We propose here that the resident microbial community can influence the structure of sea ice, particularly near the ocean interface, by lowering the local freezing point through production of, effectively, antifreeze compounds. The result is improved environmental conditions for growth and, possibly, changes to heat transport through the ice. A mathematical model together with laboratory measurements are used to illustrate and support the hypothesis.

Accurate maps of snowfall over the Greenland ice sheet are essential for reliable projections of future sea-level rise. Climate models often struggle to capture realistic snowfall patterns, leading to significant long-term errors. We present a new method that corrects these errors using over two million observations. The corrected snowfall maps can help to reduce uncertainty in sea-level rise projections and improve understanding of Greenland’s proximity to irreversible melting thresholds.

Seismic imaging of subglacial lakes is affected by multiple reflections, guided waves, and source-side ghost effects, which dominate seismic records and complicate imaging. Using wavefield simulations under varied geological scenarios and real data analysis, this study clarifies how these effects arise and tests processing methods to reduce them. 

We tested a new way to improve Arctic sea ice forecasts by adding satellite-based surface brightness, or albedo, into a sea ice model. This approach captures key surface changes like melting and snowfall that affect ice loss. We found it often gives better results when combined with standard data like ice coverage or thickness, especially during the melt season. This method offers a powerful tool for tracking Arctic sea ice in a changing climate.

Heat from inside the Earth beneath Antarctica affects how fast ice melts and how quickly the sea level rises, but direct measurements are very limited. We built a data-driven computer model that learns the complex links between geophysical features and geothermal heat flow and reports confidence. We find lower heat flow in East Antarctica and higher heat flow in West Antarctica, especially near coasts.

In this study we track winter supraglacial lake drainage on the Greenland Ice Sheet. Winter drainage is hard to observe, so we used synthetic aperture radar images to build a method that detects events across ten winter seasons. We find drainage occurs every winter, often in cascades, is most common at lower elevations, and indicates clear links to summer drainage and melt conditions. Winter drainage seldom drives seasonal changes in ice speed, though brief increases can follow cascade events.

We used new satellite radar data from 2025 to map the border where Antarctic glaciers lose contact with the ground and begin to float. This updated map shows recent changes to many glaciers in the Amundsen Sea region, some of which have retreated by several kilometers. Our results help track how Antarctica is responding to climate change and highlight the value of future satellite missions for monitoring ice sheet stability.

Studying Antarctic ice cores is crucial to assess past climate changes, as they hold historical climate data. This study examines multiple ice cores from three sites in coastal Adélie Land to see if combining cores improves data interpretability. It does at two sites, but at a third, wind-driven snow layer mixing limited benefits. We show that using multiple ice cores from one location can better uncover climate history, especially in areas with less wind disturbance.

We quantify elemental carbon and mineral dust in the seasonal snow cover sampled at a high-alpine site (2016–2024). The co-occurrence of these compounds in thermal-optical analysis necessitates a linear laser correction to minimize the bias for elemental carbon. We identify samples containing mineral dust via thermal-optical analysis and compare it to an approach from literature. We approximate mineral dust from thermal-optical analysis data and the composition of dust from long-range transport.

Current satellite monitoring often oversimplifies soil freezing by assuming it happens exactly at 0°C. We analyzed ground data across Canada and found that soil often stays in a partially frozen state for months, even when air temperatures are well below freezing, revealing a major gap in how we track seasonally frozen ground. 

We investigate crevasse initiation by analyzing the artificial drainage of a water-filled cavity at Tête Rousse Glacier (Mont Blanc, France). Using a numerical model, we compute stress fields in response to water level variations in the cavity and compare them to observed crevasse patterns. Results show that a non-linear viscous rheology and a maximum principal stress criterion (with a stress threshold of 100–130 kPa) best predict crevasse occurrence.

By analysing 30 years of satellite SAR (Synthetic Aperture Radar) data, we have found that the number of glacier surges over Svalbard has tripled since 2015. We show that this increase is unlikely to be explained solely by improvements in data quality or by random fluctuations in surge frequency, suggesting that this trend is caused by an external forcing mechanism. Given our incomplete understanding of surge initiation, the cause of the observed threefold increase remains however uncertain.

We identify lakes beneath the glaciers in the Canadian Arctic using satellite measurements over a decade, increasing the number of known subglacial lakes in this area from 2 to 37. These lakes are recharged by billions of cubic meters of water, and the draining of these lakes can lower the ice elevation by more than 100 m. We find three types of subglacial lakes, two of which are primarily located in the Canadian Arctic. When glaciers lose their ice quickly, these lakes become active.

This study introduces innovative methods in cryospheric research by mapping and quantifying multi-decadal snow cover changes in the Western Alps using remote sensing. The normalized trend (nT) index offers a novel metric for analyzing annual mean snow events. This enables intensity analysis of climate change impacts on snow dynamics, highlighting critical vulnerabilities in water management and regional economic systems.

The ocean-facing front of a glacier changes with the seasons. We know this cycle is controlled by the shape and speed of the glacier as well as by the climate, but we do not have a full understanding of these processes. Our study uses 20 years of data and a machine learning model to predict this pattern and identifies which factors matter most. We find that while several factors influence the seasonal cycle, the shape of the glacier plays a key role in how much a glacier changes annually.

This study explores how well the Sentinel-3 satellites measure Antarctic ice sheet elevation, using new detailed maps of slopes and roughness created using the Reference Elevation Model of Antarctica. We found that while the satellites tend to perform well over smoother terrain, they can struggle over more complex surfaces. These findings can improve how we track ice sheet changes and guide future satellite missions, helping us better understand the impact of climate change on polar regions.

This study improves how we track changes in permafrost by testing new ways to use ground temperature data. A set of five simple but powerful metrics was found to give a clearer picture of thawing than current methods. The results also show that the depth where sensors are placed can strongly affect measured warming rates. These findings help make permafrost monitoring more accurate and support better planning for a changing climate.

Nearly 95% of the Greenland ice margin ends on land, where meltwater leaves the ice to supply surrounding ecosystems. Here we show that nearly 30% of this land-terminating margin ends in extremely steep, often vertical sections, previously only described in individual locations. Less than 20% are shallow ramps. Knowledge of these margin shapes and their locations allows us to further investigate what they can potentially tell us about the current ice sheet health and its future evolution.

Antarctic polynyas – areas of open water surrounded by sea ice or sea ice and land – are key players in Antarctic marine ecosystems. Changes in the physical characteristics of polynyas will influence how these ecosystems respond to a changing climate. This work explores how to best compare polynyas identified in satellite data products and climate model data to verify that the model captures important features of Antarctic sea ice and marine ecosystems.

This study presents a fast, physics-guided machine-learning method that downscales coarse climate fields to fine resolution while enforcing conservation of large-scale totals. Trained on regional climate simulations and driven by Earth system model output, it handles extremes and outperforms linear interpolation, providing realistic, high-resolution forcing for ice-sheet models and improving projections of Greenland’s sea-level contribution.