not reach its minimum extent until about 4,000 years ago. Marine records show persistently low sea surface salinity in the Labrador Sea through the Early and Middle Holocene, and earlier proxy work suggests a buoyant, stratified surface layer that suppressed deep-water formation until well into the Holocene. Freshwater discharged from melting ice sheets would have capped the ocean with a light, low-density lid, preventing the dense overturning that models, deprived of this input, freely simulate. Notably, the Nordic Seas appear largely insulated from this effect, consistent with modern studies showing that most meltwater from the East Greenland Current ends up in the Labrador Sea and Baffin Bay rather than crossing eastward.

Transient simulations of the last deglaciation, which do include time-varying meltwater fluxes, lend qualified support to this hypothesis: they overestimate Labrador Sea mixed layer depth less severely than the equilibrium experiments. But the deglaciation models disagree wildly with each other and with the records, and none reproduces the reconstructed late-Holocene trend toward modern-like convection in the Labrador Sea, suggesting that the ocean’s memory in these long simulations may be unrealistically long. The team also found that model details matter enormously — different tuning of the same model changed the mixed layer response more than different ice sheet reconstructions did, and swapping the atmospheric component of a coupled model could reverse the sign of simulated change, underscoring that air-sea-ice interactions, not ocean physics alone, govern open-ocean convection.

Why should this matter beyond the paleoclimate community? Because the Labrador Sea is one of the few places on Earth where the atmosphere can reach down and set the deep ocean in motion, and because the same mechanism — ice sheet melt freshening the surface — is now operating in reverse time. As Greenland’s ice sheet accelerates its melt under global warming, the buoyant lid that suppressed convection 6,000 years ago could reassemble, with consequences for the overturning circulation, European climate and ocean carbon uptake. The study’s central message is that deep convection in the Labrador Sea may be uniquely and disproportionately sensitive to meltwater, and that current climate models, which handle this forcing imperfectly even in purpose-built paleoclimate experiments, may be underestimating that vulnerability. The mid-Holocene, it turns out, was not just an ancient curiosity but a rehearsal — and the models, on this crucial measure, are still learning their lines.

Subject of Research: Evaluation of mixed layer depth in PMIP4 mid-Holocene climate simulations against proxy reconstructions in North Atlantic deep convection regions

Article Title: Mixed layer depth in the PMIP4 midHolocene simulations: comparison to proxy data in North Atlantic deep convection regions

Article References: Wu, X., de Vernal, A., & Myers, P. G. (2026). Mixed layer depth in the PMIP4 midHolocene simulations: comparison to proxy data in North Atlantic deep convection regions. Climate of the Past, 22(9), 1609-1629. https://doi.org/10.5194/cp-22-1609-2026

Image Credits: AI Generated

DOI: 10.5194/cp-22-1609-2026

Keywords: mixed layer depth, PMIP4, mid-Holocene, Labrador Sea, Nordic Seas, deep convection, AMOC, dinocyst proxies, meltwater forcing, sea ice, climate models, paleoclimate

The research, led by Andrew G. Pauling of the University of Otago and the Antarctic Research Centre at Victoria University of Wellington, is the first coordinated multi-model study of how Antarctic sea ice responds to meltwater from ice sheet mass loss. The work emerged from the Southern Ocean Freshwater Input from Antarctica initiative, known as SOFIA, a CMIP7-endorsed model intercomparison project designed to standardize how the world’s climate modeling groups test the effects of this missing ingredient. The motivation is stark: virtually none of the state-of-the-art models in CMIP6, the suite of simulations underpinning current climate assessments, actually include meltwater entering the Southern Ocean from a shrinking Antarctic ice sheet.

That omission matters because the meltwater flux is real and growing. A 2021 review of Earth’s ice mass imbalance estimated that the Antarctic ice sheet and its ice shelves lost mass at a rate of 395 plus or minus 99 gigatonnes per year between 1994 and 2017, accelerating to 509 plus or minus 186 gigatonnes per year over 2010 to 2016. In most climate models, including every CMIP6 participant, ice sheet mass balance is simply enforced, meaning freshwater input to the ocean can only change in step with precipitation falling on the continent. In the real world, ice is also lost at the coast through basal melting of ice shelves and iceberg calving, processes that models largely cannot represent because they lack interactive ice sheets.

