Global Inaction on Climate Change Could Wipe Out Emperor Penguins

The concept of a canary in a coal mine — a sensitive species that provides an alert to danger — originated with British miners, who carried actual canaries underground through the mid-1980s to detect the presence of deadly carbon monoxide gas. Today another bird, the Emperor Penguin, is providing a similar warning about the planetary effects of burning fossil fuels.

As a seabird ecologist, I develop mathematical models to understand and predict how seabirds respond to environmental change. My research integrates many areas of science, including the expertise of climatologists, to improve our ability to anticipate future ecological consequences of climate change.

Most recently, I worked with colleagues to combine what we know about the life history of Emperor Penguins with different potential climate scenarios outlined in the 2015 Paris Agreement, to combat climate change and adapt to its effects. We wanted to understand how climate change could affect this iconic species, whose unique life habits were documented in the award-winning film “March of the Penguins.”

Our newly published study found that if climate change continues at its current rate, Emperor Penguins could virtually disappear by the year 2100 due to loss of Antarctic sea ice. However, a more aggressive global climate policy can halt the penguins’ march to extinction.

Carbon Dioxide in Earth’s Atmosphere

As many scientific reports have shown, human activities are increasing carbon dioxide concentrations in Earth’s atmosphere, which is warming the planet. Today atmospheric CO2 levels stand at slightly over 410 parts per million, well above anything the planet has experienced in millions of years.

If this trend continues, scientists project that CO2 in the atmosphere could reach 950 parts per million by 2100. These conditions would produce a very different world from today’s.

Emperor Penguins are living indicators whose population trends can illustrate the consequences of these changes. Although they are found in Antarctica, far from human civilization, they live in such delicate balance with their rapidly changing environment that they have become modern-day canaries.

A Fate Tied to Sea Ice

I have spent almost 20 years studying Emperor Penguins’ unique adaptations to the harsh conditions of their sea ice home. Each year, the surface of the ocean around Antarctica freezes over in the winter and melts back in summer. Penguins use the ice as a home base for breeding, feeding and molting, arriving at their colony from ocean waters in March or April after sea ice has formed for the Southern Hemisphere’s winter season.

In mid-May the female lays a single egg. Throughout the winter, males keep the eggs warm while females make a long trek to open water to feed during the most unforgiving weather on Earth.

When female penguins return to their newly hatched chicks with food, the males have fasted for four months and lost almost half their weight. After the egg hatches, both parents take turns feeding and protecting their chick. In September, the adults leave their young so that they can both forage to meet their chick’s growing appetite. In December, everyone leaves the colony and returns to the ocean.

Throughout this annual cycle, the penguins rely on a sea ice “Goldilocks zone” of conditions to thrive. They need openings in the ice that provide access to the water so they can feed, but also a thick, stable platform of ice to raise their chicks.

Penguin Population Trends

For more than 60 years, scientists have extensively studied one Emperor Penguin colony in Antarctica, called Terre Adélie. This research has enabled us to understand how sea ice conditions affect the birds’ population dynamics. In the 1970s, for example, the population experienced a dramatic decline when several consecutive years of low sea ice cover caused widespread deaths among male penguins.

Over the past 10 years, my colleagues and I have combined what we know about these relationships between sea ice and fluctuations in penguin life histories to create a demographic model that allows us to understand how sea ice conditions affect the abundance of Emperor Penguins, and to project their numbers based on forecasts of future sea ice cover in Antarctica.

Once we confirmed that our model successfully reproduced past observed trends in Emperor Penguin populations around all Antarctica, we expanded our analysis into a species-level threat assessment.

Climate Conditions Determine Emperor Penguins’ Fate

When we used a climate model linked to our population model to project what is likely to happen to sea ice if greenhouse gas emissions continue on their present trend, we found that all 54 known Emperor Penguin colonies would be in decline by 2100, and 80% of them would be quasi-extinct. Accordingly, we estimate that the total number of Emperor Penguins will decline by 86% relative to its current size of roughly 250,000 if nations fail to reduce their carbon dioxide emissions.

However, if the global community acts to reduce greenhouse gas emissions and succeeds in stabilizing average global temperatures at 1.5 degrees Celsius (3 degrees Faherenheit) above pre-industrial levels, we estimate that Emperor Penguin numbers would decline by 31% — still drastic, but viable.

Less-stringent cuts in greenhouse gas emissions, leading to a global temperature rise of 2°C, would result in a 44% decline.

Our model indicates that these population declines will occur predominately in the first half of this century. Nonetheless, in a scenario in which the world meets the Paris climate targets, we project that the global Emperor Penguin population would nearly stabilize by 2100, and that viable refuges would remain available to support some colonies.

In a changing climate, individual penguins may move to new locations to find more suitable conditions. Our population model included complex dispersal processes to account for these movements. However, we find that these actions are not enough to offset climate-driven global population declines. In short, global climate policy has much more influence over the future of Emperor Penguins than the penguins’ ability to move to better habitat.

Our findings starkly illustrate the far-reaching implications of national climate policy decisions. Curbing carbon dioxide emissions has critical implications for Emperor Penguins and an untold number of other species for which science has yet to document such a plain-spoken warning.

Ozone hole is the smallest on record due to ‘rare event,’ NASA says

Unusual weather patterns in the upper atmosphere over Antarctica have caused a drastic reduction in ozone depletion, leaving the ozone with the smallest hole seen sin1982, according to NASA and the National Oceanic and Atmospheric Administration.

The government agencies said that the hole had shrunk to 3.9 million square miles for the remainder of September and October, according to satellite data. The peak in the hole was 6.3 million square miles, observed on Sept. 8. During normal weather conditions, the hole is usually around 8 million square miles during this time of year.

“It’s great news for ozone in the Southern Hemisphere,” said Paul Newman, chief scientist for Earth Sciences at NASA’s Goddard Space Flight Center in a statement on NASA’s website. “But it’s important to recognize that what we’re seeing this year is due to warmer stratospheric temperatures. It’s not a sign that atmospheric ozone is suddenly on a fast track to recovery.”

This time-lapse photo from Sept. 9, 2019, shows the flight path of an ozonesonde as it rises into the atmosphere over the South Pole from the Amundsen-Scott South Pole Station. Scientists release these balloon-borne sensors to measure the thickness of the protective ozone layer high up in the atmosphere. Credits: Robert Schwarz/University of Minnesota

This time-lapse photo from Sept. 9, 2019, shows the flight path of an ozonesonde as it rises into the atmosphere over the South Pole from the Amundsen-Scott South Pole Station. Scientists release these balloon-borne sensors to measure the thickness of the protective ozone layer high up in the atmosphere. Credits: Robert Schwarz/University of Minnesota


A video was posted to NASA’s Goddard YouTube page showing the satellite data in further detail.

The ozone layer is approximately 7 to 25 miles above the Earth’s surface and acts as a “sunscreen” for the planet, NASA added. It keeps out harmful ultraviolet radiation from the Sun that has been linked to skin cancer, cataracts, immune system suppression and can also cause damage to plants.

The hole over the Antarctic forms during the Southern Hemisphere’s late winter as the Sun’s rays start to cause ozone-depleting reactions. This involves chlorine and bromine from man-made objects being released into the stratosphere which then destroys the molecules in the ozone.

