On the ocassion of the Greenland National Day we invite secondary schools to participate in the LIQUIDICE online lesson!

On the ocassion of the World Environmental Day, an event organised under the leadership of the United Nations Environment Programme (UNEP) we invite secondary schools to participate in the LIQUIDICE online lesson! The theme of this year’s edition is “A Global Call for Climate Action”.

The paper “PROMICE and GC-Net automatic weather station dataset for the Greenland Ice Sheet” by Fausto et al. (2026), published in Earth System Science Data, presents a comprehensive and harmonized dataset from the PROMICE (Programme for Monitoring of the Greenland Ice Sheet) and GC-Net (Greenland Climate Network) automatic weather station networks. These long-term observational systems provide critical in situ measurements across the Greenland Ice Sheet, supporting a wide range of glaciological and climate research.

The dataset integrates high-quality observations of key atmospheric and surface variables, including air temperature, humidity, wind speed, radiation fluxes, and surface height changes. By combining multiple monitoring efforts into a unified and consistently processed data product, the study significantly enhances accessibility and usability for the scientific community. Importantly, the inclusion of GPS measurements allows for tracking ice motion, offering valuable insight into ice dynamics alongside surface mass balance processes.

With records spanning more than a decade at several sites, this dataset represents one of the most robust observational foundations for understanding ongoing changes in the Greenland Ice Sheet. It plays a crucial role in improving climate model performance, validating satellite-derived products, and refining projections of future sea-level rise.

The work also highlights the importance of sustained international collaboration in polar research. The LIQUIDICE project contributed to this effort by supporting activities related to data treatment routines, as acknowledged by the authors. This contribution aligns with LIQUIDICE’s mission to advance understanding of ice-climate interactions and their implications for the Earth system.

Read the full paper: https://essd.copernicus.org/articles/18/2829/2026/

“Disappearing winter” paralyzes international research

Spitsbergen, April 2026. This year’s Arctic spring is going down in history as one of the most unpredictable and challenging for science. Three international LIQUIDICE research teams have faced challenges that would have been unthinkable just a decade ago. While the Polish team has been completely blocked by nature, partners from Norway and Italy are fighting for every inch of melting snow.

A paradoxical blockade: sea ice offshore, bare ground on land

The team from two Polish institutions: the Institute of Geophysics, Polish Academy of Sciences and the University of Silesia had planned to conduct key work in April in the area of the Polish Polar Station Hornsund. The plan was ambitious: precise measurements of snow water equivalent in the Fuglebekken catchment, as well as an innovative isotope experiment on the Werenskioldbreen glacier aimed at describing snow evaporation processes.

However, nature created a double barrier. First, the fjord was blocked by dense sea ice, preventing the ship from approaching and unloading the team and equipment. Second, since early April, the western coast of Spitsbergen has been experiencing a record thaw.

In the Longyearbyen area, thermometers showed +4°C, while the norm for April is around -15°C. Instead of 30 cm of compact snow cover, we have bare ground. This made it impossible to reach Hornsund by snowmobile, reports Dr. Bartłomiej Luks from IG PAS.

As a result, for the first time in decades, the Polish team has failed to reach the field and must rely solely on basic monitoring data transmitted by the overwintering staff at the station.

International Struggle for Data: “Water Is Everywhere”

The remaining two LIQUIDICE project teams, although still operational, have been forced to radically change their logistics. Norwegian scientists from NORCE: Robert Ricker and his team working in Adventdalen (near Longyearbyen), found the terrain almost completely devoid of snow. To even use snowmobiles, they must transport them by car far beyond the town, searching for surviving patches of snow. Their work, supported by drones (UAVs), is aimed at calibrating Sentinel-3 satellite data, which confirm the catastrophic condition of the snow cover. After a few days of struggling with (no)snow conditions, they need to abort their fieldwork plans.

University of Svalbard (UNIS) has cancelled all scooter operations until at least next week. But without new snow, it is unlikely that the field season will continue. We will return to Tromsø on Friday. – states Ricker.

Meanwhile, the Italian team from the Institute of Polar Sciences CNR (ISP-CNR) is attempting to operate in Ny-Ålesund, in northern Spitsbergen, where the situation is equally dramatic. Andrea Spolaor reports that “water is everywhere.” Meltwater ponds are forming on glaciers and in coastal areas, and the snow is completely saturated. However, the Italians are using these conditions to study Rain-on-Snow (ROS) events. When rain falls on snow it drastically alters the structure of the cryosphere and is one of the most serious indicators of warming.

The Future of Research Is Remote Sensing

Experts emphasize that documenting these “depressing” images of bare ground and waterlogged snow is now just as important as traditional glacier measurements. Eirik Malnes from the Norwegian institute NORCE highlights the need for a revolution in polar research methodologies.