To isolate the effect of this missing fresh water, the SOFIA team designed a deliberately idealized experiment called antwater. Eleven models, comprising 43 ensemble members in total, were each run for 100 years with a constant meltwater flux of 0.1 sverdrup, equivalent to about 3,154 gigatonnes per year, injected at the ocean surface and spread evenly across all grid cells immediately adjacent to the Antarctic coastline. That amount is larger than today’s observed melt rates, but it is comparable to projected mid-to-late twenty-first century fluxes, and the uniformity was the point: by giving every model an identical perturbation under pre-industrial conditions, any differences in response must come from the models themselves rather than from differing forcing scenarios.

The headline result is deceptively simple. Antarctic sea ice area increased in all of the models. But the magnitude of that increase ranged from 0.71 to 4.14 million square kilometers in the annual mean, a spread of nearly a factor of six. For context, the observed annual-mean Antarctic sea ice area over the satellite era from 1979 to 2024 is about 8.7 million square kilometers. In other words, one model barely noticed the meltwater while another grew an ice pack nearly half the size of the real one. Sea ice volume told a similar story, rising by between roughly 380 and 7,590 cubic kilometers across models, with a multi-model mean increase of 42 percent.

The physical mechanism behind the growth is stratification. Meltwater is fresh and therefore less dense than the salty water it enters, so it pools near the surface and strengthens the vertical density gradient of the water column. That cap suppresses the upward mixing of relatively warm water from depth, allowing the surface to cool more readily to freezing point and ice to expand. The team quantified this using a modified stratification index, summing density differences from the surface down to 500 meters, and found a statistically significant relationship between how much a model’s stratification increased and how much its sea ice grew. Models whose water columns became more stratified grew more ice.

Open-ocean deep convection emerged as another crucial player. In several models, vast chimneys of water in the Weddell and Ross seas mix to depths exceeding 2,000 meters, dredging warm water to the surface and melting ice. When meltwater was added, convection shut down almost completely in models including CanESM5, GFDL-CM4, GFDL-ESM4 and GISS-E2-1-G, and sea ice surged. Conversely, the two models with no deep convection at all, AWI-ESM-1-REcoM and CESM2, showed the weakest sea ice responses. The GFDL-ESM4 model even carried a fingerprint of its control-run behavior: a large Weddell Sea polynya in years 50 to 70 of the control simulation vanished under meltwater forcing, producing an apparent spike in the ice response that was really an artifact of the missing convective opening.

Timing and geography varied too. Fitting an exponential curve to each model’s response, the team found time constants ranging from under one year to nearly 70 years, with most models settling between 5 and 20 years and a multi-model mean of 10.2 years. In most models the ice increase was largest around the September annual maximum and smallest at the February minimum, consistent with the idea that winter freezing, which requires cooling a deeper layer of water, is more sensitive to the stratifying effect of fresh water than the summer melt season. Spatially, the strongest concentration increases appeared near the ice edge in the Ross Sea and the Amundsen and Bellingshausen Seas, while several models showed meltwater flowing from the Antarctic Peninsula into the South Atlantic, following the coastal currents anticlockwise around the continent before separating at the Peninsula’s tip.

The study’s authors caution that the idealized experiment is a controlled sensitivity test, not a realistic simulation. Real meltwater enters the ocean unevenly, concentrated in the Amundsen Sea sector, and mostly at depth through ice shelf basal melting, which accounted for 68 percent of the melt from shrinking ice shelves between 1997 and 2021. The experiment also omits the latent heat that melting ice extracts from the ocean. Atmospheric feedbacks, which recent analyses show can generate large-scale circulation responses to Antarctic freshening, add further complexity. Upcoming SOFIA tiers will test historical and future meltwater estimates and probe the effects of realistic spatial and vertical distributions of the freshwater input.