Although “measurements at the South Pole did not show any portions of the atmosphere where ozone was completely depleted,” atmospheric scientist Bryan Johnson at NOAA’s Earth System Research Laboratory said, it’s not all good news.

This is just the third time in the past 40 years (September 1998 and 2002 were the others) where the ozone depletion has been limited by unusual weather systems, a phenomena researchers are still trying to figure out.


“It’s a rare event that we’re still trying to understand,” said Susan Strahan, an atmospheric scientist. “If the warming hadn’t happened, we’d likely be looking at a much more typical ozone hole.”

The 1987 Montreal Protocol was enacted after scientists disturbingly found a hole in the ozone over Antarctica and Australia in 1985. It was enacted by the United Nations Environment Program. Former U.N. Secretary-General Kofi Annan said it was “[p]erhaps the single most successful international agreement to date” and it has been widely regarded as successful, with the ozone continuing to recover each year.


A total of 197 countries, including the U.S. under former President Ronald Reagan, are signatories of the Montreal Protocol.

Experts believe the Antarctic ozone will recover back to levels seen in 1980 around 2070.

Antarctica’s “Sudden Stratospheric Warming” Has Started Impacting Australia

main article image
Southern Hemisphere’s stratosphere in 1998. (NASA)

Record warm temperatures above Antarctica over the coming weeks are likely to bring above-average spring temperatures and below-average rainfall across large parts of New South Wales and southern Queensland.

The warming began in the last week of August, when temperatures in the stratosphere high above the South Pole began rapidly heating in a phenomenon called “sudden stratospheric warming”.

In the coming weeks the warming is forecast to intensify, and its effects will extend downward to Earth’s surface, affecting much of eastern Australia over the coming months.

The Bureau of Meteorology is predicting the strongest Antarctic warming on record, likely to exceed the previous record of September 2002.

September stratospheric warming from 2002 (left) and 2019 (right). (Australian Bureau of Meteorology)September stratospheric warming from 2002 (left) and 2019 (right). (Australian Bureau of Meteorology)

What’s going on?

Every winter, westerly winds – often up to 200 kilometre per hour (120 miles per hour) – develop in the stratosphere high above the South Pole and circle the polar region.

The winds develop as a result of the difference in temperature over the pole (where there is no sunlight) and the Southern Ocean (where the sun still shines).

As the sun shifts southward during spring, the polar region starts to warm. This warming causes the stratospheric vortex and associated westerly winds to gradually weaken over the period of a few months.

Waves of air from the lower atmosphere (from large weather systems or flow over mountains) warm the stratosphere above the South Pole, and weaken or “mix” the high-speed westerly winds.

Very rarely, if the waves are strong enough they can rapidly break down the polar vortex, actually reversing the direction of the winds so they become easterly. This is the technical definition of “sudden stratospheric warming.”

Although we have seen plenty of weak or moderate variations in the polar vortex over the past 60 years, the only other true sudden stratospheric warming event in the Southern Hemisphere was in September 2002.

In contrast, their northern counterpart occurs every other year or so during late winter of the Northern Hemisphere because of stronger and more variable tropospheric wave activity.

What can Australia expect?

Impacts from this stratospheric warming are likely to reach Earth’s surface in the next month and possibly extend through to January.

Apart from warming the Antarctic region, the most notable effect will be a shift of the Southern Ocean westerly winds towards the Equator.

But for subtropical Australia, which largely sits north of the main belt of westerlies, the shift results in reduced rainfall, clearer skies, and warmer temperatures.

Past stratospheric warming events and associated wind changes have had their strongest effects in NSW and southern Queensland, where springtime temperatures increased, rainfall decreased and heatwaves and fire risk rose.

The influence of the stratospheric warming has been captured by the Bureau’s climate outlooks, along with the influence of other major climate drivers such as the current positive Indian Ocean Dipole, leading to a hot and dry outlook for spring.

Nine anomalous polar vortex years compared to other years between 1979-2016. (Bureau of Meteorology)Nine anomalous polar vortex years compared to other years between 1979-2016. (Bureau of Meteorology)

Effects on the ozone hole and Antarctic sea ice

One positive note of sudden stratospheric warming is the reduction – or even absence altogether – of the spring Antarctic ozone hole. This is for two reasons.

First, the rapid rise of temperatures in the upper atmosphere means the super cold polar stratospheric ice clouds, which are vital for the chemical process that destroys ozone, may not even form.

We also expect an enhanced decline in Antarctic sea ice between October and January, particularly in the eastern Ross Sea and western Amundsen Sea, as more warm water moves towards the poles due to the weaker westerly winds.

Thanks to improvements in modelling and the Bureau’s new supercomputer, these types of events can be forecast better than ever before.

Compared to 2002, when we didn’t know much about the event until after it had happened, this time we’ve had almost three weeks’ notice that a very strong warming event was coming. We also know much more about the process that has been set in train, that will affect our weather over the next one to four months.The Conversation

315 billion-tonne iceberg breaks off Antarctica

Image captionThe EU’s Sentinel-1 satellite system captured these before and after images

The Amery Ice Shelf in Antarctica has just produced its biggest iceberg in more than 50 years.

The calved block covers 1,636 sq km in area – a little smaller than Scotland’s Isle of Skye – and is called D28.

The scale of the berg means it will have to be monitored and tracked because it could in future pose a hazard to shipping.

Not since the early 1960s has Amery calved a bigger iceberg. That was a whopping 9,000 sq km in area.

Amery is the third largest ice shelf in Antarctica, and is a key drainage channel for the east of the continent.

The shelf is essentially the floating extension of a number of glaciers that flow off the land into the sea. Losing bergs to the ocean is how these ice streams maintain equilibrium, balancing the input of snow upstream.

So, scientists knew this calving event was coming. What’s interesting is that much attention in the area had actually been focussed just to the east of the section that’s now broken away.

This is a segment of Amery that has affectionately become known as “Loose Tooth” because of its resemblance in satellite images to the dentition of a small child. Both ice areas had shared the same rift system.

Loose ToothImage copyrightNASA
Image captionLoose Tooth pictured in the early 2000s. D28 is seen forming to the left

But although wobbly, Loose tooth is still attached. It’s D28 that’s been extracted.

“It is the molar compared to a baby tooth,” Prof Helen Fricker from the Scripps Institution of Oceanography told BBC News.

Prof Fricker had predicted back in 2002 that Loose Tooth would come off sometime between 2010 and 2015.

“I am excited to see this calving event after all these years. We knew it would happen eventually, but just to keep us all on our toes, it is not exactly where we expected it to be,” she said.

The Scripps researcher stressed that there was no link between this event and climate change. Satellite data since the 1990s has shown that Amery is roughly in balance with its surroundings, despite experiencing strong surface melt in summer.

“While there is much to be concerned about in Antarctica, there is no cause for alarm yet for this particular ice shelf,” Prof Fricker added.

Amery ice shefImage copyrightRICHARD COLEMAN/UTAS
Image captionAmery experiences a lot of summer surface melt, but the data indicates it is in equilibrium

The Australian Antarctic Division will however be watching Amery closely to see if it reacts at all. The division’s scientists have instrumentation in the region.

It’s possible the loss of such a big berg will change the stress geometry across the front of the ice shelf. This could influence the behaviour of cracks, and even the stability of Loose Tooth.

