Climate change is leading to a global recession of mountain glaciers, and numerical modelling suggests that this will result in the rapid disappearance of many glaciers, impacting water supplies. However, an alternative scenario suggests that increased rock fall and debris flows to valley bottoms will cover glaciers with thick rock debris, slowing melting and transforming glaciers into rock–ice mixtures called rock glaciers. This paper explores these scenarios.

We applied an ice flow model to a flow line from the summit of Dome C to the Beyond EPICA ice core drill site on Little Dome C in Antarctica. Results show that the oldest ice at the drill site may be 1.12 Ma (at an age density of 20 kyr m^-1) and originate from around 15 km upstream. We also discuss the nature of the 200–250 m thick basal layer which could be composed of stagnant ice, disturbed ice or even accreted ice (possibly containing debris).

We propose an alternative electrode to perform Electrical Resistivity Tomography measurements in coarse blocky environments, such as rock glaciers. Compared to the traditional steel spike electrodes, which need to be hammered between the blocks, the proposed steel-net electrodes can be easily pushed between the builders by hand and then removed. Furthermore, the steel-net electrode weighs one-sixth of the steel spike, and is, therefore, easier to carry in challenging mountain environments.

Recent studies have shown that machine learning models are effective at predicting sea ice concentration, yet few have explored the development of such models in an operational context. In this study, we present the development of a machine learning forecasting system which can predict sea ice concentration at 1 km resolution up to 3 d ahead using real-time operational data. The developed forecasts predict the sea ice edge position with better accuracy than physical and baseline forecasts.

An airborne campaign collected unprecedented coincident multi-frequency radar and lidar data over sea ice along a CryoSat-2 and ICESat-2 (CRYO2ICE) orbit in the Weddell Sea, useful for evaluating microwave snow penetration. Ka-band and Ku-band had limited penetration with significant contributions from the air–snow interface, contradicting traditional assumptions with discrepancies between commonly used C/S-band "snow-radar" methodologies, all challenging comparisons of airborne and spaceborne estimates.

We used the Moving-Grid Permafrost Model (MVPM) to simulate the permafrost thermal regime in West Kunlun (55,669 km², NW Qinghai–Tibet Plateau), driven by remote-sensing-based land surface temperature (LST; 1980–2022). The model showed high accuracy and stability. Despite ongoing warming (+0.40 °C per decade), permafrost extent remained stable, reflecting delayed deep responses. The permafrost thermal regime reveals altitude- and soil-dependent responses to climate change and offers valuable insights into thermal states in data-scarce regions.