What the study makes unmistakably clear is that a single model’s response to Antarctic meltwater cannot be taken at face value. The spread in the results was dominated by model uncertainty rather than internal variability, and much of that spread traces back to each model’s background climate: its mean-state sea ice area and volume, its ocean stratification, and its tendency toward deep convection. As meltwater from Antarctica continues to grow through this century, getting these background states right will be essential for projecting the fate of Antarctic sea ice, a system that influences Southern Ocean heat and carbon uptake, marine ecosystems, and even tropical rainfall patterns through atmospheric teleconnections. The missing meltwater, once an afterthought in climate modeling, is now impossible to ignore.

Subject of Research: Multi-model climate model ensemble study of the Antarctic sea ice response to meltwater from Antarctic ice sheet mass loss

Article Title: Antarctic sea ice response to meltwater due to Antarctic ice sheet mass loss in a multi-model ensemble

Article References: Pauling, A. G., Smith, I. J., Martin, T., Ridley, J. K., Stevens, D. P., Thomas, M., Beadling, R. L., Danek, C., Hattermann, T., Li, Q., Marshall, J., Muilwijk, M., Purich, A., & Swart, N. C. (2026). Antarctic sea ice response to meltwater due to Antarctic ice sheet mass loss in a multi-model ensemble. The Cryosphere, 20(10), 5761-5783. https://doi.org/10.5194/tc-20-5761-2026

Image Credits: AI Generated

DOI: 10.5194/tc-20-5761-2026

Keywords: Antarctic sea ice, meltwater, Antarctic ice sheet, Southern Ocean, climate models, SOFIA, CMIP6, ocean stratification, deep convection, sea ice area, The Cryosphere, model intercomparison

The stakes are larger than they might first appear. Subsiding shells are not a curiosity of cloud physics; they are a leading contributor to downdraft mass flux in the atmosphere. Previous work by Glenn and Krueger found that the compensatory downward mass flux associated with deep convective subsiding shells amounts to roughly five to ten percent of the upward flux at any given level. Because global climate models cannot explicitly resolve individual thunderstorms, they rely on cumulus parameterizations to represent these sub-grid exchanges of mass, heat, and moisture. Many of those schemes assume downdrafts simply displace the mean properties of a model grid cell downward, an assumption that the near-cloud environment routinely violates. Getting the shells right, in other words, is a prerequisite for getting the climate right.

To probe the shells, the team ran two large-eddy simulations of deep moist convection using the Cloud Model 1 code, with an isotropic 100-meter grid spacing across a 200-square-kilometer domain extending 20 kilometers high. The simulations were initialized with composite soundings drawn from the Green Ocean Amazon campaign, a major field effort conducted in the Amazon Rainforest in 2014 and 2015. The two soundings represented the Amazonian wet and dry seasons, which share nearly identical temperature profiles but differ sharply in free-tropospheric relative humidity. By holding the temperature profiles equal and nudging the domain-averaged moisture above four kilometers back toward its initial state, the researchers isolated the influence of humidity on convection, creating a clean natural experiment inside the computer.

The simulations reproduced the observed atmosphere remarkably well. Updraft tops reached 12 to 16 kilometers, consistent with radar echo tops observed during the field campaign, and time-averaged maximum vertical velocities were greater in the dry season simulation, at roughly 31 meters per second, than in the wet season simulation, at about 27 meters per second. A simple entraining plume model helped explain why: the drier lower troposphere raised the lifting condensation level, producing wider updrafts with smaller fractional entrainment rates, while steeper low-level lapse rates boosted buoyancy. The stage was set to ask what these stronger updrafts meant for the air sinking around them.

The heart of the study was a Lagrangian trajectory analysis of extraordinary scale. Nearly five and a half million inert parcels were seeded uniformly through the domain, and their positions, vertical velocities, buoyancy, and pressure-gradient accelerations were recorded every 30 seconds during the analysis hour. Parcels qualified as shell parcels if they began descending from at least five kilometers, reached a vertical velocity of minus 1.5 meters per second or stronger, displaced at least 500 meters, and spent at least 90 percent of their downdraft lifetime within a subsiding shell, defined as the continuous ring of negative vertical velocity immediately adjacent to cloud edge.