D28 is calculated to be about 210m thick and contains some 315 billion tonnes of ice.

The name comes from a classification system run by the US National Ice Center, which divides the Antarctic into quadrants.

The D quadrant covers the longitudes 90 degrees East to zero degrees, the Prime Meridian. This is roughly Amery to the Eastern Weddell Sea.

D28 is dwarfed by the mighty A68 berg, which broke away from the Larsen C Ice Shelf in 2017. It currently covers an area more than three times as big.

Nearshore currents and winds will carry D28 westwards. It’s likely to take several years for it to break apart and melt completely.

West Antarctica is melting—and it’s our fault

Pine Island Glacier, in West Antarctica, is retreating quickly. In 2014, this iceberg, 20 miles wide, broke off the tongue of the glacier and floated away. Other chunks of ice continue to shear off the glacier.


The fingerprints of human-caused climate change have made it Antarctica, a new study shows


THE TOWERING GLACIERS of West Antarctica hold the fate of the world’s coasts in their flanks. Their collapse could send sea levels up by at least a foot by 2100—and potentially much more.

For years, scientists have watched and learned that those glaciers are crumbling and melting, the rate speeding up over the decades and imperiling the stability of the entire ice sheet. But while the science was clear that human influences on climate would affect the ice down the line, it has been hard to tell whether human-driven global warming has affected the melting already underway.

Now, a team has unraveled evidence of that human influence. In a study published Monday in Nature Geoscience, a team of scientists showed that over the past century, human-driven global warming has changed the character of the winds that blow over the ocean near some of the most fragile glaciers in West Antarctica. Sometimes, those winds have weakened or reversed, which in turn causes changes in the ocean water that laps up against the ice in a way that caused the glaciers to melt.

“We now have evidence to support that human activities have influenced the sea level rise we’ve seen from West Antarctica,” says lead author Paul Holland, a polar scientist at the British Antarctic Survey.

The ocean eats the ice

The massive West Antarctic ice sheet holds something like 6 percent of the world’s fresh water frozen in its guts. If it all melted away, global sea levels would rise by about 10 feet or more. That’s not likely to happen anytime particularly soon, scientists think, but some parts of the ice sheet are particularly vulnerable, in danger of crossing a crucial “tipping point” if they retreat too far. (Read about the “tipping point” here).

In the past decades, some glaciers in the region have been retreating shockingly quickly. Pine Island Glacier and Thwaites Glaciers, for example, are losing about 100 billion tons of ice each year, and more in bad years. (See what a 10 billion ton chunk of ice looks like in this video).

The glaciers have been receding because their snouts spill over the edge of the continent into the surrounding ocean, which is warmer than the ice. The warm water melts away the ice.

Just how warm the ocean is, though, matters a lot. Over decades, the temperature of the water has waxed and waned, driven in part by natural climate cycles that send different water masses close to the edge of the ice sheet at different times, cycling through from cold to a little less cold every five years or so.

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SEE THE CRACK SPLITTING AN ANTARCTIC ICE SHELF IN TWOStunning drone footage shows how an iceberg the size of Houston, Texas is holding on by a thread.

The main thing that controls whether warm water makes it to the edge of the ice sheet, it turns out, is the strength of the winds a little bit farther offshore, in the heart of the icy, bitter Amundsen Sea. Sometimes, those winds—cousins of the famous raging band of Southern Ocean winds known as the Roaring 40s—slacken or even reverse. When they do, more warm water ends up near the edge of the ice sheet, which means more ice melts away. (See what the world would look like if all the ice melted away).

“In the 1920s, the winds were pretty much consistently blowing toward the west,” says Holland. “So in the old days, it was cold all the time—it flopped between cold and very cold.”

But now, because of the slow warming of the planet, the whole baseline has moved up. Instead of the cycle flipping between cold and very cold, the flip is between warm and cold.

Scientists knew that the strength of the winds in this region of the Amundsen Sea affected the water temperature. Records of wind strength and direction only went back until 1979. But the patterns in this region match up nearly perfectly with conditions far away, in the tropical Pacific Ocean, where much better, longer-term records exist—so the team could extrapolate how the polar-region winds have changed over the last century.

They used a suite of climate models to look at how the wind patterns would have evolved over the last 100 years if human-caused global warming weren’t in play, and compared that with what the winds actually did. Today’s pattern—with about equal west-flowing and east-flowing winds—means the whole region ends up quite a bit warmer than it was 100 years ago, when the wind flowed toward the west most of the time.

Ice out of Balance

In the past, and even up to the early part of the record the scientists looked at in the 1920s, ice melted during warm phases and grew back during cold phases. But over the last century, that balance has come undone. The shifting winds and warm ocean phases have eaten away at the ice more quickly than it’s being replaced.

Several particularly notable moments of wind-flipping, like in the 1970s, matched up closely with major retreats of the Pine Island and Thwaites glaciers.

Those glaciers are particularly sensitive to melting at their snouts. The ground underneath them, it turns out, is concave, like a bowl. The glacier ice is attached the “rim” of the bowl, but if it melts back past that edge, warm ocean water can spill underneath it and melt it even more quickly from the bottom.

In 1974, one of these strong moments of melting pushed the glaciers past one of these “rims,” and since then the glacier has melted much more quickly than it did before—at least 50 percent more melt after that un-groundig than before, said Eric Steig, an atmospheic and ice core scientist at the University of Washington and an author of the paper.

The suspect has been identified—and it’s us

The ultimate cause of the wind patterns, they found, is human-caused climate change. The extra greenhouse gases humans have pumped into the atmosphere over the past few hundred years have changed the way heat moves around the planet so thoroughly that they’ve changed the shape of the basic wind patterns at the poles.

The Antarctic ice sheet sat more or less stable in shape and size for many thousands of years. But about a century ago, pieces of it started to retreat in measurable ways. That’s well within the time frame when carbon dioxide and other greenhouse gases had started to accumulate thickly in the atmosphere, so it seemed logical to think that human influence was affecting the ice. But Antarctica is a complicated place that changes a lot because of natural variability, so it has been challenging to pinpoint the extent of human influence on the changes.

“It was very hard to imagine that the ice sat around happily for millennia and then decided to retreat naturally just as humans started perturbing the system, but the evidence for forcing by natural variability was strong,” writes Richard Alley, a climate scientist at Pennsylvania State University, in an email.

But a warming planet has very clearly changed the way winds move around Antarctica—and that change is likely to continue, unless something drastic happens to slow or reverse the warming process.

“If we carry this pattern forward, we may move to a situation where we’re flipping between warm and very warm,” says Holland. And that could be devastating for the ice.

But the future isn’t yet written, Steig stressed. Keeping future greenhouse gas emissions in check would go a long way toward keeping those crucial winds from weakening further, the water under the edge of the ice chilly, and the ice frozen.

“[West Antarctic Ice Sheet] melting will affect everyone,” says Steig. “The effects will be global, because sea level will rise globally.”

A new map is the best view yet of how fast Antarctica is shedding ice

The research could help improve projections of sea level rise

8:00AM, AUGUST 5, 2019

ICE ICE BABY  Glaciologists used observations from a cohort of satellite missions over decades to create the most detailed map yet of ice flow across Antarctica.

