Mathieu Morlighem, Dartmouth College

Antarctica's Thwaites Glacier got its nickname the “Doomsday Glacier” for its potential to flood coastlines around the world if it collapsed. It is already contributing about 4% of annual sea-level rise as it loses ice, and one theory suggests the glacier could soon begin to collapse into the ocean like a row of dominoes.

But is that kind of rapid collapse really as likely as feared? A new study of Thwaites Glacier's susceptibility to what's known as marine ice cliff instability offers some hope. But the findings don't mean Thwaites is stable.

Polar scientist Mathieu Morlighem, who led the study, explains the results.

Why is the Thwaites Glacier so important?

Thwaites Glacier drains a huge area of Antarctica's ice sheet – about 74,000 square miles (192,000 square kilometers), an expanse bigger than Florida. If a snowflake falls within that drainage system, it will eventually end up as part of an iceberg in the ocean off Thwaites.

What we are seeing with Thwaites Glacier right now is a disaster in slow motion.

The bedrock under Thwaites Glacier sits below sea level and slopes downward going inland, so the glacier gets deeper toward the interior of the ice sheet. Once the glacier begins losing more ice than it gains from new snowfall and starts to retreat, it's very hard to slow it down because of this slope. And Thwaites is already retreating at an accelerating rate as the climate warms.

Thwaites Glacier holds enough ice to raise global sea level by more than 2 feet (0.65 meters). Once Thwaites starts to destabilize, it also will destabilize neighboring glaciers. So, what happens to Thwaites affects all of the West Antarctic Ice Sheet, and that affects sea-level rise along coastlines everywhere.

What is marine ice cliff instability?

Marine ice cliff instability is a relatively new concept proposed by scientists in the past decade.

Many of the glaciers around Antarctica have huge floating extensions called ice shelves that buttress the glacier and slow its ice flow into the ocean. With the climate warming, we have seen some of these floating extensions collapse, sometimes very rapidly, in the span of a few weeks or months.

If Thwaites' ice shelf were to collapse, it would expose a very tall ice cliff facing the ocean along its 75-mile (120-kilometer) front. There is only so much force that ice can sustain, so if the cliff is too tall, it will collapse into the ocean.

Once that happens, a new ice cliff farther back would be exposed, and the new cliff would be even taller because it is farther inland. The theory of marine ice cliff instability suggests that if the cliffs collapse quickly enough, that could have a domino effect of ever-higher ice cliffs collapsing one after the other.

However, no one has observed marine ice cliff instability in action. We don't know if it will happen, because a lot depends on how quickly the ice collapses.

What did you discover about the risk to Thwaites?

When the theory of marine ice cliff instability was first introduced, it used a rough approximation of how ice cliffs might collapse once the ice shelf was gone.

Studies since then have determined that ice cliffs won't fail systematically until the ice is about 442 feet (135 meters) high. Even at that point, they would fail more slowly than projected until they became much taller.

We used three high-resolution models to explore what this new physical understanding of ice cliff instability would mean for Thwaites Glacier this century.

Our results show that if Thwaites' entire ice shelf collapsed today, its ice front would not rapidly retreat inland due to marine ice cliff instability alone. Without the ice shelf, the glacier's ice would flow much faster toward the ocean, thinning the front of the glacier. As a result, the ice cliffs wouldn't be as high.

We found that Thwaites would remain fairly stable at least through 2100. We also simulated an ice shelf collapse in 50 years, when the glacier's grounding line – where its grounded ice meets the ocean – would have retreated deeper inland. Even then, we found that marine ice cliff instability alone would not cause a rapid retreat.

The results call into question some recent estimates of just how fast Thwaites might collapse. That includes a worst-case scenario that the Intergovernmental Panel on Climate Change mentioned in its latest assessment report but labeled as “low likelihood.”

Thwaites is the glacier everyone is worried about. If you model the entire ice sheet, this is where marine ice cliff instability starts and where it propagates far inland. So, if Thwaites isn't as vulnerable to ice cliff failure as we thought, that's a good sign for the entire ice sheet.

But marine ice cliff instability is only one mechanism of ice loss. This finding doesn't mean Thwaites is stable.

What else is causing glaciers to retreat at an accelerating rate?

There are many processes that make the Antarctic ice sheet unstable, some of them very well understood.

Ice-ocean interactions explain most of the recent ice mass loss so far. Antarctica is a very cold place, so atmospheric warming isn't having a large effect yet. But warm ocean currents are getting under the ice shelves, and they are thinning the ice from below, which weakens the ice shelves. When that happens, the ice streams flow faster because there is less resistance.

Over the past few decades, the Amundsen Sea sector, where Thwaites and Pine Island glaciers are located, has seen an intrusion of warm water from the Antarctic Circumpolar Current, which has been melting the ice from below.

What does climate change have to do with it?