The results were striking. Shell downdrafts in the dry simulation reached a mean minimum vertical velocity of minus 3.44 meters per second, compared with minus 2.78 meters per second in the wet simulation, making the dry-season shells about 23.5 percent stronger, a difference that held statistical significance through essentially the entire downdraft. This matched radar wind profiler observations from the Amazon, which had recorded more frequent strong downdrafts in the dry season. But the reason for the difference was not what many had assumed.

For years, the leading hypothesis held that drier environmental air enhances evaporative cooling at cloud edge, chilling the air, making it negatively buoyant, and thereby driving stronger descent. The trajectory analysis confirmed that shell parcels are indeed negatively buoyant, with dry-season parcels reaching a minimum mean buoyancy of minus 0.021 meters per second squared versus minus 0.016 in the wet case. Yet when the researchers computed effective buoyancy, which combines thermal buoyancy with the vertical perturbation pressure gradient that the atmosphere generates in response to buoyancy anomalies, the seasonal difference nearly vanished. The stronger negative buoyancy in the dry case was almost entirely offset by a stronger upward-directed buoyancy pressure acceleration, a self-regulating thermodynamic response that canceled the apparent advantage of extra evaporation.

The true driver of the seasonal difference lay elsewhere: in dynamic pressure accelerations tied to the toroidal circulations of rising cloud thermals. As a thermal ascends, it carries a region of low perturbation pressure at its core, embedded within the swirling vortex-like circulation that surrounds it. Air parcels passing down the cloud flank are, in the authors’ words, essentially sling-shotted downward by the descending branch of this circulation. The magnitude of this toroidal low scales with updraft strength and horizontal buoyancy gradients, so the stronger dry-season updrafts produced stronger dynamic pressure minima and correspondingly larger downward accelerations. When the team decomposed the kinetic energy budget of shell parcels, the dry-season advantage in dynamic nonlinear pressure energy emerged as the dominant explanation for the stronger downdrafts, while the effective buoyancy contributions were nearly identical between seasons.

The study also revealed that cloud depth matters profoundly. Splitting the shell population into deep convection, with cloud tops above five kilometers, and congestus convection below that threshold, the researchers found that deep shells reached minimum vertical velocities of minus 3.66 and minus 2.96 meters per second in the dry and wet simulations respectively, while congestus shells were markedly weaker, with dry congestus downdrafts a full meter per second slower than their deep counterparts. In the congestus regime, the dynamic pressure contribution collapsed, and negative effective buoyancy from persistent evaporative cooling became the primary driver, so that the stronger dry-season congestus shells were buoyancy-driven rather than dynamically driven. This regime dependence carries a direct warning for modelers: parameterizations cannot assume a single universal mechanism for shell formation across all cloud types.

The composite structures painted a coherent physical picture of a shell’s life. Near cloud top, parcels are accelerated downward both by the dynamic pressure dipole of the toroidal circulation and by negative buoyancy from evaporating cloud droplets at the edge. As they descend past the pressure minimum, the pressure acceleration reverses to point upward, and once parcels overshoot their level of neutral buoyancy, thermal buoyancy turns positive as well. Descent then ceases, typically after a displacement of only about a kilometer, with turbulent mixing at the updraft-shell interface providing a persistent drag throughout. The shells themselves proved narrower than expected, averaging roughly 480 meters wide for deep convection and 420 meters for congestus, with width depending mainly on cloud depth rather than environmental humidity. The authors caution that acceleration magnitudes remain sensitive to choices of microphysics and turbulence schemes, and they recommend that future work extend these findings to strongly sheared environments and to observational campaigns such as ESCAPE. Ultimately, they argue, the dynamics of subsiding shells deserve explicit treatment in cumulus parameterizations, so that climate models can finally capture the hidden rivers of sinking air that every thunderstorm drags down with it.