Decades of satellite observations have now provided the most detailed view yet of how Antarctica continually sheds ice accumulated from snowfall into the ocean.

The new map is based on an ice-tracking technique that is 10 times as precise as methods used for previous Antarctic surveys, researchers report online July 29 in Geophysical Research Letters. That offered the first comprehensive viewof how ice moves across all of Antarctica, including slow-moving ice in the middle of the continent rather than just rapidly melting ice at the coasts.

Charting Antarctic ice flow so exactly could reveal the topography of the ground underneath, as well as improve forecasts for how much ice Antarctica stands to lose to the ocean in the future. Ice melting off the continent is already known to be a driver of global sea level rise (SN: 7/7/18, p. 6).

Glaciologists at the University of California, Irvine, uncovered subtle movements of Antarctic ice with a kind of measurement called synthetic-aperture radar interferometric phase data. By using a satellite to bounce radar signals off a patch of ice, researchers can determine how quickly that ice is moving toward or away from the satellite. Combining observations of the same spot from different angles reveals the speed and direction of the ice’s motion along the ground.

Covering ground

A new map based on satellite radar data reveals the velocity of ice flow across Antarctica from areas of high elevation (thick black lines) to the coasts. Inland ice moves incredibly slowly — much of it plods along at fewer than 10 meters per year. Closer to the ocean, ice can travel hundreds to thousands of meters per year.

Velocity of ice flowing across Antarctica varies by location

Antarctica map

To get multiple vantage points of the same swathes of ice, researchers had to cobble together data from about half a dozen satellites launched by Canada, Europe and Japan since the early 1990s. “Each brought a little piece of the puzzle,” says study coauthor Eric Rignot.

The resulting map reveals how ice flows from points of high elevation, known as basin boundaries toward the coast. For 80 percent of Antarctica, the map shows average ice velocity down to about 20 centimeters per year. That’s a major upgrade from previous maps, which relied on ice-tracking techniques with uncertainties of a few meters per year.

In 2021, NASA and the Indian Space Research Organization plan to launch a satellite that will gather enough data to update this map every few months — allowing scientists to better monitor how ice flow across Antarctica changes as the climate changes.

If you act now you can maybe avoid the worst of climate change. But you know you’re not going to

As the crisis escalates…

… in our natural world, we refuse to turn away from the climate catastrophe and species extinction. For The Guardian, reporting on the environment is a priority. We give reporting on climate, nature and pollution the prominence it deserves, stories which often go unreported by others in the media. At this pivotal time for our species and our planet, we are determined to inform readers about threats, consequences and solutions based on scientific facts, not political prejudice or business interests.

Running the numbers on an insane scheme to save Antarctic ice


It would take a lot. Like a real lot.

Antarctica's Pine Island Glacier sheds some icebergs. Could we... sort of... put them back?
Enlarge / Antarctica’s Pine Island Glacier sheds some icebergs. Could we… sort of… put them back?

Imagine, if you will, the engineers of the king’s court after Humpty Dumpty’s disastrous fall. As panicked men apparently competed with horses for access to the site of the accident, perhaps the engineers were scoping out scenarios, looking for a better method of reassembling the poor fellow. But presumably none of those plans worked out, given the dark ending to that fairy tale.

A recent study published in Science Advances might be relatable for those fairy tale engineers. Published by Johannes Feldmann, Anders Levermann, and Matthias Mengel at the Potsdam Institute for Climate Impact Research, the study tackles a remarkable question: could we save vulnerable Antarctic glaciers with artificial snow?

Keeping our cool

Antarctica’s ice is divided into two separate ice sheets by a mountain range, with the smaller but much more vulnerable West Antarctic Ice Sheet representing one of the biggest wildcards for future sea level rise. In 2014, a study showed that two of the largest glaciers within that ice sheet—known as the Pine Island Glacier and Thwaites Glacier—had likely crossed a tipping point, guaranteeing a large amount of future ice loss that would continue even if global warming were halted today.

Much of the bedrock beneath the West Antarctic Ice Sheet is actually below sea level, though it’s buried below kilometers of solid ice. This makes for situations where the bed beneath the ice slopes down as you go inland from the coast. That’s inherently unstable, and once a glacier starts retreating downslope, the invading water provides an increasing floating force that reduces the sliding friction that slows the seaward flow of ice.

In the case of the Pine Island and Thwaites Glaciers, it seems that this is exactly what’s happening. Although this process can take centuries to fully play out, this portion of the ice sheet contains enough ice to raise global sea level by more than a meter.

Is there some extraordinary measure that could prevent that loss and preserve these glaciers? It’s the kind of question people will often ask, and scientists (who know the scale of these things) generally ignore as implausible.

But in this case, the researchers decided to go wild. Using a computer model of the ice sheet, they simulated the effects of adding huge amounts of ice near the front of these two glaciers. The idea works like this: Where a glacier meets the sea, it transitions from grounded to floating. Behind this “grounding line,” the glacier sits on the bedrock and sediment beneath; in front it gets thinner and floats as an ice shelf. To preserve the glacier, you need to keep that grounding line from retreating downhill. Thicken the ice on the inland side of the grounding line, and the thickness of ice flowing over the line and into the ice shelf increases—its weight keeps the grounding line pinned in place.

This map shows bedrock elevation beneath the ice sheet, with the white box highlighting the area of the Pine Island and Thwaites Glaciers where snow would be added in this scenario.
Enlarge / This map shows bedrock elevation beneath the ice sheet, with the white box highlighting the area of the Pine Island and Thwaites Glaciers where snow would be added in this scenario.

The researchers played around with different amounts of ice added to the glaciers for different periods of time, ranging from 10 year treatments to 50 years. Spreading it out over a longer period could mean a less preposterous addition of ice each year, but they found that the total amount has to increase if you do it that way. So in the end, the scenario they selected was 7,400 billion tons of ice added over 10 years. That was enough to restabilize these glaciers, preventing their inexorable decline.

Two for one special

To put that into context, removing that much seawater from the ocean would lower global sea level by about 2 millimeters per year. Current total sea level rise is a little over 3 millimeters per year, so it would be like nearly halting sea level rise… by bailing water out of the ocean. We can call that a bonus positive.

This analysis is more about what it would take than what such a scheme would look like, but the basic options are to pump water up and hose it around—hoping it freezes quickly—or to freeze it into snow like the world’s most awkwardly located ski resort.

Here, the researchers transition to listing all the reasons this is impractical and all the negative impacts it could have. For starters, the seawater would have to be desalinated since salt would probably affect the physics and behavior of the ice. Simply pumping that much water up the 640 meters and spreading it over an area nearly the size of West Virginia would require the power of something like 12,000 wind turbines—and that’s without the very substantial energy requirements for desalination and snow-making.

“The practical realization of elevating and distributing the ocean water would mean an unprecedented effort for humankind in one of the harshest environments of the planet,” the researchers write.

The impacts on Antarctic ecosystems could also be huge. Pumping that water out of the sea near the coast would significantly alter the circulation of water, which might even become somewhat self-defeating, as it could bring more warm water up against the ice shelf, increasing melt.

In the Potsdam Institute’s press release, Levermann puts it this way: “The apparent absurdity of the endeavour to let it snow in Antarctica to stop an ice instability reflects the breath-taking dimension of the sea-level problem. Yet as scientists we feel it is our duty to inform society about each and every potential option to counter the problems ahead.”

