For future sea-level projections, approximating Antarctic precipitation increases through temperature-scaling approaches will remain important, as coupled ice-sheet simulations with regional climate models remain computationally expensive, especially on multi-centennial timescales. We here revisit the relationship between Antarctic temperature and precipitation using different scaling approaches, identifying and explaining regional differences.

Antarctica's ice shelves (the floating extension of the ice sheet) help regulate ice flow. As ice shelves thin or lose contact with the bedrock, the upstream ice tends to accelerate, resulting in increased mass loss. Here, we use an ice sheet model to simulate the effect of seasonal sea surface height variations and see if we can reproduce observed seasonal variability of ice velocity on the ice shelf. When correctly parameterised, the model fits the observations well.

Water flow across the surface of the Greenland Ice Sheet controls the rate of water flow to the glacier bed. Here, we simulate surface water flow for a small catchment on the southwestern Greenland Ice Sheet. Our simulations predict significant differences in the form of surface water flow in high and low melt years depending on the rate and intensity of surface melt. These model outputs will be important in future work assessing the impact of surface water flow on subglacial water pressure.

There is very strong scientific and public interest regarding the snow thickness on Mountain Everest. Previously reported snow depths derived by different methods and instruments ranged from 0.92 to 3.5 m. Our measurements in 2022 provide the first clear radar image of the snowpack at the top of Mount Everest. The snow thickness at Earth's summit was averaged to be 9.5 ± 1.2 m. This updated snow thickness is considerably deeper than values reported during the past 5 decades.

To test the title question, three snow cover products were used in a snow model. Contrary to previous work, higher-spatial-resolution snow cover products only improved the model accuracy marginally. Conclusions are as follows: (1) snow cover and albedo from moderate-resolution sensors continue to provide accurate forcings and (2) finer spatial and temporal resolutions are the future for Earth observations, but existing moderate-resolution sensors still offer value.

Delicate sea floor ridges – corrugation ridges – that form by tidal motion at Antarctic grounding lines record extremely fast retreat of ice streams in the past. Here we use a mathematical model, constrained by real-world observations from Thwaites Glacier, West Antarctica, to explore how corrugation ridges form. We identify till extrusion, whereby deformable sediment is squeezed out from under the ice like toothpaste as it settles down at each low-tide position, as the most likely process.

Sea ice is a dynamic carbon reservoir. Its seasonal growth and melt modify the carbonate chemistry in the upper ocean, with consequences for the Arctic Ocean carbon sink. Yet, the importance of this process is poorly quantified. Using two independent approaches, this study provides new methods to evaluate the error in air–sea carbon flux estimates due to the lack of biogeochemistry in ice in earth system models. Those errors range from 5 % to 30 %, depending on the model and climate projection.

We find that E3SM-HR reproduces the main features of the Antarctic coastal polynyas. Despite the high amount of coastal sea ice production, the densest water masses are formed in the open ocean. Biases related to the lack of dense water formation are associated with overly strong atmospheric polar easterlies. Our results indicate that the large-scale polar atmospheric circulation must be accurately simulated in models to properly reproduce Antarctic dense water formation.

Vertical shear stress (the stress orientation usually associated with vertical gradients in horizontal velocities) is a key component of the stress balance of ice shelves. However, partly due to historical assumptions, vertical shear is often misspoken of today as negligible in ice shelf models. We address this miscommunication, providing conceptual guidance regarding this often misrepresented stress. Fundamentally, vertical shear is required to balance thickness gradients in ice shelves.

Greenland ice sheet melting due to global warming could significantly impact global sea-level rise. The ice sheet's albedo, i.e. how reflective the surface is, affects the melting speed. The ORCHIDEE computer model is used to simulate albedo and snowmelt to make predictions. However, the albedo in ORCHIDEE is lower than that observed using satellites. To correct this, we change model parameters (e.g. the rate of snow decay) to reduce the difference between simulated and observed values.

We assess spatio-temporal permafrost variations in selected rock walls in Norway over the last 120 years. Ground temperature is modelled using the two-dimensional ground heat flux model CryoGrid 2D along nine profiles. Permafrost probably occurs at most sites. All simulations show increasing ground temperature from the 1980s. Our simulations show that rock wall permafrost with a temperature of −1 °C at 20 m depth could thaw at this depth within 50 years.

Understanding ice–ocean interactions under floating ice tongues in Greenland and Antarctica is a major challenge in climate modelling and a source of uncertainty in future sea level projections. We use a high-resolution ocean model to investigate basal melting and melt-driven circulation under the floating tongue of Ryder Glacier, northwestern Greenland. We study the response to oceanic and atmospheric warming. Our results are universal and relevant for the development of climate models.

The estimation of the snow depth in mountains is hard, despite the importance of the snowpack for human societies and ecosystems. We measured the snow depth in mountains by comparing the elevation of points measured with snow from the high-precision altimetric satellite ICESat-2 to the elevation without snow from various sources. Snow depths derived only from ICESat-2 were too sparse, but using external airborne/satellite products results in spatially richer and sufficiently precise snow depths.

The density profile of polar ice sheets is a major unknown in estimating the mass loss using lidar tomography methods. In this paper, we show that combing the active radar data and passive radiometer data can provide an estimation of density properties using the new model we implemented in this paper. The new model includes the short and long timescale variations in the firn and also the refrozen layers which are not included in the previous modeling work.