“Traditional snowmobile expeditions in April are becoming too risky and unpredictable. In the future, we may need to plan them earlier, in mid-winter, although that comes with the challenges of the polar night,” Malnes notes.

The scientist stresses that this year’s crisis demonstrates how crucial it is to develop remote sensing techniques. Satellites and unmanned aerial vehicles are becoming the only viable way to monitor the Arctic as the weather window for human fieldwork rapidly closes.

This is not an anomaly – it is the new reality

The situation in Svalbard leaves little doubt about the direction of climate change. The Arctic is warming several times faster than the rest of the globe, and the disappearing snow cover is affecting not only scientific research, but also local ecosystems and tourism. Despite the logistical paralysis of one of its teams, the LIQUIDICE project is providing some of the most tangible evidence yet of how rapidly we are losing water resources that were once locked in the cryosphere.

March 21st is World Glacier Day, March 22nd World Water Day, and March 23rd Meteorology Day. To celebrate, we invite you to two special lessons connecting these three holidays. Each of these events is crucial for the scientists working on the LIQUIDICE project.

Agreement on the scenarios used in LIQUIDICE, considering CMIP and ISMIP developments and needs of the downscaling task achieved.

Within the framework of LIQUIDICE, global simulations with Earth System Models (ESMs) will be performed, coupled to the vast ice sheets of the northern and southern hemispheres, namely the Greenland (Kalaallit Nunaat) and Antarctic ice sheets. Besides deciphering the impact of these interacting ice sheets on the global and regional climate state, these global simulations will be downscaled to LIQUIDICE’s super-sites. At these super-sites, such as various glaciers in Svalbard and the Monte Rosa valley in the Italian European Alps, local-scale and specialized simulations will be performed to assess the vulnerability of the land cryosphere to climate change and project the cryosphere’s future. Therefore, the global simulations fulfill three purposes.

First, LIQUIDICE will contribute substantially to the Ice Sheet Modeling Intercomparison Project (ISMIP) under the CMIP umbrella. An ISMIP branch is dedicated to systems comprised of ESMs and ice sheet models (ISMs). In these two-way coupled setups, ice sheets respond to the climate computed in the ESM, while the simulated evolution of an ice sheet influences the Earth System; e.g., shrinking ice sheets change the orography in the atmosphere and release meltwater as additional freshwater into the ambient ocean. Since all contributing groups will perform simulations following the same protocol, systematic analyses of all ISMIP simulations will reveal model spread, allowing quantification of uncertainties.

Second, we aim to understand better how the improved representation of large-scale interacting ice sheets affects climate warming trajectories with and without these dynamically evolving ice sheets. In addition, we aspire to identify the strength of feedback loops between ice sheets and the general climate system in our model systems.

Third, we strive to uncover how these interactions leave an imprint on regional to local cryospheric environments ranging from the high Arctic in Greenland and Svalbard, to the temperate European Alps, and beyond to the West Himalaya Asia region. Consequently, we shed light on how the commonly neglected cascading effects of neglecting interacting large-scale ice bodies in downscaled simulations determine the cryospheric future across different landscapes and communities.

This milestone describes the rationale for the selected global climate scenarios. Furthermore, this document lists fields from global simulations that LIQUIDICE partners will use to downscale climate states to regional and local scales, allowing specialized simulations to determine various impacts in collaboration with WP4 on hydrological conditions, tourism development (Italy), electrification and climate adaptation (e.g., Greenland). Finally, it summarizes the existing coupled climate-ice-sheet efforts.

Read the full document Milestone 6 Agreement on the scenarios used in LIQUIDICE, considering CMIP and ISMIP developments and needs of the downscaling task in the library.

After years of planning and 2 years of work writing educational materials. We finally arrived at the debut of “Piccolo Orso e la montagna di Ghiaccio”. Where two polar bears get separated after their ice floe breaks in half separating them. One is rescued by the Regina dei Ghiacci, and the other is found by Mangia Neve. A character who seems good but has ulterior motives! This work was written by Gianfranco di Cataldo, with the composition by Giovanni Sollima in collaboration with Opera Domani and Fenice Education. CNR ISP as part of the LIQUIDICE project are proud to be the scientific partners in this wonderful initiative aimed at young students.