And to be clear, this is in addition to halting climate change—the scenario the numbers are based on assumes the temperatures don’t keep rising. But as the alternative is eventual inundation of parts of the world’s coastal cities, an argument can be made that the cost could be worth paying. It least it gives us an idea just how hard it would be to put Humpty Dumpty back together again.

Marine ice sheet instability amplifies and skews uncertainty in projections of future sea-level rise

Alexander A. RobelHélène Seroussi, and Gerard H. Roe
  1. Edited by Isabel J. Nias, Goddard Space Flight Center, Greenbelt, MD, and accepted by Editorial Board Member Jean Jouzel June 11, 2019 (received for review March 20, 2019)


The potential for collapse of the Antarctic ice sheet remains the largest single source of uncertainty in projections of future sea-level rise. This uncertainty comes from an imperfect understanding of ice sheet processes and the internal variability of climate forcing of ice sheets. Using a mathematical technique from statistical physics and large ensembles of state-of-the-art ice sheet simulations, we show that collapse of ice sheets widens the range of possible scenarios for future sea-level rise. We also find that the collapse of marine ice sheets makes worst-case scenarios of rapid sea-level rise more likely in future projections.


Sea-level rise may accelerate significantly if marine ice sheets become unstable. If such instability occurs, there would be considerable uncertainty in future sea-level rise projections due to imperfectly modeled ice sheet processes and unpredictable climate variability. In this study, we use mathematical and computational approaches to identify the ice sheet processes that drive uncertainty in sea-level projections. Using stochastic perturbation theory from statistical physics as a tool, we show mathematically that the marine ice sheet instability greatly amplifies and skews uncertainty in sea-level projections with worst-case scenarios of rapid sea-level rise being more likely than best-case scenarios of slower sea-level rise. We also perform large ensemble simulations with a state-of-the-art ice sheet model of Thwaites Glacier, a marine-terminating glacier in West Antarctica that is thought to be unstable. These ensemble simulations indicate that the uncertainty solely related to internal climate variability can be a large fraction of the total ice loss expected from Thwaites Glacier. We conclude that internal climate variability alone can be responsible for significant uncertainty in projections of sea-level rise and that large ensembles are a necessary tool for quantifying the upper bounds of this uncertainty.

In marine ice sheets, the grounding line is a critical boundary where ice flowing from the ice sheet interior becomes thin enough to float in ocean water. The grounding line location and ice flux are sensitive functions of the depth of the surrounding ocean (13). When the bedrock beneath the grounding line is reverse sloping (i.e., deepens toward the ice sheet interior), a small retreat of the grounding line onto deeper bed leads to greater ice flux and therefore more retreat. This positive flux feedback leads to the potential for rapid and irreversible retreat wherever the bed is reverse sloping, which has been termed the “marine ice sheet instability” (4). Rapid ice loss from the Antarctic ice sheet through this instability will likely drive sea-level rise beyond the next century (56). However, projections of future sea-level rise are uncertain due to imperfect representation of ice sheet processes in models, unknown future anthropogenic emissions, and the internal variability of future climate forcing of ice sheets. Even with improvements in ice sheet models and climate projections, there will always remain a component of sea-level projection uncertainty that cannot be reduced due to the fundamentally unpredictable internal variability of the climate system which causes ice sheet change. This fundamental lower bound in the uncertainty of projections due to internal climate variability (for ice sheets and other elements of the climate system) has been termed “irreducible uncertainty” (7). The inevitability of uncertainty remaining in sea-level projections necessitates robust modeling of the ice sheet dynamical factors which produce uncertainty in future ice sheet projections, for which there is no existing theoretical framework. In particular, it is critically important to constrain the upper bounds of uncertainty in sea-level rise projections, which have a disproportionate influence on planning for coastal adaptation measures (8).

Ice sheets evolve in response to changes in climate variables (i.e., climate “forcing”), such as snowfall and ocean temperature. The amount and structure of uncertainty in projections of the future ice sheet contribution to sea-level rise can thus be determined through large ensembles of ice sheet model simulations, which are plausible realizations of the future evolution of an ice sheet in response to climate forcing (see Fig. 1Upper for a conceptual illustration of an ensemble). Each ensemble member is distinguished by selecting either a unique set of model parameters or one realization of future variable climate forcing from a distribution of possibilities. At a particular point in time, the statistical properties of the full ensemble represent the probability distribution of ice sheet state, represented by a variable such as extent or volume (conditioned on the probability of the model parameters or climate variability having particular values). The spread (or standard deviation [SD]) of the probability distribution quantifies the amount of uncertainty in the projection. In a probability distribution that is symmetric, the skewness is 0, and the projected change in ice sheet volume is equally likely to fall above or below the mostly likely projection (Fig. 1Lower Left). A negative skewness of the probability distribution indicates that the probability of ice sheet volume turning out to be below the most likely projection is greater than that of ice sheet volume turning out to be above the most likely projection (and vice versa for positive skewness). Put another way, a negative skewness indicates that the probability of worst-case scenarios (i.e., more ice sheet mass loss and corresponding sea-level rise than is expected from the highest-likelihood projection) is greater than the probability of best-case scenarios (of less sea-level rise than the highest-likelihood projection).

Fig. 1.

(Upper) Conceptual illustration of an evolving ensemble of ice sheet model simulations, where each solid line is a single plausible realization of the future ice sheet evolution. Dashed colored lines indicate two time slices, for which probability distributions are provided (Lower Left and Lower Right). The statistical properties of the probability distribution of ensemble simulations change with time from a narrow, symmetric distribution at early times (blue dashed line, Lower Left) to a wide, asymmetric distribution with negative skewness (red dashed line, Lower Right), making the probability of ice sheet volumes below the most likely projection many times greater than that of ice sheet volumes above the most likely projection (arrows show example of ice sheet volumes above and below the most likely ice sheet volume projection).

In this study, we develop a framework for determining how marine ice sheet processes produce uncertainty in projections of future sea level. We do so using 2 complementary approaches: 1) Stochastic perturbation analysis of a simple model of marine ice sheet evolution with one evolving quantity and 2) statistical analysis of a large number of simulations of the future evolution of a West Antarctic glacier using a state-of-the-art numerical ice sheet model with many thousands of evolving quantities. These 2 approaches represent end members of the hierarchy of modern ice sheet models. They provide both a theoretical framework for understanding the sources of uncertainty in projections of the future ice sheet contribution to sea level and an application of this framework to an actual glacier that is thought to be undergoing the marine ice sheet instability.

