Under the right topographic and hydrological conditions, lakes may form beneath the large ice sheets. Some of these subglacial lakes are active, meaning that they periodically drain and refill. When a subglacial lake drains rapidly, it may cause the ice surface above to collapse, and here we investigate how to improve the monitoring of active subglacial lakes in Greenland by monitoring how their associated collapse basins change over time.

In this study we developed methods for automatically identifying supraglacial lakes in multiple satellite imagery sources for eight glaciers in Nepal. We identified a substantial seasonal variability in lake area, which was as large as the variability seen across entire decades. These complex patterns are not captured in existing regional-scale datasets. Our findings show that this seasonal variability must be accounted for in order to interpret long-term changes in debris-covered glaciers.

Lakes on glaciers hold large volumes of water which can drain through the ice, influencing estimates of sea level rise. To estimate water volume, we must calculate lake depth. We assessed the accuracy of three satellite-based depth detection methods on a study area in western Greenland and considered the implications for quantifying the volume of water within lakes. We found that the most popular method of detecting depth on the ice sheet scale has higher uncertainty than previously assumed.

The seasonal snowpack provides water resources to billions of people worldwide. Large-scale mapping of snow water equivalent (SWE) with high resolution is critical for many scientific and economics fields. In this work we used the radar remote sensing interferometric synthetic aperture radar (InSAR) to estimate the SWE change between 2 d. The error in the estimated SWE change is less than 2 cm for in situ stations. Additionally, the retrieved SWE using InSAR is correlated with lidar snow depth. 

We used changes in radar echo travel time from multiple airborne flights to estimate changes in snow depths across Idaho for two winters. We compared our radar-derived retrievals to snow pits, weather stations, and a 100 m resolution numerical snow model. We had a strong Pearson correlation and root mean squared error of 10 cm relative to in situ measurements. Our retrievals also correlated well with our model, especially in regions of dry snow and low tree coverage.

Local and large-scale meteorological conditions have been considered in order to explain some peculiar changes of snow grains on the East Antarctic Plateau from 2000 to 2022, by using remote sensing observations and reanalysis. We identified some extreme grain size events on the highest ice divide, resulting from a combination of conditions of low wind speed and low temperature. Moreover, the beginning of seasonal grain growth has been linked to the occurrence of atmospheric rivers.

How fast is the Greenland ice sheet warming? In this study, we compiled 4500+ temperature measurements at 10 m below the ice sheet surface (T_10m) from 1912 to 2022. We trained a machine learning model on these data and reconstructed T_10m for the ice sheet during 1950–2022. After a slight cooling during 1950–1985, the ice sheet warmed at a rate of 0.7 °C per decade until 2022. Climate models showed mixed results compared to our observations and underestimated the warming in key regions.

Aiming to study the long-term influence of an extremely warm climate in the Greenland Ice Sheet contribution to sea level rise, a new regional atmosphere–ice sheet model setup was established. The coupling, explicitly considering the melt–elevation feedback, is compared to an offline method to consider this feedback. We highlight mitigation of the feedback due to local changes in atmospheric circulation with changes in surface topography, making the offline correction invalid on the margins.

We present new projections of the evolution of the Antarctic ice sheet until the end of the millennium, calibrated with observations. We show that the ocean will be the main trigger of future ice loss. As temperatures continue to rise, the atmosphere's role may shift from mitigating to amplifying Antarctic mass loss already by the end of the century. For high-emission scenarios, this may lead to substantial sea-level rise. Adopting sustainable practices would however reduce the rate of ice loss.

Antarctic precipitation is a crucial component of the climate system. Its spatio-temporal variability impacts sea level changes and the interpretation of water isotope measurements in ice cores. To better understand its climatic drivers, we developed water tracers in an atmospheric model to identify moisture source conditions from which precipitation originates. We find that mid-latitude surface winds exert an important control on moisture availability for Antarctic precipitation.

The Brunt Ice Shelf has accelerated rapidly after calving an iceberg in January 2023. A decade of GPS data show that the rate of acceleration in August 2023 was 30 times higher than before calving, and velocity has doubled in 6 months. Satellite velocity maps show the extent of the change. The acceleration is due to loss of contact between the ice shelf and a pinning point known as the McDonald Ice Rumples. The observations highlight how iceberg calving can directly impact ice shelves.

In spite of enhanced technologies, many large cryospheric events remain unreported because of their remoteness, inaccessibility, or poor communications. In this Brief communication, we report on a large ice-debris avalanche that occurred sometime between 16 and 21 August 2022 in the Kanchenjunga Conservation Area (KCA), eastern Nepal. 

The lower part of mountain glaciers is often covered with debris. Knowing the thickness of the debris is important as it influences the melting and future evolution of the affected glaciers. We have developed an open-source approach to map variations in debris thickness on glaciers using a low-cost drone equipped with a thermal infrared camera. The resulting high-resolution maps of debris surface temperature and thickness enable more accurate monitoring and modelling of debris-covered glaciers.