Subject of Research: Driving mechanisms of subsiding shells surrounding deep convective clouds in large-eddy simulations

Article Title: Driving mechanisms for subsiding shells in simulations of deep moist convection

Article References: Mulhern, Q. R., Peters, J. M., & Mulholland, J. P. (2026). Driving mechanisms for subsiding shells in simulations of deep moist convection. Atmospheric Chemistry and Physics, 26(19), 13959-13982. https://doi.org/10.5194/acp-26-13959-2026

Image Credits: AI Generated

DOI: 10.5194/acp-26-13959-2026

Keywords: subsiding shells, deep convection, downdrafts, large-eddy simulation, cumulus parameterization, evaporative cooling, perturbation pressure, toroidal circulation, Amazon, GOAMAZON, cloud dynamics, relative humidity

The study focuses on HadGEM3-GC3.1-LL, the low-resolution configuration of the UK’s CMIP6 climate model, which simulates the atmosphere, ocean, land, and sea ice as a fully coupled system. The atmosphere component, the Met Office Unified Model, runs on a grid of roughly 135 kilometers, which means that much of Antarctica’s rugged terrain is too small to be resolved directly. Instead, the model relies on a parameterization of orographic gravity wave drag, or OGWD, to represent the forces that sub-grid-scale mountains impose on the flow. This parameterization splits the total drag into two components: flow-blocking drag, which arises when air is too stable to climb over an obstacle and is deflected around it, and gravity wave drag, which arises when air does surmount the terrain and generates waves that break aloft and deposit momentum.

Which of these two regimes dominates depends on a delicate balance captured by the non-dimensional parameter Nh/U, where U is wind speed, N is atmospheric stability, and h is obstacle height. When Nh/U greatly exceeds one, blocking prevails; when it is near or below one, the flow passes over the mountain. In the Unified Model, the effective sub-grid mountain height is set by a tuning constant called n-sigma, with a default value of 2.5 that is among the least constrained parameters in the entire model. The researchers exploited this lever to run two sets of sensitivity experiments over Antarctica: one, called F_BLOCK, in which n-sigma was doubled to 5, making virtual mountains effectively taller and forcing the flow into a blocking regime, and another, called F_OVER, in which n-sigma was reduced to 1.5, nearly halving the barrier height and letting winds sweep across the terrain while generating strong gravity waves. Crucially, the modifications were applied only over Antarctica, so any circulation change in the simulations could be attributed unambiguously to the southernmost continent.

The results were striking. In the baseline historical simulation, pan-Antarctic sea ice area begins a sustained decline around the early 1980s, driven largely by the Weddell Sea, one of the continent’s main sea ice factories. In the flow-blocking experiments, that decline is delayed by roughly ten to twenty years, with the ensemble mean holding steady until just before 1995. In the flow-over experiment, the decline begins about ten years earlier still, around 1972. Because the delayed decline appears consistently across all four members of the flow-blocking ensemble, the team could rule out natural variability as the explanation: the differences are a systematic response of the coupled climate system to how orographic drag is represented.

The immediate physical mechanism operates through the atmosphere’s vertical structure. In the flow-over configuration, larger-amplitude gravity waves break in the lower and mid-troposphere, decelerating the background westerly flow and weakening the tropospheric polar vortex. In the flow-blocking configuration, weaker wave amplitudes mean less drag and stronger zonal winds aloft. A stronger polar vortex insulates the Antarctic continent, exchanging less heat with the mid-latitudes, so surface air temperatures drop in F_BLOCK and rise in F_OVER. Colder conditions strengthen the katabatic winds, the rivers of cold, dense air that drain from the high interior toward the coast, which push sea ice offshore in the Weddell Sea and promote the formation of fresh ice. Within the first one to two years of simulation, sea ice area rises by about one million square kilometers in F_BLOCK and falls by a similar amount in F_OVER relative to the historical run.

The long-term story, however, unfolds in the Weddell Sea, and it hinges on the Antarctic Peninsula acting as a formidable barrier to the prevailing westerlies. In the flow-blocking experiment, the incoming flow cannot clear the ridge, so westerly winds both upstream over the Amundsen and Bellingshausen Seas and downstream over the Weddell Sea are weakened. Mean sea level pressure anomalies generated by the blocking propagate vast distances around the continent, echoing earlier work by Sandu and colleagues showing that orographic blocking leaves fingerprints far beyond the mountains that create it. June-to-November westerly winds at 850 hectopascals across the Weddell Sea are reduced by about half a meter per second, roughly sixteen percent, in F_BLOCK, and strengthened by a comparable margin in F_OVER.