Stochastic Perturbation Theory

Over the past several decades, much of the observed increase in Antarctic ice loss has been caused by ocean-driven ice sheet melting (9). Our goal in this study is thus to quantify the uncertainty in projected ice sheet state that is caused by uncertainty in ocean-induced ice sheet melt, although the principles involved are extendable to uncertainty in other climate forcing (or uncertainty in glaciological parameters). We start by mathematically and numerically analyzing the uncertainty in ice sheet state simulated by a minimal model of grounding-line migration for a glacier under climate forcing (1011)


[1]where L is the distance of the grounding line from the glacier onset, and hg=ρwρibghg=−ρwρibg is the thickness of ice at the grounding line, which depends on the ratio of seawater (ρwρw) and ice (ρiρi) densities and the local bedrock depth (bgbg). This model, which is derived and discussed in more detail in Robel et al. (11), tracks the total mass balance of the glacier, captured in 3 processes. The first term captures ice entering as snowfall over the glacier surface at accumulation rate P (averaged through glacier geometry: L and hghg). The second term captures ice leaving the glacier due to ice flow through the grounding line (γhβ1gγhgβ−1). The third term captures ocean-induced melt at the grounding line (η). The parameters β and γ are related to the balance of glaciological processes which contribute to setting the velocity of ice at the grounding line (e.g., gravitational driving stress, basal sliding, and ice shelf buttressing). Observations (12), mathematical analyses (1313), and numerical simulations (111415) have all shown that grounding-line velocity is generally a nonlinear function of grounding-line ice thickness (as we assume in Eq. 1), even during periods of transient grounding-line migration, although there is perhaps some variation in the exact value of β that applies in such a situation. Still, this minimal model is meant as a tool to understand the processes which drive uncertainty in simulations of marine ice sheet instability, not a means for making actual predictions of ice sheet change. As we show later on, the conclusions drawn from this minimal model are reproduced in a state-of-the-art ice sheet model which does not make the same simplifying assumptions.

In Eq. 1, the rate at which the grounding line migrates in response to ocean-induced melting (or freezing) is η=η¯+η(t)η=η¯+η′(t), consisting of a time-averaged component (η¯η¯) and a time-variable component (η(t)η′(t)). The time-averaged ocean forcing may be uncertain and so is drawn from a Gaussian distribution with SD σPσP. The time-variable ocean forcing is a first-order autoregressive Gaussian noise process with interannual SD σFσF, and decorrelation timescale τFτF. Other studies have shown using a complex spatially resolved model that ocean-induced grounding-line variability is filtered through the frequency-dependent response of the ice shelf to ocean forcing (16). In this minimal model, we assume a simpler form for η in which all ocean-induced grounding-line migration is the result of melting directly at the grounding line and neglects effects from sub-ice shelf melt and buttressing. While this assumption will likely produce some quantitative difference than that of a model which includes sub-ice shelf melt beyond the grounding line, the more complicated ice-shelf–resolving simulations in the next section show that the qualitative aspects of our mathematical analysis do not appear to be changed by such detailed considerations.

Fig. 2 shows ensembles (with 10,000 simulations each) of simulated grounding-line migration over a bed of constant slope, calculated using Eq. 1 (details in Materials and Methods). The only forcing during the simulation period shown is ocean-induced grounding-line migration (η). The ensemble spread (represented in Fig. 2 by the interquartile range) captures the uncertainty in projected grounding-line position due to uncertainty in ocean forcing. On a forward-sloping bed (green shading/lines), small interannual forcing in the grounding-line position (σF=100σF=100 m/y, η¯=0η¯=0) produces an ensemble spread that remains small, bounded, and symmetric. For the same stochastic forcing on a reverse-sloping bed (orange shading/lines), all ensemble members retreat, as the ensemble spread grows rapidly without bound and becomes skewed (negatively) toward more retreat.

Evolution of a 10,000-member ensemble of minimal model (Eq. 1) simulations of grounding-line retreat over idealized constant-slope bed topography and variability in ocean forcing. (A) Ensemble interquartile range (shading spans 25th percentile to 75th percentile). (B) SD derived from numerically calculated ensemble statistics (solid lines) and analytic predictions from stochastic perturbation theory (circles). (C) Skewness derived from numerically calculated ensemble statistics (solid lines) and analytic predictions from stochastic perturbation theory (circles). Negative skew indicates more retreated grounding line. There is no analytic approximation available for skewness under autocorrelated forcing (see SI Appendix for discussion of stochastic perturbation theory). Pink shading and lines are simulations on a reverse-sloping bed (bx=4×10−3) with constant ocean forcing, selected from a Gaussian distribution. Blue shading and lines are simulations on a reverse-sloping bed (bx=4×10−3) with interdecadal variability in ocean forcing (τF=10 y). Orange shading and lines are simulations on a reverse-sloping bed (bx=3.5×10−3) with interannual variability in ocean forcing (τF=1 y). Green shading and lines are simulations on a forward-sloping bed (bx=−10−3) with interannual variability in ocean forcing (τF=1 y). In all simulations, P=0.35 m/y, γ=7.8×10−9 m−2.75⋅y−1, and β=4.75. In simulations with variable ocean forcing (blue, orange, green), η¯=0 and σF=100 m/y. In simulations with uncertainty in constant ocean forcing (pink), σP=50 m/y.

” data-icon-position=”” data-hide-link-title=”0″>Fig. 2.

Fig. 2.

Evolution of a 10,000-member ensemble of minimal model (Eq. 1) simulations of grounding-line retreat over idealized constant-slope bed topography and variability in ocean forcing. (A) Ensemble interquartile range (shading spans 25th percentile to 75th percentile). (B) SD derived from numerically calculated ensemble statistics (solid lines) and analytic predictions from stochastic perturbation theory (circles). (C) Skewness derived from numerically calculated ensemble statistics (solid lines) and analytic predictions from stochastic perturbation theory (circles). Negative skew indicates more retreated grounding line. There is no analytic approximation available for skewness under autocorrelated forcing (see SI Appendix for discussion of stochastic perturbation theory). Pink shading and lines are simulations on a reverse-sloping bed (bx=4×103bx=4×10−3) with constant ocean forcing, selected from a Gaussian distribution. Blue shading and lines are simulations on a reverse-sloping bed (bx=4×103bx=4×10−3) with interdecadal variability in ocean forcing (τF=10τF=10 y). Orange shading and lines are simulations on a reverse-sloping bed (bx=3.5×103bx=3.5×10−3) with interannual variability in ocean forcing (τF=1τF=1 y). Green shading and lines are simulations on a forward-sloping bed (bx=103bx=−10−3) with interannual variability in ocean forcing (τF=1τF=1 y). In all simulations, P=0.35P=0.35 m/y, γ=7.8×109γ=7.8×10−9 m−2.75⋅y−1, and β=4.75β=4.75. In simulations with variable ocean forcing (blue, orange, green), η¯=0η¯=0 and σF=100σF=100 m/y. In simulations with uncertainty in constant ocean forcing (pink), σP=50σP=50 m/y.

The growth in ensemble spread (i.e., uncertainty) occurs because the marine ice sheet instability amplifies (rather than damps) small perturbations from stochastic ocean forcing. These growing perturbations accumulate over time, leading to a divergence between ensemble members, which each experience a different series of perturbations from ocean forcing. The skewness of the ensemble can be understood physically and from an analysis of Eq. 1. For a retreating ice sheet, the rate of retreat is set by the difference between two fluxes: The accumulation flux and the grounding-line flux. If the grounding-line flux is more sensitive to the position of the grounding line than the accumulation (which it is for sufficiently nonlinear grounding-line flux), the net effect will be that the rate of retreat of more-retreated ensemble members will be greater than the rate of retreat of the less-retreated ensemble members. The result is that the retreat of the ensemble becomes progressively more negatively skewed with time. In ensembles where all simulations are advancing, the most advanced ensemble members accelerate faster, producing a positive skew.

