Many glaciers are thinning rapidly beneath debris cover (loose rock) that reduces melt, including Kennicott Glacier in Alaska. This contradiction has been explained by melt hotspots, such as ice cliffs, scattered within the debris cover. However, at Kennicott Glacier declining ice flow explains the rapid thinning. Through this study, Kennicott Glacier is now the first glacier in Alaska, and the largest glacier globally, where melt across its debris-covered tongue has been rigorously quantified.

When glaciers become snow-free in summer, darker glacier ice is exposed. The ice surface is darker than snow and absorbs more radiation, which increases ice melt. We measured how much radiation is reflected at different wavelengths in the ablation zone of Jamtalferner, Austria. Due to impurities and water on the ice surface there are large variations in reflectance. Landsat 8 and Sentinel-2 surface reflectance products do not capture the full range of reflectance found on the glacier.

Alpine glaciers are retreating at an accelerating rate in a warming climate. Numerical models allow us to study and anticipate these changes, but the performance of a model is difficult to evaluate. So we compared an ice flow model with the long dataset of observations obtained between 1979 and 2015 on Mer de Glace (Mont Blanc area). The model accurately reconstructs the past evolution of the glacier. We simulate the future evolution of Mer de Glace; it could retreat by 2 to 6 km by 2050.

In this field study, we repeated ground-penetrating radar measurements over an active englacial channel network that transports meltwater through the glacier. We successfully imaged the englacial meltwater pathway and were able to delimitate the channel's shape. Meltwater from the glacier can impact the glacier's dynamics if it reaches the ice–bed interface, and therefore monitoring these englacial drainage networks is important to understand how these networks behave throughout a season.

Simple models of glacier dynamics based on volume–area scaling underestimate climate sensitivity and response time of glaciers. Consequently, they may predict a faster response and a smaller long-term glacier loss. These biases in scaling models are established theoretically and are analysed in detail by simulating the step response of a set of 703 Himalayan glaciers separately by three different models: a scaling model, a 2-D shallow-ice approximation model, and a linear-response model.