Antarctica can seem like a faraway place, but human activities that warm the planet – such as burning fossil fuels – are having dramatic effects at the poles. Ice loss contributes to sea-level rise, affecting coastal regions around the world.

People's choices today will determine how quickly the water rises.

Mathieu Morlighem, Professor of Earth Sciences, Dartmouth College

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Koki Ho, Georgia Institute of Technology and Mariel Borowitz, Georgia Institute of Technology

Most space mission systems historically have used one spacecraft designed to complete an entire mission independently. Whether it was a weather satellite or a human-crewed module like Apollo, nearly every spacecraft was deployed and performed its one-off mission completely on its own.

But today, space industry organizations are exploring missions with many satellites working together. For example, SpaceX's Starlink constellations include thousands of satellites. And new spacecraft could soon have the capabilities to link up or engage with other satellites in orbit for repairs or refueling.

Some of these spacecraft are already operating and serving customers, such as Northrop Grumman's mission extension vehicle. This orbiting craft has extended the lives of multiple communications satellites.

These new design options and in-orbit capabilities make space missions look more like large logistics operations on Earth.

We're researchers who have studied the space industry for years. We've studied how the space sector could learn lessons from companies like Amazon or FedEx about managing complex fleets and coordinating operations.

Lessons from the ground transportation network

Space mission designers plan their routes in order to deliver their payloads to the Moon or Mars, or orbit efficiently within a set of cost, timeline and capacity constraints. But when they need to coordinate multiple space vehicles working together, route planning can get complicated.

Logistics companies on the ground solve similar problems every day and transport goods and commodities across the globe. So, researchers can study how these companies manage their logistics to help space companies and agencies figure out how to successfully plan their mission operations.

One NASA-funded study in the early 2000s had an idea for simulating space logistics operations. These researchers viewed orbits or planets as cities and the trajectories connecting them as routes. They also viewed the payload, consumables, fuel and other items to transport as commodities.

This approach helped them reframe the space mission problem as a commodity flow problem – a type of question that ground logistics companies work on all the time.

Lessons from ground logistics infrastructure

New capabilities for refueling and repairing spacecraft in orbit create new opportunities as well as challenges.

Namely, space operators don't usually know which satellite will be the next one to fail or when that will happen. For these new technologies to be useful, space mission designers would need to come up with an infrastructure system. That could look like a fleet of service vehicles and depots in space that quickly respond to any unpredictable events.

Fortunately, space mission designers can learn from operations on the ground. City planners and emergency response organizations think through these types of challenges while determining where to locate hospitals or fire departments. They also consider these facilities' capacities to respond to unpredictable calls.

We can draw an analogy between a ground logistics system design and an in-space servicing system design. This way, researchers can leverage theories developed for ground logistics to improve the space mission design practice.

One study published in November 2020 developed a framework for servicing spacecraft on orbit using what logistics experts call spatial queuing theory. Researchers most commonly use this modeling theory to analyze the performance of a ground logistics system.

Lessons from ground warehouse management

In the past, individual spacecraft carried out their missions independently, so if a satellite failed, its mission engineers had to develop and send a replacement.

Now, for missions with multiple satellites, such as the Iridium satellite constellation, operators often maintain one or more spares on orbit.

This becomes complicated for constellations made up of hundreds or thousands of spacecraft. Mission designers want to ensure they have enough spare satellites in orbit so they don't have to interrupt the mission if one breaks. But sending too many spare satellites gets expensive.

When dealing with these types of large constellations, mission designers can learn from the methods Amazon and other ground companies use to manage their warehouses. Amazon puts these warehouses in specific places and stocks them with certain items to make sure the deliveries are handled efficiently.

Inventory management theories on the ground can help inform how space companies tackle these challenges.

A study published in November 2019 developed an approach that space companies could use to manage their spare strategies. This approach can help them decide where in orbit to allocate their spare satellites to meet their needs while minimizing any service interruptions.

International dimensions

Spacecraft operate in a complex and rapidly changing environment. Operators need to know where other missions are operating and what rules they should follow when refueling or repairing in space. In space, however, nobody has defined these rules yet.

Ships, aircraft and ground vehicles all have clear rules of the road to follow when interacting with other vehicles. For example, civilian ships and aircraft have to share their location with other vehicles and officials to help manage traffic.

Some researchers are examining what similar rules could look like for space. One study examined how developing rules based on a spacecraft's size, age or other attributes might help future space operations run more smoothly. For example, one rule might be that the spacecraft that launched most recently should take responsibility for maneuvering when there's another craft in its path.

With more satellites and spacecraft launching now than ever, companies and government agencies will need new technologies and policies to coordinate them. As space activity becomes more complex, researchers can continue to apply what they've learned on the ground to new missions in space.

Koki Ho, Associate Professor of Aerospace Engineering, Georgia Institute of Technology and Mariel Borowitz, Associate Professor of International Affairs, Georgia Institute of Technology

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Shaoyu Yuan, Rutgers University – Newark

In the competitive arena of global technology, China's ambitions in artificial intelligence stand out – not just for their scale but for their distinct strategic approach.