Seasonal snowfall accumulation plays a critical role in climate. The water stored in it is measured by the snow water equivalent (SWE), the amount of water released after completely melting. We demonstrate a Bayesian physical–statistical framework to estimate SWE from airborne X- and Ku-band synthetic aperture radar backscatter measurements constrained by physical snow hydrology and radar models. We explored spatial resolutions and vertical structures that agree well with ground observations.

Shrinkage of the Antarctic ice sheet (AIS) leads to sea level rise. Satellite gravimetry measures AIS mass changes. We apply a new method that overcomes two limitations: low spatial resolution and large uncertainties due to the Earth's interior mass changes. To do so, we additionally include data from satellite altimetry and climate and firn modelling, which are evaluated in a globally consistent way with thoroughly characterized errors. The results are in better agreement with independent data.

A total of 937 seawater paired oxygen isotope (δ¹⁸O)–salinity samples collected during seven cruises on the SE Amundsen Sea between 1994 and 2020 reveal a deep freshwater source with δ¹⁸O − 29.4±1.0‰, consistent with the signature of local ice shelf melt. Local mean meteoric water content – comprised primarily of glacial meltwater – increased between 1994 and 2020 but exhibited greater interannual variability than increasing trend. 

As the temperature increases within a deforming ice aggregate, composed of deuterium (D₂O) ice and water (H₂O) ice, a set of meltwater segregations are produced. These are composed of H₂O and HDO and are located in conjugate shear bands and in compaction bands which accommodate the deformation and weaken the ice aggregate. This has major implications for the passage of meltwater in ice sheets and the formation of the layering recognized in glaciers.

Seismology can help study the mechanism of disintegration of floating ice plates. We conduct a seismic experiment on a frozen lake using a distributed acoustic sensing array. Icequakes and low-frequency events are detected with an artificial intelligence method. Our study demonstrates the merit of distributed acoustic sensing array in illuminating the internal failure process and properties of the ice shelf, which eventually contributes to the understanding and prediction of ice shelf collapse.

Wind-driven snow redistribution affects glacier mass balance. A case study of Hintereisferner glacier in Austria used high-resolution observations and simulations to model snow redistribution. Simulations matched observations, showing the potential of the model for studying snow redistribution on other mountain glaciers.

This research focuses on the interaction between microwave signals and lake ice under wet conditions. Field data collected for Lake Oulujärvi in Finland were used to model backscatter under different conditions. The results of the modelling likely indicate that a combination of increased water content and roughness of different interfaces caused backscatter to increase. These results could help to identify areas where lake ice is unsafe for winter transportation.

Glaciers in western North American outside of Alaska are often overlooked in global studies because their potential to contribute to changes in sea level is small. Nonetheless, these glaciers represent important sources of freshwater, especially during times of drought. We show that these glaciers lost mass at a rate of about 12 Gt yr^-1 for about the period 2013–2021;  the rate of mass loss over the period 2018–2022 was similar. 

We used satellite images to create sea ice maps of Hornsund fjord, Svalbard, for nine seasons and calculated the percentage of the fjord that was covered by ice. On average, sea ice was present in Hornsund for 158 d per year, but it varied from year to year. April was the "iciest'" month and 2019/2020, 2021/22 and 2014/15 were the "iciest'" seasons. Our data can be used to understand sea ice conditions compared with other fjords of Svalbard and in studies of wave modelling and coastal erosion.

Warming ocean temperatures cause considerable ice loss from the Greenland Ice Sheet; however climate models are unable to resolve the complex ocean processes within fjords that influence near-glacier ocean temperatures. Here, we use a computer model to test the accuracy of assumptions that allow climate and ice sheet models to project near-glacier ocean temperatures, and thus glacier melt, into the future. We then develop new methods that improve accuracy by accounting for local ocean processes.

Melt ponds are puddles of meltwater which form on Arctic sea ice in the summer period. They are darker than the ice cover and lead to increased absorption of solar energy. Global climate models need information about the Earth's energy budget. Thus satellite observations are used to monitor the surface fractions of melt ponds, ocean, and sea ice in the entire Arctic. We present a new physically based algorithm that can separate these three surface types with uncertainty below 10 %.

A prerequisite for understanding the local, regional, and hemispherical impacts of Arctic sea-ice decline on the atmosphere is to quantify the effects of sea-ice concentration (SIC) on the sensible and latent heat fluxes in the Arctic. We analyse these effects utilising four data sets called atmospheric reanalyses, and we evaluate uncertainties in these effects arising from inter-reanalysis differences in SIC and in the sensitivity of the latent and sensible heat fluxes to SIC.