Observations indicate that climate forcing of glaciers in Antarctica (and elsewhere) exhibits strong variability on decadal timescales (1718). In our minimal model, when stochastic forcing has decadal persistence, the ensemble spread and skewness grow considerably faster (blue shading/lines in Fig. 2). Such an amplified glacier response to temporal persistence in forcing agrees with previous model studies of mountain glaciers (19) and periodically forced ice streams (162021).

For temporal ocean variability, stochastic perturbation theory (22) (SI Appendix) provides a theoretical framework for determining the physical processes which control the amplification and skewing of uncertainty in ice sheet projections. Analytic approximations for the spread and skewness of ensembles derived from stochastic perturbation theory (circles in Fig. 2 B and C) match well with numerically calculated ensemble statistics. This theoretical framework shows that ensemble spread grows exponentially with a rate that is proportional to the bed slope and the nonlinearity in grounding-line ice flux (β in Eq. 1). Thus, when the bed is forward sloping (negative), the ensemble spread remains bounded. When the bed is reverse sloping (positive), the marine ice sheet instability causes the ensemble spread to grow exponentially without bound. The ensemble variance is also proportional to the decorrelation timescale of the forcing, implying greater uncertainty in projections when climate forcing is persistent on longer timescales.

As alluded to above, the skewness of the ensemble is caused by the changing rate of grounding-line migration over a reverse-sloping bed. It can be shown analytically (see SI Appendix for details) that when the grounding-line ice flux is sufficiently nonlinear with respect to ice thickness (β>3β>3 in Eq. 1), then ensembles of a retreating grounding line will tend to be skewed toward more retreat. Conversely, when grounding-line ice flux is linear or weakly nonlinear (β<3β<3), then ensembles will tend to be skewed toward less retreat. In a wide range of realistic settings, we expect ensembles to skew toward more retreat during the retreating phase of the marine ice sheet instability because of the high-degree nonlinearity of grounding-line ice flux (β=4.75β=4.75 in ref. 1β=5β=5 in ref. 2β=4β=4 in ref. 3). In other words, the fact that the probability distribution is skewed in the direction of more sea-level rise is a fundamental consequence of the strong nonlinearity inherent in grounding-line dynamics.

Uncertainty in the time-averaged ocean forcing (η¯η¯; pink shading/lines in Fig. 2) produces even more ensemble spread (for relatively less uncertainty, σP=50σP=50 m/y) and further indicates the importance of the marine ice sheet instability for amplifying and skewing uncertainty in ice sheet projections. Uncertainty in the time-averaged climate forcing can be thought of as a limiting case of the response to an initial impulse with an infinite decorrelation time (τFτF→∞). However, for such a nonstochastic case, there is no formal limit from stochastic perturbation theory in which the ensemble spread can be predicted.

Large Ensembles of Thwaites Glacier Instability.

To demonstrate that the intuition gained from the theoretical framework developed in the previous section applies to realistic glacier models, we simulate ensembles of the future retreat of Thwaites Glacier in West Antarctica using the Ice Sheet System Model (ISSM), a state-of-the-art finite-element model of ice sheet flow (23). Thwaites Glacier rests on a reverse-sloping bed and is currently retreating rapidly, which is argued to be the result of the marine ice sheet instability (2425). In ISSM, as in other models, ocean-induced ice sheet melting is parameterized with a depth-dependent melt rate, with maximum melt rate, MmaxMmax, prescribed at some depth (25). We treat MmaxMmax as a first-order autoregressive noise process that varies monthly with a prescribed decorrelation timescale (τFτF), a mean of 80 m/y, no long-term trend, and no variation in space. Many observations and models indicate that subice shelf melt rates at glaciers in the Amundsen Sea, and elsewhere in Antarctica, exhibit strong variability on decadal (and longer) timescales (172627). A short run of a regional ocean model simulation for the Amundsen Sea region (SI Appendix) produces variability in MmaxMmax with interannual SD of 1.4 m/y. This estimate of variability is likely an underestimate since the ocean simulation was run for only 15 y (the time period over which reanalysis forcing is available) and did not include coupled ocean–atmosphere feedbacks. Thus, for our baseline ensemble of Thwaites Glacier, our conservative estimate for the statistics of ocean-induced melt variability is τF=10τF=10 y and σM=1.4σM=1.4 m/y. In reality, we also expect that MmaxMmax varies in space, due to (for example) the Coriolis effect on ocean circulation in the subshelf cavity, which would quantitatively (but not necessarily qualitatively) affect our results.

Fig. 3A shows the evolution of the probability distribution of a 500-member ensemble of ISSM-simulated ice volume at Thwaites Glacier in response to decadal variability in subice shelf melt rate. All ensemble members initialized with the modern state of Thwaites Glacier eventually reach complete deglaciation (Fig. 3B), in agreement with previous studies (2425). The rate of grounding-line migration (Fig. 3C) experiences significant variability over the course of the retreat due to the stochastic ocean forcing and the presence of forward-sloping “speed bumps” in the bed topography, both of which can slow the rate of retreat or even cause advance for short durations (28). Even with the relatively conservative assumption that there is no variability in surface mass balance and a small amplitude of subshelf melt variability (representing <2%<2% of the time-averaged subshelf melt), the spread in the ensemble spans ∼20 cm of uncertainty in projected sea-level rise during periods of fast retreat (i.e., the green probability distribution functions [PDFs] in Fig. 3A), with a probability distribution skewed in the direction of lower ice volume (greater contribution to sea level). This uncertainty is over 25% of the entire sea-level rise due to deglaciation of Thwaites Glacier and 50% of the median sea-level rise achieved during those periods of fast retreat. This spread between simulations amounts to instantaneous differences of hundreds of kilometers in the grounding-line position (Fig. 3D). Following this growth of uncertainty during the centuries of most rapid retreat, the ensemble then contracts and skews in the opposite direction as individual ensemble members achieve complete deglaciation of Thwaites Glacier, due to the limited model domain used in our simulations. In simulations of the entire Antarctic Ice Sheet in which the marine ice sheet instability spreads to other glaciers (56), we would expect even faster amplification of uncertainty as multiple glaciers become involved in deglaciation.

Fig. 3.

Evolution of a 500-member ensemble of ISSM simulations of Thwaites Glacier evolution over 500 y (where year 0 in model time is the modern glacier state) in response to decadal variability and constant average in maximum subice shelf melt rate. (A) Evolution of ensemble PDF over time, plotted every 25 y, with probability on the y axis and Thwaites Glacier ice volume (in cm sea-level equivalent [SLE]) on the x axis. (B) Black lines are simulated ice volume contained in Thwaites Glacier catchment in cm SLE for all ensemble members. (C) Black dots are evolving grounding-line migration rates for all ensemble members (based on the centroid of the 2D grounding line). (D) Snapshots (red, orange, and pink lines) of grounding-line positions at year 635 in model time, from 5th percentile, 50th percentile, and 95th percentile ice volume ensemble members.

