Spatial phenomena often exhibit heterogeneity across spatial extents and in proximity, making them complex to model-especially in dynamic regions like ice shelves and sea ice. In this study, we address this challenge by exploring the linkages between sea ice retreat and Antarctic ice shelf (AIS) melt. Although atmospheric forcing and basal melting have been widely studied, the direct impact of sea ice retreat on AIS mass loss remains underexplored. Traditional models treat sea ice and AIS as separate systems. It limits their ability to capture localized linkages and cascading feedback. To overcome this, we propose Spatial-Link, a novel graph-based framework that quantifies spatial heterogeneity to capture linkages between sea ice retreat and AIS melt. Our method constructs a spatial graph using Delaunay triangulation of satellite-derived ice change matrices, where nodes represent regions of significant change and edges encode proximity and directional consistency. We extract and statistically validate linkage paths using breadth-first search and Monte Carlo simulations. Results reveal non-local, spatially heterogeneous coupling patterns, suggesting sea ice loss can initiate or amplify downstream AIS melt. Our analysis shows how sea ice retreat evolves over an oceanic grid and progresses toward ice shelves-establishing a direct linkage. To our knowledge, this is the first proposed methodology linking sea ice retreat to AIS melt. Spatial-Link offers a scalable, data-driven tool to improve sea-level rise projections and inform climate adaptation strategies.

The suspect in Charlie Kirk's assassination has been captured, FBI director Kash Patel announced MSNBC sparks outrage for'disgusting' Charlie Kirk comments following Utah shooting Tragedy as Charlie Kirk's wife left behind with two young children after conservative activist is fatally shot A DEI mayor, an inconvenient crime and video they never wanted you to see: MAUREEN CALLAHAN knows why the Left has sympathy for that killer... but none for his victim Sweater weather starts here - the cozy, chic pieces from Soft Surroundings you'll actually wear all season We only had one symptom we dismissed... but then we were diagnosed with the rarest form of melanoma Soft-touch prosecutor let felon walk free... before crook'slit Auburn professor's throat in random attack' I tried the 30 cent'miracle chill pill' before a big event.. now I'm taking it for everything Donald Trump and House Republicans lead prayers for Charlie Kirk's family after conservative star is fatally shot Prince Harry says his father King Charles is'great' following their first meeting in 19 months... which was over a cup of tea and just 55 minutes long Liberal media defends thug who killed Ukrainian woman in cold blood: 'This man was hurting' Knifeman accused of stabbing Ukrainian refugee to death gives chilling reason for the attack... as he speaks for the first time from jail on the murder that shocked America Fox News reveals new lineup and elevates star White House reporter who's sparred with Trump Horrific new details of passenger injuries after they were'thrown' around Delta flight during'severe turbulence' Antarctica's'Doomsday Glacier' is on the verge of COLLAPSING: Huge ice sheet the size of Great Britain could cause global sea levels to rise by 2 FEET, study warns READ MORE: 'Doomsday Glacier' melting'much faster' than previously thought With the potential to cause sea levels across the planet to rise, it's no wonder the Thwaites Glacier has earned the nickname the'Doomsday Glacier.' Now, scientists have revealed concerning findings about how and when the glacier could collapse. Researchers from the British Antarctic Survey (BAS) used underwater robots to take new measurements of the glacier, which is the same size as Great Britain. The data indicates that the Thwaites Glacier and much of the West Antarctic Ice Sheet could be lost entirely by the 23rd century. Worryingly, if it collapses entirely, the experts say global sea levels would rise by two feet (65cm) - plunging huge areas underwater. With the potential to cause seas across the planet to rise, it's no wonder the Thwaites Glacier has earned the nickname the'Doomsday Glacier' The Thwaites Glacier is roughly 74.5 miles (120km) across - the same size as Great Britain or Florida - making it the widest glacier on the planet Ice shelf connected to Antarctic's doomsday glacier is CRACKING The Thwaites Glacier is roughly 74.5 miles (120km) across - the same size as Great Britain or Florida.

Although numerical models provide accurate solutions for ice sheet dynamics based on physics laws, they accompany intensified computational demands to solve partial differential equations. In recent years, convolutional neural networks (CNNs) have been widely used as statistical emulators for those numerical models. However, since CNNs operate on regular grids, they cannot represent the refined meshes and computational efficiency of finite-element numerical models. Therefore, instead of CNNs, this study adopts an equivariant graph convolutional network (EGCN) as an emulator for the ice sheet dynamics modeling. EGCN reproduces ice thickness and velocity changes in the Helheim Glacier, Greenland, and Pine Island Glacier, Antarctica, with 260 times and 44 times faster computation time, respectively. Compared to the traditional CNN and graph convolutional network, EGCN shows outstanding accuracy in thickness prediction near fast ice streams by preserving the equivariance to the translation and rotation of graphs.