In 2017, the Chinese Communist Party declared its intent to surpass the United States to become the world leader in AI by 2030. This plan, however, is less about pioneering novel technologies and more about strategically adapting existing ones to serve state economic, political and social objectives.

While both China and the United States are actively pursuing AI technologies, their approaches differ significantly. The U.S. has traditionally led in fundamental AI research and innovation, with institutions such as Massachusetts Institute of Technology and Stanford and tech giants such as Google and Microsoft driving breakthroughs in machine learning. This innovation-first approach contrasts with China's focus on adaptation and application of existing technologies for specific state objectives.

The United States' AI development is primarily driven by a decentralized network of academic institutions, private companies and government agencies, often with competing interests and a focus on commercial applications. In contrast, China's AI strategy is more centralized and state directed, with a clear focus on supporting government initiatives such as social control and economic planning.

AI for ideological control

At the heart of China's AI strategy lies its effort to embed the technology in the machinery of the government's ideological control. A prime example is the Xue Xi chatbot developed by researchers at China's top-ranked university, Tsinghua University. Unlike Western AI models designed to foster open-ended dialogue, Xue Xi was trained in part on “Xi Jinping Thought” to indoctrinate users – likely initially to be party members in government – with Communist Party ideology.

This isn't just a singular initiative but part of a broader trend. AI-driven surveillance systems, like the facial recognition technology deployed across the Xinjiang region of China, enable the government to maintain tight control over the area's minority Muslim Uyghur population.

These technologies are not groundbreaking. They build on existing innovations but are finely tuned to serve the Communist Party's efforts to maintain social order and prevent dissent. China's AI prowess comes not by creating the newest technology but by mastering and deploying AI in ways that align with its ideological imperatives.

AI for economic control

China's AI strategy is also deeply intertwined with its economic ambitions. Faced with slowing growth, the Communist Party views technology as the essential tool for pulling the country out of its economic slowdown. This is particularly evident in sectors such as manufacturing and logistics, where AI is used to drive efficiencies and maintain China's competitive edge in global supply chains. For example, companies such as online retail giant Alibaba have developed AI-driven logistics platforms that optimize delivery routes and manage warehouse operations, ensuring that China remains the factory of the world.

Additionally, China's social credit system, which rates citizens on their civic and financial behavior, represents a significant strategic initiative where AI plays an increasingly crucial role. China's system is designed to monitor and influence citizen behavior on a massive scale. Although AI is not yet fully implemented across the entire social credit system, it is being integrated to track and analyze vast amounts of data, such as financial transactions, online interactions and social relationships in real time.

This data is then used to assign scores that can affect various aspects of life, from loan approvals to travel permissions. As AI becomes increasingly embedded in the system, it is likely, I believe, to further reinforce state control and ensure societal compliance, prioritizing government oversight over personal autonomy.

Strategic exports

On the international stage, China is exporting its AI technologies to expand its influence, particularly in developing nations. Through the Belt and Road Initiative, Chinese tech giants such as Huawei and ZTE are providing AI-driven surveillance systems to governments in Africa, Southeast Asia and Latin America. These systems, often framed as tools for improving public safety, are part of a larger strategy to export China's governance model.

For instance, in Zimbabwe, Chinese firms have helped implement a nationwide facial recognition system under the guise of combating crime. Political activists in Zimbabwe fear that technology is being used to monitor political opponents and activists, mirroring its use in China. By exporting AI technologies that are tightly integrated with state control, China is not only expanding its market share but also promoting its authoritarian model as a viable alternative to Western democracy.

AI for strategic military advantage

China's military ambitions are also tightly linked to its AI strategy. The People's Liberation Army, China's military, is investing heavily in AI-driven autonomous systems, including drones and robotic platforms. These technologies are not necessarily the most advanced in the world, but China is adapting them to fit its strategic needs.

China is developing AI systems to support its naval operations in the South China Sea, a region of significant geopolitical tension. China is deploying autonomous submarines and surveillance drones to monitor and potentially disrupt foreign military activities in the region. This strategic use of AI in military applications highlights China's focus on using existing technologies to achieve specific geopolitical objectives, rather than seeking innovation for its own sake.

Calculated strategy

China's approach to AI is a calculated strategy of adaptation and application, rather than raw innovation. By mastering the use of existing technologies and aligning them with state objectives, China is not only bolstering its domestic control but also reshaping global power dynamics.

Whether through ideological indoctrination, economic control, strategic exports or military advancements, China's AI playbook is a powerful reminder that in the realm of technology, how tools are used can be just as transformative as the tools themselves.

Shaoyu Yuan, Dean's Fellow at the Division of Global Affairs, Rutgers University – Newark

This article is republished from The Conversation under a Creative Commons license. Read the original article.