In Fig. 4, we compare Thwaites Glacier ensemble statistics, given a comparable amplitude (σM=1.4σM=1.4 m/y) of variability in MmaxMmax, but differing degrees of temporal persistence. As predicted by theory, ensemble spread (Fig. 4A) increases with longer persistence in forcing variability (proportional to τF−−√τFSI Appendix). During the century of fastest retreat, multidecadal ocean variability (yellow line; τF=30τF=30 y) produces skewed uncertainty that is nearly 50% of the total ice loss from Thwaites glacier or ∼40 cm of uncertainty in projected sea-level rise. Some studies have suggested that Antarctic glaciers may be subject to such multidecadal variability in forcing through low-frequency coupled modes of the ocean–atmosphere system (26) or sporadic detachment of very large tabular icebergs (29).

Fig. 4.

Evolution of uncertainty and skewness of uncertainty in four Thwaites Glacier ensembles (500 simulations each). Three of the ensembles have variability in ocean forcing specified using a first-order autoregressive model: Including variability at interannual (τF=1.1τF=1.1 y, blue line), interdecadal (τF=10τF=10 y, red line; Fig. 3), and multidecadal (τF=30τF=30 y, yellow line) timescales. One ensemble has no temporal variability, but the constant maximum subshelf melt rate is uncertain and so drawn from a Gaussian distribution (with σM=5σM=5m/y and the same mean as other ensembles, purple line). (A) “Fractional projection uncertainty” given by the ratio of ensemble spread (measured by ±2σ±2σ of ensemble) to total ice loss at the end of simulation: 4σvol/μvloss4σvol/μvloss. (B) Ensemble skewness, with negative skewness representing a distribution skewed toward lower total ice volume (more ice loss and more sea-level rise).

Poorly constrained subice shelf properties [such as roughness (30)] and the small scale of the turbulent ice–ocean boundary layer make it difficult to accurately simulate even the time-averaged subice shelf melt rate given some change in global climate. Consequently, we also consider uncertainty in the time-averaged subshelf basal melt rate (which may also result from uncertainties in future anthropogenic emissions) by keeping MmaxMmax constant in time, but varying it between ensemble members (drawing from a Gaussian distribution with SD of 5 m/y). As in the minimal model, this ensemble (purple line in Fig. 4) has a very strong amplification of skewed uncertainty due to the accumulation of differences in subshelf basal melt rate among ensemble members over the course of the instability. For several centuries, the spread in this ensemble amounts to nearly the entire signal of ice loss from Thwaites Glacier (i.e., some ensemble members have retreated completely while others have lost almost no ice at all), skewed in the direction of more ice loss throughout most of the early period of the simulation.

Discussion and Conclusions

Studies of the future evolution of the Antarctic Ice Sheet have estimated the uncertainty in future sea-level rise due to poorly constrained model parameters (563134). Other studies (35) have investigated the role of internal climate variability in the Greenland Ice Sheet contribution to sea-level rise, but with simulations that were too short to capture much of the marine ice sheet instability that may occur in the future. No study has provided a theoretical framework explaining the role of ice sheet dynamics in setting the amount and structure of uncertainty in sea-level rise projections. We provide such a theoretical framework in this study and find that ice sheet instabilities are amplifiers of uncertainty, which is a common mathematical property of unstable nonlinear systems (22). Although there are processes not considered here that might stabilize (36) or further destabilize (6) an ice sheet, our analysis shows that we should expect more rapid instability (of any kind) to cause more rapid uncertainty growth. Indeed, the theoretical framework developed in this study applies to a sufficiently broad set of assumptions regarding ice sheet dynamics, such that we expect that any type of ice sheet instability, regardless of the processes involved, will experience rapid growth in the ice sheet projection uncertainty during periods of most rapid instability. Integrating the contribution of marine ice sheet instability over many glaciers also integrates the uncertainty of each glacier’s future evolution, potentially leading to considerable uncertainty in sea-level projections, as has been seen in ensemble studies of total ice sheet contribution to future sea-level rise (56323435). We have shown that model ensembles can be used to quantify a range of possible scenarios for future sea-level rise, including potentially catastrophic scenarios of rapid sea-level rise. However, large model ensembles can be prohibitively expensive when extended to the entire Antarctic Ice Sheet. To fully capture the complete range of possible Antarctic futures, we will need efficient methods for uncertainty quantification (3237) and model order reduction that captures the complexities of ice sheet dynamics (3134). Such sophisticated methods will ensure that we can make the most useful sea-level projections beyond 2100 for those stakeholders who depend on them.

‘World’s most dangerous glacier’ could cause catastrophic sea level rise, study warns

A glacier in West Antarctica, known as “the world’s most dangerous,” could completely melt away and cause a rapid and “catastrophic” sea-level rise, a new study warns.

The study, published in the scientific journal PNAS, notes that the Thwaites Glacier is at a proverbial “tipping point” that could cause a neverending flow of ice into the world’s oceans.

“If you trigger this instability, you don’t need to continue to force the ice sheet by cranking up temperatures. It will keep going by itself, and that’s the worry,” said the study’s lead author and Georgia Tech professor Alex Robel, in a statement. “Climate variations will still be important after that tipping point because they will determine how fast the ice will move.”

The Thwaites Glacier is seen above.

The Thwaites Glacier is seen above. (NASA/OIB/Jeremy Harbeck)


NASA JPL scientist Helene Seroussi, who worked on the study along with Robel, said that the glacier could lose all of its ice over the next 150 years. “That would make for a sea level rise of about half a meter (1.64 feet),” Seroussi added in the statement.

According to the National Oceanic and Atmospheric Administration, sea levels “continue to rise at a rate of about one-eighth of an inch per year.”

The Thwaites Glacier is “the largest single source of uncertainty in projections of future sea-level rise,” according to the study’s abstract. If it were to collapse, it would make “worst-case scenarios of rapid sea-level rise more likely in future projections,” the abstract added.

“If you trigger this instability, you don’t need to continue to force the ice sheet by cranking up temperatures. It will keep going by itself, and that’s the worry.”

— Georgia Tech professor Alex Robel

The Antarctic ice sheet has more than 50 times the amount of ice than the mountain glaciers in the world combined, and eight times as much ice in the Greenland ice sheet, Robel added in the statement.

If and when the glacier becomes unstable, the after-effects would be considered “catastrophic.”

Thwaites Glacier acts like a giant cork that holds back the West Antarctic Ice Sheet.

Thwaites Glacier acts like a giant cork that holds back the West Antarctic Ice Sheet. (NASA/James Yungel)

“Once [the] ice is past the grounding line and only over water, it’s contributing to sea level because buoyancy is holding it up more than it was before,” Robel said. “Ice flows out into the floating ice shelf and melts or breaks off as icebergs.”

The grounding line is the line between where the ice sheet rests on the seafloor and where it extends over the water.

As is common for most sea-level studies, the time scale for the study was in centuries and simulations showed that the ice loss for the Thwaites Glacier started after 600 years. However, the researchers warn that if ocean temperatures continue to rise, the instability in the glacier could occur much faster than many expect.


“It could happen in the next 200 to 600 years. It depends on the bedrock topography under the ice, and we don’t know it in great detail yet,” Seroussi added.

Earlier this year, NASA scientists found a massive hole two-thirds the size of Manhattan under the Thwaites Glacier, a fact that left them disturbed.

The huge cavity – which is approximately 1,000 feet tall, about as tall as New York City’s Chrysler Building – is growing at the bottom of the glacier and is large enough to have once contained 14 billion tons of ice, according to NASA. Most of that ice has melted over the past three years.