The scientific story behind Piccolo Orso, the title of which in English is Little Bear and the Ice Mountain is clearly in line with LIQUIDICE and its objectives. With sea ice melting due to the ocean being too warm, the ice floes become unstable and break, and the two bears, a brother and sister become separated. The sister is found by the ice queen who cures and looks after here, the brother by Mangianeve (snow eater) who presents himself as someone who’ll bring abundance and fun to where they live. They go looking for the ice queen because she is blocking progress by keeping the mountain cold and find a tourist who decides to help. All the while the ice starts forming black marks due to black carbon deposition accelerating the melting, towards the end mangianeve reveals himself as his clothes are becoming darker and wants to build an ice theme park by stealing the land uncovered by ice melt. In the end all understand that he is the bad guy, not the mysterious ice queen and with a final song the ice starts to heal.

Photo credits: WARREN RAYMOND LEE CAIRNS

We are pleased to share that a new research article was published in the Journal of Glaciology. The study, titled “Bayesian data assimilation on an Arctic glacier: learning from large ensemble twin experiments”, presents cutting-edge advances in cryospheric modelling techniques developed by Wenxue Cao, Kristoffer Aalstad, Louise S. Schmidt, Sebastian Westermann, and Thomas V. Schuler from the Department of Geosciences at the University of Oslo – the LIQUIDICE partner.

This work explores the use of Bayesian data assimilation methods to improve glacier surface mass balance simulations by integrating noisy synthetic observations (such as snow depth and albedo) with ensemble-based modelling frameworks. By leveraging large ensemble twin experiments, the authors demonstrate significant enhancements in predictive accuracy and reduction of uncertainties in glacier model outputs – a crucial step toward refining climate-driven cryospheric predictions.

The approaches outlined in this article are particularly relevant to the objectives of LIQUIDICE, as they offer robust tools for combining observational data with numerical models to better predict glacier behaviour under changing climate conditions. These methods can help improve regional and global glacier projections, complementing the project’s observational and modelling activities across Arctic and high-mountain environments.

This new contribution underscores the importance of advanced statistical and data assimilation methods in enhancing our understanding of glacier processes – insights that are highly valuable for both scientific research and climate impact assessments related to snow, ice, and water resources.

The article can be read in full here.

We are delighted to share a significant new scientific paper published in Remote Sensing (Vol. 18, Issue 1, Article 87) titled “Elevation-Dependent Glacier Albedo Modelling Using Machine Learning and a Multi-Algorithm Satellite Approach in Svalbard” by Dominik Cyran and Dariusz Ignatiuk (University of Silesia, Poland). The article, published on 26 December 2025, tackles one of the central challenges in understanding glacier-climate feedbacks: modelling glacier surface albedo — the fraction of solar radiation reflected by glacier surfaces — across complex Arctic environments. Through this contribution, the LIQUIDICE project supports advancing our ability to assess climate-cryosphere interactions with enhanced predictive capacity, which is essential for planning climate adaptation strategies and sustainable water-resource management.

Background: Why Glacier Albedo Matters

Surface albedo is a fundamental driver of glacier mass balance. Fresh snow reflects most incoming solar radiation, while exposed ice absorbs more energy, accelerating melt. As Arctic warming progresses, understanding and accurately modelling how albedo evolves in space and time is critical for predicting glacier responses to climate change.

What the Study Did

This research developed and validated multiple albedo modelling frameworks using automatic weather station (AWS) data from Hansbreen and Werenskioldbreen glaciers in southern Svalbard. The authors compared different modelling approaches across elevation zones during the 2011 melt season:

• Linear regression models proved highly effective in ablation zones (lower elevations), achieving strong performance (R² = 0.84–0.86) for conditions dominated by snow–ice transitions.
• Neural network models were superior in snow-dominated upper elevation zones (R² = 0.65), where cumulative thermal history drives albedo change.
• Spatial modelling, incorporating elevation-dependent interpolation using temperature lapse rates, extended point models across entire glacier surfaces.
• Satellite validation, using five different albedo algorithms, revealed that while absolute albedo estimates varied by ~12 %, the temporal dynamics (seasonal decline) were robustly captured across algorithms.

These results demonstrate that combining physically informed modelling with data-efficient machine learning methods—and validating against multi-algorithm satellite products—yields practical tools for cryospheric monitoring, even in data-limited Arctic environments.

Key Scientific Insights

• The study provides a data-efficient modelling framework that requires only basic AWS inputs (temperature and precipitation), making it suitable for operational applications in remote Arctic sites.
• Albedo temporal trends were captured consistently across satellite algorithms, even if absolute values differed, highlighting the value of multi-algorithm evaluation for robust temporal validation.
• The elevation-dependent approach underscores how glacier surface processes vary with altitude, indicating that different modelling strategies are optimal for different surface conditions.

The peer-reviewed article is open access and can be read in full here:
Elevation-Dependent Glacier Albedo Modelling Using Machine Learning and a Multi-Algorithm Satellite Approach in Svalbard, Remote Sensing 18(1):87 — https://www.mdpi.com/2072-4292/18/1/87