Those wind changes translate directly into the ocean. The total surface stress exerted on the Weddell Sea, the combined push of atmosphere and sea ice on the water, is much weaker under flow-blocking conditions and much stronger under flow-over conditions, partly because stress scales with the square of wind speed and partly because thinner or reduced ice allows more efficient momentum transfer. Stronger winds spin up the cyclonic Weddell gyre, whose depth-integrated circulation, measured by the barotropic streamfunction, strengthens steadily through the historical run. A stronger gyre makes the surface flow more divergent, and by continuity, relatively warm, salty water is pumped upward from depth, with Ekman pumping in the historical simulation rising from roughly 55 meters per year in 1980 to about 85 meters per year by the end of the run.

Near Maud Rise, at about 66 degrees south and 3 degrees east, weak stratification and favorable topography set the stage for open-ocean deep convection, the vertical mixing that draws heat from the deep ocean to the surface. In the model, these events are diagnosed when the ocean mixed layer exceeds 2000 meters in depth, and polynya-scale events are flagged when the convecting area surpasses 80,000 square kilometers, the size of the real Weddell Sea polynya of 2016 and 2017. The correspondence with sea ice is dramatic: every cluster of deep convection years coincides with a sharp drop in sea ice area. In the historical simulation, convection recurs almost every year from 1989 onward, and in F_OVER it appears even earlier and more often. In F_BLOCK, by contrast, deep convection is nearly absent, with only a handful of small events across sixty-five years, and the ice survives largely intact.

The team then turned the correlation into a diagnostic tool. Plotting annual sea ice area against ocean surface stress reveals a strong negative relationship, with a correlation coefficient of minus 0.75, and the historical simulation migrates over time from a low-stress, high-ice state toward a high-stress, low-ice state that mirrors the flow-over experiment. Using the observational range of sea ice area from the HadISST1 dataset as an emergent constraint, the researchers estimate that plausible surface stress values lie between 0.042 and 0.066 newtons per square meter, a range that the flow-blocking simulation satisfies best. That result suggests the default model may underestimate atmospheric blocking by the Peninsula, and that a calibrated tuning of the sub-grid orography there would be advisable.

The broader implications reach beyond model tuning. The study shows that a more positive Southern Annular Mode does not necessarily mean stronger winds over the Weddell Sea, because the Peninsula’s barrier effect can override the large-scale annular signal. It also suggests that the springtime strengthening of westerlies over the Weddell Sea seen in the historical run, which is consistent with ERA5 reanalysis, may partly reflect a long-term shift in the Peninsula’s flow regime toward weaker blocking, driven by declining static stability, rather than greenhouse and ozone forcing alone. And because the spurious deep convection is fueled by wind-driven Ekman pumping, a large-scale process the model resolves explicitly, simply tweaking vertical mixing parameterizations will not fix it. The authors point instead to revising how ocean surface stress is represented, potentially through variable drag coefficients that respond to the evolving state of the ice and atmosphere, an approach already under development for the next version of HadGEM3. In the end, the message is humbling and exhilarating in equal measure: a single tuning constant, buried in the treatment of invisible mountains, can decide whether a flagship climate model loses its Antarctic sea ice a decade early, a decade late, or not at all.

Subject of Research: The influence of orographic gravity wave drag and flow regimes over the Antarctic Peninsula on Weddell Sea sea ice and deep convection in a coupled climate model

Article Title: Southern Hemisphere sea ice response to different flow regimes over the Antarctic Peninsula

Article References: Guarino, M.-V., Ridley, J. K., Farneti, R., Kucharski, F., & Tompkins, A. M. (2026). Southern Hemisphere sea ice response to different flow regimes over the Antarctic Peninsula. Climate Dynamics, 64(9), Article 410. https://doi.org/10.1007/s00382-026-08350-6

Image Credits: AI Generated

DOI: 10.1007/s00382-026-08350-6

Keywords: Antarctic sea ice, Antarctic Peninsula, orographic gravity wave drag, Weddell Sea, deep convection, polynyas, HadGEM3, CMIP6, wind stress, Ekman pumping, Southern Annular Mode, climate modeling