Our analysis demonstrates the capability of machine learning models in estimating glacier mass balance in terms of performance metrics and dataset availability. Feature importance analysis suggests that ablation features are significant. This is in agreement with the predominantly negative mass balance observations. We show that ensemble tree models typically depict the best performance. However, neural network models are preferable for biased inputs and kernel-based models for smaller datasets.

Spaceborne thermal infrared sensors with kilometer-scale resolution cannot support adequate parameterization of Arctic leads. For the first time, we applied the 30 m resolution data from the Thermal Infrared Spectrometer (TIS) on the emerging SDGSAT-1 to detect Arctic leads. Validation with Sentinel-2 data shows high accuracy for the three TIS bands. Compared to MODIS, the TIS presents more narrow leads, demonstrating its great potential for observing previously unresolvable Arctic leads.

The largest floating glacier mass in Greenland, the 79° N Glacier, is showing signs of instability. We investigate how crack formation at the glacier's calving front has changed over the last decades by using satellite imagery and airborne data. The calving front is about to lose contact to stabilizing ice islands. Simulations show that the glacier will accelerate as a result of this, leading to an increase in ice discharge of more than 5.1 % if its calving front retreats by 46 %.

Sea ice parcels may experience thickness changes primarily through two processes: due to freezing or melting or due to motion relative to other parcels. These processes are independent and will be affected differently in a changing climate. In order to better understand these processes and compare them against models, observational estimates of these process independent from one another are necessary. We present a large spatial- and temporal-scale observational estimate of these processes.

Kyagar Glacier in the Karakoram is well known for its surge history and its frequent blocking of the downstream valley, leading to a series of high-magnitude glacial lake outburst floods. Using it as a test bed, we develop a new approach for quantifying surge behaviour using successive digital elevation models. This method could be applied to other surge studies. Combined with the results from optical satellite images, we also reconstruct the surge process in unprecedented detail.

Ice–albedo feedbacks in the ablation region of the Greenland Ice Sheet are difficult to constrain and model. Surface samples were collected across the 2014 summer melt season from different ice surface colors. On average, concentrations were higher in patches that were visibly dark, compared to medium patches and light patches, suggesting that black carbon aggregation contributed to snow aging, and vice versa. High concentrations are likely due to smoke transport from high-latitude wildfires.

This study reveals permafrost degradation by repeating old geophysical measurements at three Alpine sites. The compared data indicate that ice-poor permafrost is highly affected by temperature warming. The melting of ice-rich permafrost could not be identified. However, complex geomorphic processes are responsible for this rather than external temperature change. We suspect permafrost degradation here as well. In addition, we introduce a new current injection method for data acquisition.

Here, we present high-resolution simulations of glacier mass balance (the gain and loss of ice over a year) and runoff on Svalbard from 1991–2022, one of the fastest warming regions in the Arctic. The simulations are created using the CryoGrid community model. We find a small overall loss of mass over the simulation period of −0.08 m yr⁻¹ but with no statistically significant trend. The average runoff was found to be 41 Gt yr⁻¹, with a significant increasing trend of 6.3 Gt per decade.

We combine deep learning with a regional sea-ice model to correct model errors in the sea-ice dynamics of low-resolution forecasts towards high-resolution simulations. The combined model improves the forecast by up to 75 % and thereby surpasses the performance of persistence. As the error connection can additionally be used to analyse the shortcomings of the forecasts, this study highlights the potential of combined modelling for short-term sea-ice forecasting.

At the end of an Arctic winter, we found ponded water 500 m under a glacier. We explored the chemistry and microbiology of this unique, dark, and cold aquatic habitat to better understand ecology beneath glaciers. The water was occupied by cold-loving and cold-tolerant microbes with versatile metabolisms and broad habitat ranges and was depleted in compounds commonly used by microbes. These results show that microbes can become established beneath glaciers and deplete nutrients within months.

Sea ice has a large interannual variability, and studying its evolution requires long time series of observations. In this paper, we propose the first method to extend Arctic sea ice thickness time series to the ERS-2 altimeter. The developed method is based on a neural network to calibrate past missions on the current one by taking advantage of their differences during the mission-overlap periods. Data are available as monthly maps for each year during the winter period between 1995 and 2021.

Role of Foehn Winds in ice and snow conditions at the Pine Island Glacier, West Antarctica.

The stable isotopes of oxygen and hydrogen in ice cores are routinely analysed for the climate signals which they carry. It has long been known that the system of water veins in ice facilitates isotopic diffusion. Here, mathematical modelling shows that water flow in the veins strongly accelerates the diffusion and the decay of climate signals. The process hampers methods using the variations in signal decay with depth to reconstruct past climatic temperature.

Over the past decade, Greenland has experienced several extreme melt events. With progressing climate change, such extreme melt events can be expected to occur more frequently and potentially become more severe and persistent. Strong melt events may considerably contribute to Greenland's mass loss, which in turn strongly determines future sea level rise. How important these extreme melt events could be in the future is assessed in this study for the first time.

This study demonstrated the response of organic soils in the Arctic tundra to freeze–thaw cycles (FTCs), focusing on the quantitative and qualitative characteristics of dissolved organic carbon (DOC). The highlights found in this study are as follows: (i) FTCs altered DOC properties without decreasing soil microbial activities, and (ii) soil aggregate distribution influenced by FTCs changed DOC characteristics by enhancing microbial activities and altering specific-sized soil pore proportion.