We examine the thermal regime of the Grigoriev ice cap and the Sary-Tor glacier, both located in the inner Tien Shan in Kyrgyzstan. Our findings are important as the ice dynamics can only be understood and modelled precisely if ice temperature is considered correctly in ice flow models. The calibrated parameters of this study can be used in applications with ice flow models for individual ice masses as well as to optimise more general models for large-scale regional simulations.

We present a new approach for modelling debris area and thickness evolution. We implement the module into a combined mass-balance ice-flow model, and we apply it using different climate scenarios to project the future evolution of all glaciers in High Mountain Asia. We show that glacier geometry, volume, and flow velocity evolve differently when modelling explicitly debris cover compared to glacier evolution without the debris-cover module, demonstrating the importance of accounting for debris.

We simulate the current state and future evolution of the Mocho-Choshuenco ice cap in southern Chile (40°S, 72°W) with the ice-sheet model SICOPOLIS. Under different global warming scenarios, we project ice mass losses between 56 % and 97 % by the end of the 21st century. We quantify the uncertainties based on an ensemble of climate models and on the temperature dependence of the equilibrium line altitude. Our results suggest a considerable deglaciation in southern Chile in the next 80 years.

Debris-covered glaciers have a greater extent than their debris-free counterparts due to insulation from the debris cover. However, the transient response to climate change remains poorly understood. We use a numerical model that couples ice dynamics and debris transport and varies the climate signal. We find that debris cover delays the transient response, especially for the extent. However, adding cryokarst features near the terminus greatly enhances the response.

To better estimate the uncertainty in glacier mass change modeling during the 20th century we ran an established model with an ensemble of meteorological data sets. We find that the total ensemble uncertainty, especially in the early 20th century, when glaciological and meteorological observations at glacier locations were sparse, increases considerably compared to individual ensemble runs. This stems from regions with a lot of ice mass but few observations (e.g., Greenland periphery).