Although the finite element approach of the Ice-sheet and Sea-level System Model (ISSM) solves ice dynamics problems governed by Stokes equations quickly and accurately, such numerical modeling requires intensive computation on central processing units (CPU). In this study, we develop graph neural networks (GNN) as fast surrogate models to preserve the finite element structure of ISSM. Using the 20-year transient simulations in the Pine Island Glacier (PIG), we train and test three GNNs: graph convolutional network (GCN), graph attention network (GAT), and equivariant graph convolutional network (EGCN). These GNNs reproduce ice thickness and velocity with better accuracy than the classic convolutional neural network (CNN) and multi-layer perception (MLP). In particular, GNNs successfully capture the ice mass loss and acceleration induced by higher basal melting rates in the PIG. When our GNN emulators are implemented on graphic processing units (GPUs), they show up to 50 times faster computational time than the CPU-based ISSM simulation.

Synthetic Aperture Radar (SAR) imagery is the primary data type used for sea ice mapping due to its spatio-temporal coverage and the ability to detect sea ice independent of cloud and lighting conditions. Automatic sea ice detection using SAR imagery remains problematic due to the presence of ambiguous signal and noise within the image. Conversely, ice and water are easily distinguishable using multispectral imagery (MSI), but in the polar regions the ocean's surface is often occluded by cloud or the sun may not appear above the horizon for many months. To address some of these limitations, this paper proposes a new tool trained using concurrent multispectral Visible and SAR imagery for sea Ice Detection (ViSual\_IceD). ViSual\_IceD is a convolution neural network (CNN) that builds on the classic U-Net architecture by containing two parallel encoder stages, enabling the fusion and concatenation of MSI and SAR imagery containing different spatial resolutions. The performance of ViSual\_IceD is compared with U-Net models trained using concatenated MSI and SAR imagery as well as models trained exclusively on MSI or SAR imagery. ViSual\_IceD outperforms the other networks, with a F1 score 1.60\% points higher than the next best network, and results indicate that ViSual\_IceD is selective in the image type it uses during image segmentation. Outputs from ViSual\_IceD are compared to sea ice concentration products derived from the AMSR2 Passive Microwave (PMW) sensor. Results highlight how ViSual\_IceD is a useful tool to use in conjunction with PMW data, particularly in coastal regions. As the spatial-temporal coverage of MSI and SAR imagery continues to increase, ViSual\_IceD provides a new opportunity for robust, accurate sea ice coverage detection in polar regions.

Antarctica's Thwaites Glacier is'holding on by its fingernails', experts say, after discovering that it has retreated twice as fast as previously thought over the past 200 years. The West Antarctica glacier – which is about the size of Florida – has been an important consideration for scientists trying to make predictions about global sea level rise. The potential impact of its retreat is huge because a total loss of Thwaites and its surrounding icy basins could raise global sea levels by up to 10 feet. That is why it is widely nicknamed the'Doomsday Glacier.' For the first time, scientists mapped in high-resolution a critical area of the seafloor in front of Thwaites that gives them a window into how fast the glacier has retreated and moved in the past.

There is an increasing demand for piloted autonomous underwater vehicles (AUVs) to operate in polar ice conditions. At present, AUVs are deployed from ships and directly human-piloted in these regions, entailing a high carbon cost and limiting the scope of operations. A key requirement for long-term autonomous missions is a long-range route planning capability that is aware of the changing ice conditions. In this paper we address the problem of automating long-range route-planning for AUVs operating in the Southern Ocean. We present the route-planning method and results showing that efficient, ice-avoiding, long-distance traverses can be planned.

As more and more industries take on artificial intelligence to solve some of their biggest challenges, can machines help us understand and fix climate change issues? So your phone recognises your face, and your bank can block any transaction unlike your spending habits. And your online supermarket nudges you with their vegan products just because you've bought that oat milk once, while your online movie platform keeps throwing B-movies at you after you watched that soap opera last month. A growing number of our devices and services are relying on artificial intelligence (AI), a technology that continues to branch out and pop up in more and more areas of our lives. Scientists, entrepreneurs, and governments are leveraging AI to explore solutions for some of society's biggest challenges.

Antarctica's Thwaites glacier has warm water from three directions well under it threatening to destroy the ice sheet and raise global sea levels by up to two feet. A team of scientists from Oregon State University made the most of ice free waters in West Antarctica to look under the glacier - which is about the size of Great Britain. Warm water from the deep ocean is welling up under the glacier from three different directions and mixing under the ice, the researchers discovered. If it collapses it could take other parts of the ice shelf with it and lead to the single largest driver of sea-level rise this century, lead researcher Erin Pettit told Nature. The £39million study involving UK and US scientists was launched after concerns the increasingly unstable glacier may have already started to collapse.

First ever footage of the underside of the'doomsday' Thwaites glacier has been sent back by a robotic yellow submarine dubbed Icefin. Glaciologists have likened the groundbreaking images and video to the first steps on the moon taken by Neil Armstrong in 1969. Early analysis reveals that turbulent warm waters underneath the ice sheet, which is the same size as Britain, are causing an'unstoppable retreat'. Experts have previously predicted that if Thwaites was to melt completely, it would lead to a significant increase in worldwide sea levels of around two feet (65cm). The impact on coastal communities around the world would be catastrophic.